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f45f3739-0bc8-47fd-bd00-ecad84d2e5c4/8b80399e-47d7-436e-a8f8-ec58c4bf2218/2/0 | Masks detection | High-accuracy solution for medical masks detection. This solution analyzes a given image, detects people in it and reports if they wear protective masks or not. [](https://api4.ai/apis/mask-detection?utm_source=med_mask_rapidapi&utm_medium=endpoints&utm_campaign=rap... | 8.3 | Analyse image and return results | Performs actual image analysis and responds with results.
Image must be a regular JPEG or PNG image (with or without transparency) or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 422 | Missing image/url | {"detail": "Missing image or url field."} | {"type": "object", "properties": {"detail": {"type": "string"}}} |
a5879bf8-a6e9-4f26-99e8-e37c5e680e18/4fa1cc86-9dbc-4970-9842-6734b69dddfa/0/0 | General Detection | This ready-to-use API offers high-accuracy detection of different types of objects, framing them with bounding boxes and predicting their class. ... | 9.1 | Analyse image and return results | Performs actual image analysis and responds with results.
Image must be a regular JPEG or PNG image (with or without transparency) or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 422 | Missing image/url | {"detail": "Missing image or url field."} | {"type": "object", "properties": {"detail": {"type": "string"}}} |
a5879bf8-a6e9-4f26-99e8-e37c5e680e18/4fa1cc86-9dbc-4970-9842-6734b69dddfa/2/0 | General Detection | This ready-to-use API offers high-accuracy detection of different types of objects, framing them with bounding boxes and predicting their class. ... | 9.1 | Analyse image and return results | Performs actual image analysis and responds with results.
Image must be a regular JPEG or PNG image (with or without transparency) or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 200 | Successul detection | {"results": [{"status": {"code": "ok", "message": "Success"}, "name": "image.jpg", "md5": "a447c0aa2b2b89aa6ffb488317c0ab1e", "width": 1024, "height": 768, "entities": [{"kind": "objects", "name": "general-object-detector", "objects": [{"box": [0.26268550753593445, 0.046176016330718994, 0.6867486536502838, 0.6496018171310425], "entities": [{"kind": "classes", "name": "classes", "classes": {"racket": 0.6910336017608643}}]}]}]}]} | {"type": "object", "properties": {"results": {"type": "array", "items": {"type": "object", "properties": {"status": {"type": "object", "properties": {"code": {"type": "string"}, "message": {"type": "string"}}}, "name": {"type": "string"}, "md5": {"type": "string"}, "entities": {"type": "array", "items": {"type": "object", "properties": {"kind": {"type": "string"}, "name": {"type": "string"}, "objects": {"type": "array", "items": {"type": "object", "properties": {"box": {"type": "array", "items": {"type": "number"}}, "entities": {"type": "array", "items": {"type": "object", "properties": {"kind": {"type": "string"}, "name": {"type": "string"}, "classes": {"type": "object"}}}}}}}}}}}}}}} |
a5879bf8-a6e9-4f26-99e8-e37c5e680e18/4fa1cc86-9dbc-4970-9842-6734b69dddfa/2/1 | General Detection | This ready-to-use API offers high-accuracy detection of different types of objects, framing them with bounding boxes and predicting their class. ... | 9.1 | Analyse image and return results | Performs actual image analysis and responds with results.
Image must be a regular JPEG or PNG image (with or without transparency) or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 200 | Unsupported media type | {"results": [{"status": {"code": "failure", "message": "Unsupported media type. Expected one of ['image/jpeg', 'image/png']. Got 'text/plain'."}, "name": "file.txt", "md5": "d41d8cd98f00b204e9800998ecf8427e", "entities": []}]} | {"type": "object", "properties": {"results": {"type": "array", "items": {"type": "object", "properties": {"status": {"type": "object", "properties": {"code": {"type": "string"}, "message": {"type": "string"}}}, "name": {"type": "string"}, "md5": {"type": "string"}, "entities": {"type": "array", "items": {"type": "object", "properties": {"kind": {"type": "string"}, "name": {"type": "string"}, "objects": {"type": "array", "items": {"type": "object", "properties": {"box": {"type": "array", "items": {"type": "number"}}, "entities": {"type": "array", "items": {"type": "object", "properties": {"kind": {"type": "string"}, "name": {"type": "string"}, "classes": {"type": "object"}}}}}}}}}}}}}}} |
a5879bf8-a6e9-4f26-99e8-e37c5e680e18/871986d0-dbd5-4eef-b86a-28903a228c6e/0/0 | General Detection | This ready-to-use API offers high-accuracy detection of different types of objects, framing them with bounding boxes and predicting their class. ... | 9.1 | Get list of algorithms | Service provides alternative algorithms that may be used for image detection.
The idea behind multiple algorithms is to let client try different algorithms to get the best one that matches client's use case. | 200 | Get list of algorithms | ["algo1", "algo2"] | {"type": "array", "items": {"type": "string"}} |
146d552e-1446-45fe-abc7-7b66502d7a1b/23b2693b-70b1-45d8-a84b-547004d68c8d/0/0 | Logo Recognition | Logo & brand recognition API is a combination of logo detection and logo recognition technologies. The API first detects any part of the image that looks like a logo. As a second step, it compares all detected logos to existing logo samples in an internal database, thus returning the name of the brand, if it finds a match. | 7.7 | Logo recognition from image (url) |
For more details contact us | 200 | Response | [{"coordinate": [314, 242, 933, 399], "possible_brands": []}] | {"$schema": "http://json-schema.org/schema#", "type": "array", "items": {"type": "object", "properties": {"coordinate": {"type": "array", "items": {"type": "integer"}}, "possible_brands": {"type": "array"}}, "required": ["coordinate", "possible_brands"]}} |
4ae17a14-48bf-4303-b74a-edba856bbddd/a481b07f-c1b3-4da6-acb3-27f63a9c6515/0/0 | Identity Verification From ID | Quickly check whether a user's face and name match what's on their government-issued ID (driver's license, passport, etc.) | null | verify-identity | Verify the identity of the person from their government issued ID, a picture of themselves and their full name. | 200 | New Example | {"success": "true", "message": "Identity verified!"} | {"type": "object", "properties": {"success": {"type": "string"}, "message": {"type": "string"}}} |
cb5a120d-2611-413b-a0f3-f22a8eff7a2f/a4750cbf-ae70-474f-84d2-ad7f6e96f4ba/0/0 | Macau ID Card OCR | Extracted from the Macao Identity Card, including last name, first name, English name, date of birth and ID number on the back, date of first issue, etc. | 6.3 | Macau ID Card OCR | Support jpg, png, bmp, pdf, tiff, single-frame gif and other formats, the image size does not exceed 10M. | 200 | Response | {"code": "200", "status": "SUCCESS", "date": "11/22/2023 01:24:49 AM", "result": {"rotated_image_height": 609, "image_angle": 0, "rotated_image_width": 480, "item_list": [{"value": "Macau ID Front", "key": "id_type"}, {"value": "\u90ed", "position": {"bottom": 44, "left": 23, "right": 145, "top": 17}, "key": "lastname"}, {"value": "\u660c\u660e", "key": "firstname"}, {"value": "KUOK,CHEONG MENG RICARDO", "position": {"bottom": 76, "left": 24, "right": 260, "top": 59}, "key": "english_name"}, {"value": "KUOK", "position": {"bottom": 76, "left": 24, "right": 260, "top": 59}, "key": "family_name"}, {"value": "CHEONG MENG RICARDO", "position": {"bottom": 76, "left": 24, "right": 260, "top": 59}, "key": "given_name"}, {"value": "6753 2490 2494", "position": {"bottom": 58, "left": 24, "right": 140, "top": 43}, "key": "code"}, {"value": "5215299(8)", "position": {"bottom": 285, "left": 320, "right": 455, "top": 264}, "key": "id_number"}, {"value": "52152998", "key": "id_number_back"}, {"value": "03-12-1960", "position": {"bottom": 203, "left": 25, "right": 131, "top": 184}, "key": "birth"}, {"value": "15-12-1981", "position": {"bottom": 257, "left": 158, "right": 265, "top": 238}, "key": "first_issued"}, {"value": "18-12-2002", "position": {"bottom": 287, "left": 141, "right": 280, "top": 266}, "key": "issued"}, {"value": "18-12-2012", "position": {"bottom": 257, "left": 26, "right": 134, "top": 238}, "key": "validate_date"}, {"value": "1,80", "position": {"bottom": 225, "left": 28, "right": 70, "top": 203}, "key": "height"}, {"value": "M", "position": {"bottom": 209, "left": 347, "right": 381, "top": 192}, "key": "sex"}], "type": "macau_id_card"}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"code": {"type": "string"}, "status": {"type": "string"}, "date": {"type": "string"}, "result": {"type": "object", "properties": {"rotated_image_height": {"type": "integer"}, "image_angle": {"type": "integer"}, "rotated_image_width": {"type": "integer"}, "item_list": {"type": "array", "items": {"type": "object", "properties": {"value": {"type": "string"}, "key": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["key", "value"]}}, "type": {"type": "string"}}, "required": ["image_angle", "item_list", "rotated_image_height", "rotated_image_width", "type"]}}, "required": ["code", "date", "result", "status"]} |
f1b055c3-6856-4f42-ba7d-83c6e71b66bf/082fda1e-21c7-4005-8393-c1e9cdbfee63/0/0 | NSFW Classifier | Content Moderation API for classifying nudity/adult/18+ contents | 0.1 | classify_image_post | Classifying images from (.png / .jpg / .jpeg) files | 422 | Example_1 | {"detail": [{"loc": [], "msg": "", "type": ""}]} | {"title": "HTTPValidationError", "type": "object", "properties": {"detail": {"title": "Detail", "type": "array", "items": {"title": "ValidationError", "required": ["loc", "msg", "type"], "type": "object", "properties": {"loc": {"title": "Location", "type": "array", "items": {"type": "string"}}, "msg": {"title": "Message", "type": "string"}, "type": {"title": "Error Type", "type": "string"}}}}}} |
f1b055c3-6856-4f42-ba7d-83c6e71b66bf/bb0258da-1fea-4618-bcf1-c21b935272d6/0/0 | NSFW Classifier | Content Moderation API for classifying nudity/adult/18+ contents | 0.1 | classify_url__url__post | Classifying image from URL | 422 | Example_1 | {"detail": [{"loc": [], "msg": "", "type": ""}]} | {"title": "HTTPValidationError", "type": "object", "properties": {"detail": {"title": "Detail", "type": "array", "items": {"title": "ValidationError", "required": ["loc", "msg", "type"], "type": "object", "properties": {"loc": {"title": "Location", "type": "array", "items": {"type": "string"}}, "msg": {"title": "Message", "type": "string"}, "type": {"title": "Error Type", "type": "string"}}}}}} |
f1b055c3-6856-4f42-ba7d-83c6e71b66bf/bb0258da-1fea-4618-bcf1-c21b935272d6/1/0 | NSFW Classifier | Content Moderation API for classifying nudity/adult/18+ contents | 0.1 | classify_url__url__post | Classifying image from URL | 200 | Response | {"safe": 0.2469814270734787, "unsafe": 0.7530185580253601} | {"type": "object", "properties": {"safe": {"type": "number"}, "unsafe": {"type": "number"}}} |
ac4b327c-4707-47d1-bfc2-4635dea3393c/e18c9bb2-251e-4188-afd1-d3bfd609b9ee/0/0 | Promity Age and Gender Recognition | API for age and gender recognition | 8.5 | Age and gender by URL | Endpoint for age and gender prediction. Send us link to image, we return position of detected faces and predicted age and gender.
Check out our tutorials for example of usage in Python. | 200 | New Example | {"detections": [{"crop": {"x1": 0.49029475450515747, "y1": 0.5199255347251892, "x2": 0.5589765906333923, "y2": 0.38276559114456177, "score": 0.9992923736572266}, "age": 23, "gender": {"F": 0.999700665473938, "M": 0.0002993345260620117}}, {"crop": {"x1": 0.11643223464488983, "y1": 0.5169875025749207, "x2": 0.1809975504875183, "y2": 0.39529597759246826, "score": 0.998594343662262}, "age": 22, "gender": {"F": 0.002291440963745117, "M": 0.9977085590362549}}, {"crop": {"x1": 0.8563294410705566, "y1": 0.24784332513809204, "x2": 0.917901873588562, "y2": 0.12237813323736191, "score": 0.9980091452598572}, "age": 33, "gender": {"F": 0.9146032929420471, "M": 0.08539670705795288}}, {"crop": {"x1": 0.1482899785041809, "y1": 0.3003842234611511, "x2": 0.20176897943019867, "y2": 0.20043990015983582, "score": 0.9973342418670654}, "age": 19, "gender": {"F": 0.9946532249450684, "M": 0.005346775054931641}}, {"crop": {"x1": 0.598613440990448, "y1": 0.3124071955680847, "x2": 0.6528789401054382, "y2": 0.20392273366451263, "score": 0.9954931735992432}, "age": 24, "gender": {"F": 0.005447328090667725, "M": 0.9945526719093323}}, {"crop": {"x1": 0.7280519008636475, "y1": 0.5563205480575562, "x2": 0.7874197363853455, "y2": 0.4102036952972412, "score": 0.7963488101959229}, "age": 39, "gender": {"F": 0.8345146179199219, "M": 0.16548538208007812}}]} | {"type": "object", "properties": {"detections": {"type": "array", "items": {"type": "object", "properties": {"crop": {"type": "object", "properties": {"x1": {"type": "number"}, "y1": {"type": "number"}, "x2": {"type": "number"}, "y2": {"type": "number"}, "score": {"type": "number"}}}, "age": {"type": "integer"}, "gender": {"type": "object", "properties": {"F": {"type": "number"}, "M": {"type": "number"}}}}}}}} |
ac4b327c-4707-47d1-bfc2-4635dea3393c/925570e0-7f54-4ccd-90cc-dfa6270e3256/0/0 | Promity Age and Gender Recognition | API for age and gender recognition | 8.5 | Age and gender by file | Endpoint for age and gender prediction. Send us image, we return position of detected faces and predicted age and gender.
Check out our tutorials for example of usage in Python. | 200 | New Example | {"detections": [{"crop": {"x1": 0.49029475450515747, "y1": 0.5199255347251892, "x2": 0.5589765906333923, "y2": 0.38276559114456177, "score": 0.9992923736572266}, "age": 23, "gender": {"F": 0.999700665473938, "M": 0.0002993345260620117}}, {"crop": {"x1": 0.11643223464488983, "y1": 0.5169875025749207, "x2": 0.1809975504875183, "y2": 0.39529597759246826, "score": 0.998594343662262}, "age": 22, "gender": {"F": 0.002291440963745117, "M": 0.9977085590362549}}, {"crop": {"x1": 0.8563294410705566, "y1": 0.24784332513809204, "x2": 0.917901873588562, "y2": 0.12237813323736191, "score": 0.9980091452598572}, "age": 33, "gender": {"F": 0.9146032929420471, "M": 0.08539670705795288}}, {"crop": {"x1": 0.1482899785041809, "y1": 0.3003842234611511, "x2": 0.20176897943019867, "y2": 0.20043990015983582, "score": 0.9973342418670654}, "age": 19, "gender": {"F": 0.9946532249450684, "M": 0.005346775054931641}}, {"crop": {"x1": 0.598613440990448, "y1": 0.3124071955680847, "x2": 0.6528789401054382, "y2": 0.20392273366451263, "score": 0.9954931735992432}, "age": 24, "gender": {"F": 0.005447328090667725, "M": 0.9945526719093323}}, {"crop": {"x1": 0.7280519008636475, "y1": 0.5563205480575562, "x2": 0.7874197363853455, "y2": 0.4102036952972412, "score": 0.7963488101959229}, "age": 39, "gender": {"F": 0.8345146179199219, "M": 0.16548538208007812}}]} | {"type": "object", "properties": {"detections": {"type": "array", "items": {"type": "object", "properties": {"crop": {"type": "object", "properties": {"x1": {"type": "number"}, "y1": {"type": "number"}, "x2": {"type": "number"}, "y2": {"type": "number"}, "score": {"type": "number"}}}, "age": {"type": "integer"}, "gender": {"type": "object", "properties": {"F": {"type": "number"}, "M": {"type": "number"}}}}}}}} |
c4a988df-a0ae-49bd-a542-02160c14f1de/5a3af898-e246-4ebd-880e-cab3050c9a8b/0/0 | India AadHaar ID Card OCR | Extract all key fields from India AadHaar ID including AadHaar number, name, year of birth, gender and head portrait. | 5.9 | India AadHaar ID Card OCR | Support jpg, png, bmp, pdf, tiff, single-frame gif and other formats, the image size does not exceed 10M. | 200 | Response | {"code": "200", "status": "SUCCESS", "date": "11/23/2023 01:30:09 AM", "result": {"rotated_image_height": 272, "image_angle": 0, "rotated_image_width": 435, "type": "india_id_card", "details": {"birthday": {"value": ""}, "head_portrait": {"value": 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", "position": {"bottom": 0, "left": 0, "right": 0, "top": 0}}, "license_number": {"value": "4444 5555 6666", "position": {"bottom": 228, "left": 153, "right": 359, "top": 204}}, "gender": {"value": "Aadhaaritis", "position": {"bottom": 155, "left": 213, "right": 278, "top": 141}}, "name": {"value": "Name:Kettan SinghShow:Janhit Mein Jaar", "position": {"bottom": 128, "left": 164, "right": 304, "top": 94}}}}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"code": {"type": "string"}, "status": {"type": "string"}, "date": {"type": "string"}, "result": {"type": "object", "properties": {"rotated_image_height": {"type": "integer"}, "image_angle": {"type": "integer"}, "rotated_image_width": {"type": "integer"}, "type": {"type": "string"}, "details": {"type": "object", "properties": {"birthday": {"type": "object", "properties": {"value": {"type": "string"}}, "required": ["value"]}, "head_portrait": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}, "license_number": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}, "gender": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}, "name": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}}, "required": ["birthday", "gender", "head_portrait", "license_number", "name"]}}, "required": ["details", "image_angle", "rotated_image_height", "rotated_image_width", "type"]}}, "required": ["code", "date", "result", "status"]} |
2c6f4ae3-539e-40ce-ac12-1d85ec8acc2d/3422d64e-fc39-4854-852e-aabc38d601d4/0/0 | Plate Recognizer Snapshot | Plate Recognizer ALPR decodes license plate, vehicle make, model, color and other attributes in 90+ countries. | null | Read Number Plates from an Image | This Snapshot API endpoint reads all license plates from an image.
If you need to detect vehicles and decode license plates from a live camera or video feed, consider using Plate Recognizer Stream. Contact us to request a Free Trial of Stream.
If you need to blur license plates, consider using Plate Recognizer Blur. | 200 | Success | {"processing_time": 288.758, "results": [{"box": {"xmin": 143, "ymin": 481, "xmax": 282, "ymax": 575}, "plate": "nhk552", "region": {"code": "gb", "score": 0.747}, "vehicle": {"score": 0.798, "type": "Sedan", "box": {"xmin": 67, "ymin": 113, "xmax": 908, "ymax": 653}}, "score": 0.904, "candidates": [{"score": 0.904, "plate": "nhk552"}], "dscore": 0.99, "model_make": [{"make": "Riley", "model": "RMF", "score": 0.306}], "color": [{"color": "black", "score": 0.937}], "orientation": [{"orientation": "Front", "score": 0.937}]}], "filename": "1617_7M83K_car.jpg", "version": 1, "camera_id": null, "timestamp": "2020-10-12T16:17:27.574008Z"} | {"type": "object", "properties": {"processing_time": {"type": "number"}, "results": {"type": "array", "items": {"type": "object", "properties": {"box": {"type": "object", "properties": {"xmin": {"type": "integer"}, "ymin": {"type": "integer"}, "xmax": {"type": "integer"}, "ymax": {"type": "integer"}}}, "plate": {"type": "string"}, "region": {"type": "object", "properties": {"code": {"type": "string"}, "score": {"type": "number"}}}, "vehicle": {"type": "object", "properties": {"score": {"type": "number"}, "type": {"type": "string"}, "box": {"type": "object", "properties": {"xmin": {"type": "integer"}, "ymin": {"type": "integer"}, "xmax": {"type": "integer"}, "ymax": {"type": "integer"}}}}}, "score": {"type": "number"}, "candidates": {"type": "array", "items": {"type": "object", "properties": {"score": {"type": "number"}, "plate": {"type": "string"}}}}, "dscore": {"type": "number"}, "model_make": {"type": "array", "items": {"type": "object", "properties": {"make": {"type": "string"}, "model": {"type": "string"}, "score": {"type": "number"}}}}, "color": {"type": "array", "items": {"type": "object", "properties": {"color": {"type": "string"}, "score": {"type": "number"}}}}, "orientation": {"type": "array", "items": {"type": "object", "properties": {"orientation": {"type": "string"}, "score": {"type": "number"}}}}}}}, "filename": {"type": "string"}, "version": {"type": "integer"}, "camera_id": {"type": "null"}, "timestamp": {"type": "string"}}} |
c1eac149-87c8-4fc2-9884-0f3c7bfa46d8/c96a1d3b-4515-4bac-85ca-fb13dbbebd80/0/0 | ImageGenerator Detection | This API can be used to identify the source of an image. It can identify if an image was artificially generated or if it is real. | 5.8 | Image Classification | Provide a base64 encoded image or a URL of an image and the endpoint will provide a classification for it.
It will tell if the image is likely to be fake or if it is a real image. | 200 | Response | [{"class": "Fake", "confidence": 99.99444484710693}, {"class": "Real", "confidence": 0.005556088945013471}] | {"type": "array", "items": {"type": "object", "properties": {"class": {"type": "string"}, "confidence": {"type": "number"}}}} |
05754b15-7b6f-4e97-980a-6a4843f1040e/97f6c1a2-e668-40d5-9a57-870614e0989e/0/0 | License Plate Recognition | Supports license plate recognition in 67 countries. Supported Countries | 8.7 | License Plate Recognition | The size of the input image should be less than 5MB | 200 | Response | {"processing_time": 18, "plates": [{"text": "02\uad6c 0844", "country": "KR", "state": "", "confidence": 98}], "code": "200", "message": "Success"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"processing_time": {"type": "integer"}, "plates": {"type": "array", "items": {"type": "object", "properties": {"text": {"type": "string"}, "country": {"type": "string"}, "state": {"type": "string"}, "confidence": {"type": "integer"}}, "required": ["confidence", "country", "state", "text"]}}, "code": {"type": "string"}, "message": {"type": "string"}}, "required": ["code", "message", "plates", "processing_time"]} |
82c4b55f-25a5-4ca5-a8ae-5506231b4f84/33207aeb-a9e3-4f7d-9f49-3f5b58e6867f/0/0 | ocr | Scene text OCR. Detect & recognize text lines in natural scenes. | null | OCR for scene text detection | Detect text in images and recognize the characters.
Must specify the language using language code.
Currently supporting:
Chinese simplified (horizontal): chi_sim
Korean: ko
| 200 | Response | {"predicted": [{"x": 81, "y": 19, "width": 678, "height": 76, "ocr": "\u8a79\u59ae\u5f17\u8bf4\u5979\u524d\u51e0\u5929\u53c2\u52a0\u4e00\u4e2a\u6ce2\u97f3\u516c\u53f8\u7684\u5546"}, {"x": 82, "y": 54, "width": 681, "height": 146, "ocr": "\u4e1a\u6d3b\u52a8\u3002\u542c\u4ed6\u4eec\u8bf4\u3002\u6700\u8fd1\u4ed6\u4eec\u516c\u53f8\u9047\u5230\u4e86"}, {"x": 85, "y": 87, "width": 682, "height": 212, "ocr": "\u4e00\u70b9\u95ee\u9898\u3002\u6709\u4e00\u67b6\u98de\u673a\u7684\u8ba2\u8d2d\u5ba2\u6237\u7f34\u7eb3\u4e86"}, {"x": 83, "y": 122, "width": 354, "height": 282, "ocr": "\u9996\u7b14\u6b3e\u9879\u4e4b\u540e,"}, {"x": 281, "y": 122, "width": 866, "height": 282, "ocr": "\u56e0\u4e3a\u7ecf\u6d4e\u95ee\u9000\u8ba2\u4e86\u98de\u673a\u3002"}]} | {"type": "object", "properties": {"predicted": {"type": "array", "items": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}, "width": {"type": "integer"}, "height": {"type": "integer"}, "ocr": {"type": "string"}}}}}} |
6dd43074-6785-464c-93d2-b1c2f863b805/7ba91fee-a6b8-4f5f-b969-6c2ac94d19e0/0/0 | Malaysia ID Card OCR | Extract all text on Malaysian ID card, including head portrait. | 6.1 | Malaysia ID Card OCR | Support jpg, png, bmp, pdf, tiff, single-frame gif and other formats, the image size does not exceed 10M. | 200 | Response | {"code": "200", "status": "SUCCESS", "date": "11/22/2023 06:47:11 PM", "result": {"rotated_image_height": 370, "image_angle": 0, "rotated_image_width": 492, "type": "malaysia_id_card", "category": {"citizenship": "one_to_one", "id": "one_to_one", "gender": "one_to_one", "name": "one_to_one", "head_portrait": "one_to_one", "address": "one_to_one"}, "details": {"citizenship": {"value": "WARGANEGARA", "position": {"bottom": 314, "left": 350, "right": 461, "top": 302}}, "id": {"value": "900311-13-6671", "position": {"bottom": 125, "left": 20, "right": 175, "top": 108}}, "gender": {"value": "LELAKI", "position": {"bottom": 327, "left": 398, "right": 453, "top": 314}}, "name": {"value": "GROSEN EOLYANAK HENRY", "position": {"bottom": 246, "left": 13, "right": 248, "top": 235}}, "head_portrait": {"value": 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wJnvtO8ZafrEdsjC2vUJZRnHIr9r/AIOeJ7HxT4I03VrNCI5bVMA9iBzWmY1JNaHl0abhM6bW582r5PG3mvIfHRKX+YWOB3HrXr2rti1kKIM7e9eQ+OBd3N5sS3O0Nk7V6Cu3h9r2mp4Of39mRQ6lL5S5znaO1FQJDMEAwelFfSOWp84m7HvmjSCGzS5x97ORTJ7gs7EfhSWEoGlxgjr0qQsW6qelfmmJ+Nn6XhNKaPjv/gqhq12/w5sfDqp8t3MX347rX5b+LtCfTtTSMtvMjZx6bq/Wf/gpJoCan8PLHVBECbS+Ac4/hY4r8zPjDo9ha+KYXs4OGulVxnoAa6aGIUaVkehHDwq6s9Z+H2jPoPw3tYorNVZrYA7q5zX08V3F2Hu7porGIny1t/vE1614X0yw1Pwfa4TaDAoUGkuPA2lJM6ykMSMhe1YVMRDqethsJ7WKSPmbWPCPjXVdcD6feytZSThnLDkDPeu98FeD9fn1OdLaxdoBwsjcZPrXq+n+BNJinWVdPPJ5Paul03StOtZhGkBjz0GBzXlVsVSloe7gcvdJ3Od+GXghLW73X8HmMydM/drsvjf8M7O80exkghKF4Rt561Y8P29vDqbvCQPk5wOK9I8faMknhGyVo97LCCorkjNX0OqUVGXKz4+174RarBd21wSpgUESK3fNchoPwcttH8XpqtxdyPFC5ZbWQfKSfevqS4t7TUIzbvCodW6YHas1PCNrc3YuRHGcNyGUV30sV7M4a+WKoro8t8N/DTULvxCNd0xFtnOPkj+7t/xrU+N3ha71H4W3cMkOfIUu5zzkZH9a9atNN0+2gCJEisOflGOPSud+K0NjN4B1KBzwbck4HWvQw+O9rUSPHxWB9lTZ8xfAfTHu9Sm06KPawKuD6YNfqn+xJrGpal8LILfUMA2rlB9K/Oj9kzww02t3epRWO6GOPbn3yK/UX9nfwza+F/AtpFa2vl+bEsh9yetejiKikkj52UeU7u9CeUyOMjZXAeLLeO2vSRFnIwea9DvsGFsoWwma4DxWY55fMWILXdlMuSpofO5xBSo3MP7JbH/l1/8AHqKtrEMD6elFfRc77nzvs0eo20ymCOM4OxKnaDC4z+tVtHMe5vMGeKvGREPyjt/FXwGK+Nn3+E1po8s/aj+HKfET4ValoMShpzbl4B/tLyK/KL40eCNciuW1I2+JrScLcRey96/ZbxL5VzaSW0xQhgQd3oa+B/2q/wBnvxQnim/vbfQ5ru1u5WdTaRZIH8qwpVIRaTPcwy9w8l8KeKZE8GWUtnNj9yAw64PpWloniW41W5YTt0GM1iaVpTaZpp0u4VoWgfZ5Lpgg+4NLbEWwlnSMoV7ZwawxnLy3R7WXVPZzSPTNJ8sWqnvVW/vmW7VPNSMFseY56VjeFPFMNyFhlP31x+NHxM02efTUk06bbKFJGK8aEOaWp9VTcVT3Ox0Xxp4Q0pzpc+oQyz7cswI4rqdU+OHhWPQ47W/1WHaFCq5I+T/GvlP/AIQMw3D6he3Mv2mZNvyy45+ma05PhTea/Yy2jahNJj0nxiulJLSxwz0bPatU1TRmvE1rQtRS4t5DnKdqv2uradbwm8mfABOcciuF+A3wxvtFV11K5cwKny75N3PrXQ+K4/7HdoreTdEV+UGmrnTR5OXUTxHrERU3NlPhfY4rmvEmuSa74UutMa5wJIyuCPamNqrXRa1cABu/pS6Po8WrZ0ksQZX2btpOOevFejgYtvmPnM4nGGiO2/Ze+G2m6dYaTYFMPJIrMw/iGe/rX6A+F7KLT9OjtrddiRxBQvoMV4f+z7+zu3h+xsdQ1O88wJGGiTy9uOnrX0DZwJANu3DYxXpc3Oz4+q0wvGChmYZUcEetcJ4ukhe4YY5z6YFdvehvKYLzXEeKhL9pyc/dzXpZb/FPnc2TdEwQZ8fc/Win/vKK+i1PnLs9N0WWNIGWRSeetT3t3DGzYJ96q2F3+5G2MJ6+9Vb67LFlK8mvgMXO1Ro/Rctg5UkyLU7gTRssWM469a5LXdPgumC3EW4HIyTnrXS5LFs+9ZOpAMOThc8kivJqVPeVj26MUlY+EP2hPCKeEfiTqFqiFRdSlgB/nivOZQ6u7GXarcYNfTv7bHg6G30y28YQLzA5jf1w3T618qat4l0wgCMEfNxXbb2sEmdMJezqJlrSbyHRLjzTLnac4q3dfFC0u7kW0wwu7Gc8CuN1TxDBKJCOuPkFcXeaPrur3BaS/e3ic8FTXM6PLI9qGKbiezX/AMRPhzpcqXHii5hldTykX3hW2vx1+Cuk2A1WwuGcyjaIVUbgfevAbDwF4cDmPUL13bH+seXbmtPS/A3w3T9zfXWVB6faDXQoQtqP6wm9T2bTPj/4Hlnaey1L7OFGPLkOM1eg8c2PimweaG4SQDO0qa8Nvvhf4Pvpk/sdjGA3Uyk5/Kug8FWN/wCD92npNvTOc5o9nG2gpYhqNz0ElFk86TG32612Pwq0ddb8YadY2w3GW5XP0yK8wg8S2zEwzR7mz69K93/YqGieIviZH9pkzJbxtIifTFehQjyQ0PnczxCm7H3F4NsG0/TYLZogCkYXOeO1b+P3uf8AZrK019sEY/GtKNw8vXtWqsjw6i0HXDqsZJxXE+MkTLOvXdiuzvBmHlN1cd42Uuzjyto25r0cuv7Y8PMl+5OYWdcD5O3pRVcFcD5jRX058tzHotjdxm2ITPBxz1qK7kVm8zcM/WohcMUY9Oew61DLcBVy3I7mvznH6TZ+n5UksOiRZEZuSOmOtZmrXUECs7gEEEAehovb+KFfNDMgX7zKoxXi37SP7WHgD4T+Fby8GvwTakkLrBbIwJ3EcZwa48PRdV7HpSl7NXZ4B/wUk/aDhg1vTvhxoOqxFYrnfe7TyhPQHH0r5gl13fJILmcBicp83UVwnxS+IGseP/Et94m1e8826upWmZmYk9eBntU1nPceJ9Dtr1JCHWMb8GvYWHVKGpyRxSnOx09nq8xl3PLubPQ+lWzq8288Db3rirDW3sblobgkEYANdjpAtL2ESecDvxuA7V51be57WHrpNXH/AGH+0X3Sxlgeh5qVfACzqGt4JQx6BBya6vRYPD0NqFuZBuToRiur0PXvCdgFmQK7BcgECuJ1WmevH2ckmzitL8MaxpFirvDKAMHLA1PcS3hcKCQGHNdx4j8eaJqFmsSIkWU4BxXlvjjx5pmmFohMu7OFx1rpw8pSmcmLUVDQsXeqJp8xE84XcuMn1rU/Z9+P954A/aD0zVLe+iNrHJsuBI3DKccGvI9b8Uy6hm5DNsVc/erD8NXKfa21Jw2TJneCcivo8PSjUjY+NzGTjI/eHwB4ntfFmh2euafLE8N1bq4MZztz2rrYF+fdjjbX56fsD/tsWfhnSrbwD8Q9R8uA4FpO53YxgBSfTk8197+G/E1hremQ6pYXiSwSrmJo3DDH1FctWlKlNnnxxHOrGtckiPiuK8XCNPMicYBHXNdhPL5kakf3q5Hxim+ZvpXbl7bqo4cwX7hnJ/ZIRwWNFRSRv5jZZvvHtRX1fyPjWzsHvd43L09BWH4v8deHvCOmS6tr2pQ2sUYz5k7D5qwPiJ8WPC/w38FXXiHxHfrEtohaNCwDO3pz1r80v2oP2xvHPxg8Szo2rvHpocpb2UTFQVyeTXw2Iwsq1R6H6fhMRSpUYxPZ/wBsj/goRfX91N8P/hPrTQWp4l1FGIZ/pXxz4n8a6jrJeXU7+a4dz800sjMzfUnkViavr1zLdea8vT7nOcfj3rKu9W81G3OB+NdOHwiorYiviZzdokGo3AYO6yn5ck89vSuj+FGsWsCSaXcykAcjJ7Vxd5I5mCg/Keo9ar6Hqc9hrZYE4YY608VFuBOFV6iueqeKNC+2kvY88Z3LWTa61rOjqLVC5ZOOD1rd8O6ol5YxuSCdvOTUWrWkU0xmjiUZ64rxGu59Ly8sEyCP4n3cNs0dy5VvfNUbn4o6mCph1BwOexFTRaPptzdiC8tc+Z36Uuu+FtJ0yFvs2wlvuDOanlovc0hi58tijcfFXXJ4/Lgld2HA2mobBL/XrpbnVpJiGOSC1R2nh+WILdCPg/eHpWnbym0jaRsDj5Riuil7NRskc9WVe3MZfje+h02EWNrI4LDkg1S0C9aC3SN3OG61m+M9RmvLvaE+UdDTtPEsMSbwemTXsYBt6nzmYycrs9I8K+I30qZH+0MuRktux/8Aqr7X/YJ/bMvfDetQ/Dnxfqbtps7KIZmk3eWewyen4V+fdrqbzICgx2ORXT6Tr2r6ZL59lO6MAuDGQCMdx716NWnGotUfPU6jjM/d7TPEun6paJdRT5Eg3J5bArt+o71leJ2jeFnGDxgH1r8uP2f/ANv74rfDKSPSr3V3vrKMgNbXTZbHoCa+wfh9+3z8KviXYR2mrah/Z13IoD20zZUn69q5cNh5wrXRvjJ82HPU3ClyRk89aKw1+IPgVlDJrdqQRkH7WP8AGivoOaR8t7Nn5ofGX9qHx38UpnXxJrZaAN8sMZIA+orxvXb4yu1yTvUnglcGtq8QS3zLPjCgBmA6msPWmhAZXQjb93A4rz3TUZbH2NOadNIz3ZpYiTFlT0JFZd+8kQzFBlvQitXfbyQeXHu+uKrXD2mftEcbE4xgik0mdCrxijBmRyVdzglqoziWyvNxJIIyOa3LyCMg7I2bIz06GsTX5fNw8cbjYcGsMRGn7PU0o4iPtUd94F1xRbLC+TwK7BJYbq3SQKB1yfWvLvDWomGGCaJCB/FXoGkX5mhDwLkDqOwr5Gv7tRn1+Hl7SiixPYRyowtJQ0meOeaoSaDcJdD7XKzk9i3SprnUBDKZNoXZ0wKqXmvySKWBz/telY2i1qynTs9EWLxo7VfLUcVha1fCOH5Wx6c9KvI090yySn5e+a5zxDeGa7XT4EyN/BArWm1dWJqJqk0zH1qcyTRn1PP0qc3guAskDkKq4ODVLxA6x3QiRCCOvsKi09mSVY0bKk5PvX0uDSUFY+Rx1VczibdperGdhY4z61tWVw0qbwxPvk1z8TxFy6xk89AKtwXTRpt+ZRjqTXoXR43Kkb11ei2Rb2MgYOc5NW9J+JWpWzb1mEZ6q/INc8br7XbNbB2Py5xmsWxvZftZhkQlUJFbU9HoKtfkPaLf4reJzbxlddmxsGP3j+lFeRJ4oaNBGs7YUYFFdHMzz/ZxOp1XWnEc6wvho3y2TyaxL7VZNRZCWwFPIHeneI2YXL4J5lOfequjqplYFR9z0rnqO87HrUX+6RaMyqxkEgVfeq1zqNkudswJHpVHWndXcKxA3HgGsy35Y59aSSN1Zo07jUhIrYGAehTiufvvGGnxXklmljMzpwoU/eNaJ/4+wvbb0rzrxNI6eKbhkcghQQQfc1wYp9DSjbm2PRND8daPHpgiaxuhISwACg4bv+Arp/CnxH02yM8V7a3BWOETsQgwV9vpXiWhyyrcqFlYcv0avSfBYDadIWAJOhtkn6189ioJ3Z9XgqjhQO58R+Jba1W0mitJJTdkeWsDdMjofzH5VgXXxB0yx0j+17u2kUxTmJrWU/O7e3qKm12GFNJ0ZkiUFpYdxC9eG61514gZm8PXl0zEyjUziQn5hz615vs79TqVaUju7v4t6XNZSrpmmXD+UgkYg4ye4/lVj4eLJ4s8RSJJaTILeNZX89ByDmvMo2b7NL8x5znnrkrmvcPhkiL4j1oKgAGmQ4wOnyvXVh6ackZTrSimjgfGk9v/AMJBP5LfKGAOO1Zr3sMcYgtyTnow7VF4lZjrs+WP3m71nxE8c19lhqcVSR8dmFRyqtnT6PqUc0XlqcsFwfr61aivW80QSsfXGa57SXdZTtYj952NamT9tY57V0+yVjyXUdjTjvYEaR2kIxwSO1ZuJBfbFmCiU/L61LFy8gPcVnKzHWhkk4Tj2rWMEkEptxsav9hynkyqKKQO+B85/Oiq5TA//9k=", "position": {"bottom": 291, "left": 328, "right": 474, "top": 105}}, "address": {"value": "LOT 1746TAMAN RIVERVIEWLORONG 1H JALAN DAYA93450 KUCHINGSARAWAK", "position": {"bottom": 337, "left": 15, "right": 191, "top": 272}}}}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"code": {"type": "string"}, "status": {"type": "string"}, "date": {"type": "string"}, "result": {"type": "object", "properties": {"rotated_image_height": {"type": "integer"}, "image_angle": {"type": "integer"}, "rotated_image_width": {"type": "integer"}, "type": {"type": "string"}, "category": {"type": "object", "properties": {"citizenship": {"type": "string"}, "id": {"type": "string"}, "gender": {"type": "string"}, "name": {"type": "string"}, "head_portrait": {"type": "string"}, "address": {"type": "string"}}, "required": ["address", "citizenship", "gender", "head_portrait", "id", "name"]}, "details": {"type": "object", "properties": {"citizenship": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}, "id": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}, "gender": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}, "name": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}, "head_portrait": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}, "address": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}}, "required": ["position", "value"]}}, "required": ["address", "citizenship", "gender", "head_portrait", "id", "name"]}}, "required": ["category", "details", "image_angle", "rotated_image_height", "rotated_image_width", "type"]}}, "required": ["code", "date", "result", "status"]} |
b92bf405-5420-42f8-be17-32348ddbc107/48fc2dd0-ef9c-4741-baae-25d6b96f81bb/0/0 | Vehicle Damage Assessment | Identify over 15 vehicle damage types from 38 car parts. Freemium available. | 9.2 | Main | Main function endpoint | 200 | Output | {"job_id": "4feb7c0c-0705-411b-ae4c-58498d78cf31", "draw_result": true, "output": {"elements": [{"bbox": [99, 217, 167, 308], "damage_category": "crack_and_hole", "damage_color": [75, 100, 0], "damage_id": "6", "damage_location": "front_bumper", "score": 0.839188}, {"bbox": [92, 207, 245, 325], "damage_category": "crack_and_hole", "damage_color": [75, 100, 0], "damage_id": "6", "damage_location": "front_bumper", "score": 0.305776}, {"bbox": [102, 155, 150, 220], "damage_category": "car_light_damage", "damage_color": [50, 140, 0], "damage_id": "11", "damage_location": "right_light", "score": 0.416646}]}, "output_url": "https://sensor-ai.oss-ap-southeast-1.aliyuncs.com/vehicle_damage%2Fdraw-150503.5000_20210714150503.jpg", "url_expiry": "2021/07/14 15:06:04"} | {"type": "object", "properties": {"job_id": {"type": "string"}, "draw_result": {"type": "boolean"}, "output": {"type": "object", "properties": {"elements": {"type": "array", "items": {"type": "object", "properties": {"bbox": {"type": "array", "items": {"type": "integer"}}, "damage_category": {"type": "string"}, "damage_color": {"type": "array", "items": {"type": "integer"}}, "damage_id": {"type": "string"}, "damage_location": {"type": "string"}, "score": {"type": "number"}}}}}}, "output_url": {"type": "string"}, "url_expiry": {"type": "string"}}} |
0234d4ee-c3f6-4dfd-bbd4-cc8635766ee9/afe541b3-19f8-43f0-960a-5fcad4140e88/0/0 | Face Fusion | Based on computer vision technologies such as 3D face and adversarial generative networks, the image fusion operation is performed on the portraits in the stencil image and the fusion image, and the fused image is returned. | 8 | Face Fusion | Face Fusion | 401 | Example | {"message": "Invalid API key in request"} | {"message": {"type": "String", "required": true, "example": "Invalid API key in request", "description": "Error Message."}} |
0234d4ee-c3f6-4dfd-bbd4-cc8635766ee9/afe541b3-19f8-43f0-960a-5fcad4140e88/1/0 | Face Fusion | Based on computer vision technologies such as 3D face and adversarial generative networks, the image fusion operation is performed on the portraits in the stencil image and the fusion image, and the fused image is returned. | 8 | Face Fusion | Face Fusion | 200 | Success | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 0, "data": {"image": ""}} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image": {"type": "String", "required": false, "description": "The result image, returning the Base64 encoding of the image."}}}} |
0234d4ee-c3f6-4dfd-bbd4-cc8635766ee9/afe541b3-19f8-43f0-960a-5fcad4140e88/1/1 | Face Fusion | Based on computer vision technologies such as 3D face and adversarial generative networks, the image fusion operation is performed on the portraits in the stencil image and the fusion image, and the fused image is returned. | 8 | Face Fusion | Face Fusion | 200 | Error | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 400, "error_code_str": "ERROR_PARAMETERS", "error_msg": "image cannot be empty"} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image": {"type": "String", "required": false, "description": "The result image, returning the Base64 encoding of the image."}}}} |
9081683c-d3b3-4f53-b1c2-30a0f5e4b382/987cf249-f65f-43b5-ae5d-16d782256aee/0/0 | Body Recognition | For an input image, it detects all the human bodies in the image and outputs 21 key points of each human body, including the top of the head, the five senses, the neck, the limbs and other parts, and also outputs the coordinate information and the number of human bodies. | 7 | Body Recognition | Body Recognition | 200 | Response | {"message": "success", "data": {"person_num": 4, "person_info": [{"location": {"top": 329.16717529297, "height": 398.73376464844, "score": 0.99482369422913, "left": 83.935195922852, "width": 184.01873779297}, "body_parts": {"left_ear": {"y": 386.134765625, "x": 231.357421875, "score": 0.82972419261932}, "left_wrist": {"y": 522.169921875, "x": 246.904296875, "score": 0.83682531118393}, "top_head": {"y": 347.267578125, "x": 215.810546875, "score": 0.83453011512756}, "left_shoulder": {"y": 432.775390625, "x": 231.357421875, "score": 0.82867068052292}, "right_mouth_corner": {"y": 401.681640625, "x": 204.150390625, "score": 0.85599774122238}, "left_elbow": {"y": 479.416015625, "x": 243.017578125, "score": 0.84861755371094}, "left_mouth_corner": {"y": 401.681640625, "x": 219.697265625, "score": 0.86684691905975}, "right_knee": {"y": 603.791015625, "x": 161.396484375, "score": 0.75707840919495}, "right_hip": {"y": 529.943359375, "x": 141.962890625, "score": 0.79752606153488}, "neck": {"y": 413.341796875, "x": 200.263671875, "score": 0.80784571170807}, "left_knee": {"y": 599.904296875, "x": 176.943359375, "score": 0.77508634328842}, "right_wrist": {"y": 506.623046875, "x": 106.982421875, "score": 0.87072920799255}, "right_ankle": {"y": 677.638671875, "x": 169.169921875, "score": 0.81904417276382}, "left_eye": {"y": 382.248046875, "x": 223.583984375, "score": 0.90387237071991}, "left_ankle": {"y": 665.978515625, "x": 165.283203125, "score": 0.62612092494965}, "right_elbow": {"y": 463.869140625, "x": 122.529296875, "score": 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"score": {"type": "number"}}, "required": ["score", "x", "y"]}, "right_hip": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "neck": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "left_knee": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "right_wrist": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "right_ankle": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "left_eye": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "left_ankle": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "right_elbow": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "left_hip": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "nose": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "right_ear": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "right_shoulder": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}, "right_eye": {"type": "object", "properties": {"y": {"type": "number"}, "x": {"type": "number"}, "score": {"type": "number"}}, "required": ["score", "x", "y"]}}, "required": ["left_ankle", "left_ear", "left_elbow", "left_eye", "left_hip", "left_knee", "left_mouth_corner", "left_shoulder", "left_wrist", "neck", "nose", "right_ankle", "right_ear", "right_elbow", "right_eye", "right_hip", "right_knee", "right_mouth_corner", "right_shoulder", "right_wrist", "top_head"]}}, "required": ["body_parts", "location"]}}}, "required": ["person_info", "person_num"]}, "code": {"type": "integer"}}, "required": ["code", "data", "message"]} |
22eec1a2-5656-4f15-83cf-981391b35e6b/f78cf375-10d4-4c96-8f5f-20d03496bb23/0/0 | thai-national-id | Thai National ID Card OCR -> Doc: https://docs.iapp.co.th/thai-national-id-card-version-3-api-documentation and Postman Example: https://www.getpostman.com/collections/b643e60f146e6f37858c | 8.3 | Back Card (v3.5) | Back Card OCR | 200 | New Example | {"back_number": "JT0-1740123-05", "back_number_status": 1, "detection_score": 0.987130731344223, "error_message": "", "process_time": 2.107041120529175, "request_id": "1dcc2bdb-bcba-43e4-810e-5ca183b44566#81807"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"back_number": {"type": "string"}, "back_number_status": {"type": "integer"}, "detection_score": {"type": "number"}, "error_message": {"type": "string"}, "process_time": {"type": "number"}, "request_id": {"type": "string"}}, "required": ["back_number", "back_number_status", "detection_score", "error_message", "process_time", "request_id"]} |
22eec1a2-5656-4f15-83cf-981391b35e6b/2ea7d7dd-60d2-43c2-ba8e-57824618354a/0/0 | thai-national-id | Thai National ID Card OCR -> Doc: https://docs.iapp.co.th/thai-national-id-card-version-3-api-documentation and Postman Example: https://www.getpostman.com/collections/b643e60f146e6f37858c | 8.3 | Front Card (v3.5) | Front Card OCR | 200 | New Example | {"address": "33/349 \u0e2b\u0e21\u0e39\u0e48\u0e17\u0e35\u0e48 7 \u0e15.\u0e2b\u0e19\u0e2d\u0e07\u0e1b\u0e23\u0e37\u0e2d \u0e2d.\u0e1a\u0e32\u0e07\u0e25\u0e30\u0e21\u0e38\u0e07 \u0e08.\u0e0a\u0e25\u0e1a\u0e38\u0e23\u0e35", "alley": "", "detection_score": 0.9819779147704442, "district": "\u0e1a\u0e32\u0e07\u0e25\u0e30\u0e21\u0e38\u0e07", "en_dob": "22 Mar 1957", "en_expire": "21 Jan 2025", "en_fname": "Bunyang", "en_init": "Mrs.", "en_issue": "25 Jul 2016", "en_lname": "Lopez", "en_name": "Mrs. Bunyang Lopez", "error_message": "", "face": 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"gender": "Female", "home_address": "33/349 \u0e2b\u0e21\u0e39\u0e48\u0e17\u0e35\u0e48 7", "house_no": "33/349", "id_number": "3411700830334", "id_number_status": 1, "lane": "", "postal_code": "20150", "process_time": 3.3079464435577393, "province": "\u0e0a\u0e25\u0e1a\u0e38\u0e23\u0e35", "religion": "", "request_id": null, "road": "", "sub_district": "\u0e2b\u0e19\u0e2d\u0e07\u0e1b\u0e23\u0e37\u0e2d", "th_dob": "22 \u0e21\u0e35.\u0e04. 2500", "th_expire": "21 \u0e21.\u0e04. 2568", "th_fname": "\u0e1a\u0e38\u0e0d\u0e22\u0e31\u0e07", "th_init": "\u0e19\u0e32\u0e07", "th_issue": "25 \u0e01.\u0e04. 2559", "th_lname": "\u0e42\u0e25\u0e40\u0e1b\u0e0a", "th_name": "\u0e19\u0e32\u0e07 \u0e1a\u0e38\u0e0d\u0e22\u0e31\u0e07 \u0e42\u0e25\u0e40\u0e1b\u0e0a", "village": "", "village_no": "7"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"address": {"type": "string"}, "alley": {"type": "string"}, "detection_score": {"type": "number"}, "district": {"type": "string"}, "en_dob": {"type": "string"}, "en_expire": {"type": "string"}, "en_fname": {"type": "string"}, "en_init": {"type": "string"}, "en_issue": {"type": "string"}, "en_lname": {"type": "string"}, "en_name": {"type": "string"}, "error_message": {"type": "string"}, "face": {"type": "string"}, "gender": {"type": "string"}, "home_address": {"type": "string"}, "house_no": {"type": "string"}, "id_number": {"type": "string"}, "id_number_status": {"type": "integer"}, "lane": {"type": "string"}, "postal_code": {"type": "string"}, "process_time": {"type": "number"}, "province": {"type": "string"}, "religion": {"type": "string"}, "request_id": {"type": "null"}, "road": {"type": "string"}, "sub_district": {"type": "string"}, "th_dob": {"type": "string"}, "th_expire": {"type": "string"}, "th_fname": {"type": "string"}, "th_init": {"type": "string"}, "th_issue": {"type": "string"}, "th_lname": {"type": "string"}, "th_name": {"type": "string"}, "village": {"type": "string"}, "village_no": {"type": "string"}}, "required": ["address", "alley", "detection_score", "district", "en_dob", "en_expire", "en_fname", "en_init", "en_issue", "en_lname", "en_name", "error_message", "face", "gender", "home_address", "house_no", "id_number", "id_number_status", "lane", "postal_code", "process_time", "province", "religion", "request_id", "road", "sub_district", "th_dob", "th_expire", "th_fname", "th_init", "th_issue", "th_lname", "th_name", "village", "village_no"]} |
66faa20d-2bf4-4a30-beb2-16bfd2fc05a0/6d265551-d077-4d13-9794-c07651b0ff68/0/0 | Automatic removal of watermarks or handwritten text | Automatically detects handwritten or watermarked text in document images and removes it
See the functional effects | 8.4 | Automatic removal of watermarks or handwritten text | Support jpg, png, BMP, pdf, tiff, single frame gif, etc., image size not more than 10M | 200 | Response | {"code": "200", "image_result": "https://seaout.oss-accelerate.aliyuncs.com/temp/xxxxxxxxxxxxxx.png", "msg": "Success"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"code": {"type": "string"}, "image_result": {"type": "string"}, "msg": {"type": "string"}}, "required": ["code", "image_result", "msg"]} |
a1e468a5-1dfb-45e1-b678-6d37fbade277/508645e9-ec03-4600-8c62-d03a43e3f492/0/0 | Face Recognition | Card2G Face Recognition Services: Unleashing the Power of Secure and Seamless Identification | 7 | face verification file upload | Card2G's Face Verification API ensures secure matching of photo IDs, determining if two faces belong to the same person. Supports images up to 5MB, ranging from 50 to 4000 pixels | 200 | New Example | {"error": 0, "message": "The two faces belong to the same person.", "SimilarPercent": 60, "execution_time": 0.4952874183654785} | {"error": {"type": "integer"}, "message": {"type": "string"}, "SimilarPercent": {"type": "integer"}, "execution_time": {"type": "number"}} |
8ddaec23-fb4d-45fe-90a5-e0d2b749c8b8/34492825-39c4-4403-9402-268d70795e46/0/0 | AI Face Slimming | Based on AI algorithm to automatically detect and analyze the five features of the face, it generates images of the face after the five features are adjusted and slimmed down. When the image contains more than one person, up to 3 faces can be processed. | null | AI Face Slimming | AI Face Slimming | 401 | Example | {"message": "Invalid API key in request"} | {"message": {"type": "String", "required": true, "example": "Invalid API key in request", "description": "Error Message."}} |
8ddaec23-fb4d-45fe-90a5-e0d2b749c8b8/34492825-39c4-4403-9402-268d70795e46/1/0 | AI Face Slimming | Based on AI algorithm to automatically detect and analyze the five features of the face, it generates images of the face after the five features are adjusted and slimmed down. When the image contains more than one person, up to 3 faces can be processed. | null | AI Face Slimming | AI Face Slimming | 200 | Success | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 0, "data": {"image_url": "Temporary address"}} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image_url": {"type": "String", "required": false, "description": "Resulting image URL address. **Note**: The URL address is a temporary address, valid for 1 day, after which it will not be accessible."}}}} |
8ddaec23-fb4d-45fe-90a5-e0d2b749c8b8/34492825-39c4-4403-9402-268d70795e46/1/1 | AI Face Slimming | Based on AI algorithm to automatically detect and analyze the five features of the face, it generates images of the face after the five features are adjusted and slimmed down. When the image contains more than one person, up to 3 faces can be processed. | null | AI Face Slimming | AI Face Slimming | 200 | Error | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 400, "error_code_str": "ERROR_PARAMETERS", "error_msg": "image cannot be empty"} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image_url": {"type": "String", "required": false, "description": "Resulting image URL address. **Note**: The URL address is a temporary address, valid for 1 day, after which it will not be accessible."}}}} |
3b769acf-5d79-4078-b570-a9abc63c7d6e/be1a40e2-8308-466a-a83b-f6bedfdfc984/0/0 | AI Makeup | Based on AI algorithm to simulate realistic makeup effect, it further enhances the face beautification effect by adding lipstick, highlighter, whole makeup and other makeup materials. Users can choose different beauty types and match with personalized beauty materials to complete the makeup look. | 6.8 | AI Makeup | AI Makeup | 401 | Example | {"message": "Invalid API key in request"} | {"message": {"type": "String", "required": true, "example": "Invalid API key in request", "description": "Error Message."}} |
3b769acf-5d79-4078-b570-a9abc63c7d6e/be1a40e2-8308-466a-a83b-f6bedfdfc984/1/0 | AI Makeup | Based on AI algorithm to simulate realistic makeup effect, it further enhances the face beautification effect by adding lipstick, highlighter, whole makeup and other makeup materials. Users can choose different beauty types and match with personalized beauty materials to complete the makeup look. | 6.8 | AI Makeup | AI Makeup | 200 | Success | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 0, "data": {"image_url": "Temporary address"}} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image_url": {"type": "String", "required": false, "description": "Resulting image URL address. **Note**: The URL address is a temporary address, valid for 1 day, after which it will not be accessible."}}}} |
3b769acf-5d79-4078-b570-a9abc63c7d6e/be1a40e2-8308-466a-a83b-f6bedfdfc984/1/1 | AI Makeup | Based on AI algorithm to simulate realistic makeup effect, it further enhances the face beautification effect by adding lipstick, highlighter, whole makeup and other makeup materials. Users can choose different beauty types and match with personalized beauty materials to complete the makeup look. | 6.8 | AI Makeup | AI Makeup | 200 | Error | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 400, "error_code_str": "ERROR_PARAMETERS", "error_msg": "image cannot be empty"} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image_url": {"type": "String", "required": false, "description": "Resulting image URL address. **Note**: The URL address is a temporary address, valid for 1 day, after which it will not be accessible."}}}} |
93ccda0b-29b8-4ee2-9c9c-77502642f95b/5c62348b-5e6f-452c-b1e3-0afa82f5751a/0/0 | APIvalidFace | The APIvalidFace validates sent faces by comparing them with registered faces, with the return being a "True" or "False" | null | Delete face image | This endpoint delete face image | 200 | New Example | {"deleted_face": ""} | {"type": "object", "properties": {"deleted_face": {"type": "string"}}} |
93ccda0b-29b8-4ee2-9c9c-77502642f95b/4d7a72e9-1706-416f-9fe9-49a459e6bbba/0/0 | APIvalidFace | The APIvalidFace validates sent faces by comparing them with registered faces, with the return being a "True" or "False" | null | Face Recognition | This endpoint recognize the face image | 200 | New Example | {"know_face": "", "face_name": "", "base64_valid": ""} | {"type": "object", "properties": {"know_face": {"type": "string"}, "face_name": {"type": "string"}, "base64_valid": {"type": "string"}}} |
93ccda0b-29b8-4ee2-9c9c-77502642f95b/91b3252f-d1a1-4293-9dc4-7f784a4aa9fd/0/0 | APIvalidFace | The APIvalidFace validates sent faces by comparing them with registered faces, with the return being a "True" or "False" | null | Register of face image | This endpoint register face image | 200 | New Example | {"image_save": ""} | {"type": "object", "properties": {"image_save": {"type": "string"}}} |
d52236fa-7ecf-4f92-8dd2-db4d922dcf9b/a0598b35-153c-4626-98ad-cfffaa44fee5/0/0 | Photo retouching | Using advanced image processing technology, the input face picture is intelligently changed into beauty. It can help the beauty ability of cell phone manufacturers, beauty apps and other camera classes to achieve sharpening of skin, skin tone whitening, face slimming, adjustment of five features, spot and acne treatment in one click intelligently. Can also be applied to interactive entertainment and other scenarios, such as live streaming, short video, social networking platforms, easily enha... | null | Photo retouching | Photo retouching | 401 | Example | {"message": {"type": "String", "required": true, "example": "Invalid API key in request", "description": "Error Message."}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"message": {"type": "object", "properties": {"type": {"type": "string"}, "required": {"type": "boolean"}, "example": {"type": "string"}, "description": {"type": "string"}}, "required": ["description", "example", "required", "type"]}}, "required": ["message"]} |
d52236fa-7ecf-4f92-8dd2-db4d922dcf9b/a0598b35-153c-4626-98ad-cfffaa44fee5/1/0 | Photo retouching | Using advanced image processing technology, the input face picture is intelligently changed into beauty. It can help the beauty ability of cell phone manufacturers, beauty apps and other camera classes to achieve sharpening of skin, skin tone whitening, face slimming, adjustment of five features, spot and acne treatment in one click intelligently. Can also be applied to interactive entertainment and other scenarios, such as live streaming, short video, social networking platforms, easily enha... | null | Photo retouching | Photo retouching | 200 | Success | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 0, "data": {"image": ""}} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image": {"type": "String", "required": false, "description": "The result image, returning the Base64 encoding of the image."}}}} |
d52236fa-7ecf-4f92-8dd2-db4d922dcf9b/a0598b35-153c-4626-98ad-cfffaa44fee5/1/1 | Photo retouching | Using advanced image processing technology, the input face picture is intelligently changed into beauty. It can help the beauty ability of cell phone manufacturers, beauty apps and other camera classes to achieve sharpening of skin, skin tone whitening, face slimming, adjustment of five features, spot and acne treatment in one click intelligently. Can also be applied to interactive entertainment and other scenarios, such as live streaming, short video, social networking platforms, easily enha... | null | Photo retouching | Photo retouching | 200 | Error | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 400, "error_code_str": "ERROR_PARAMETERS", "error_msg": "image cannot be empty"} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image": {"type": "String", "required": false, "description": "The result image, returning the Base64 encoding of the image."}}}} |
639123be-c691-47a5-ad9b-6cd1d8f40189/de378bce-cd2e-494f-992a-b2a192cea636/0/0 | Face and medical mask detection | This API detects faces and the presence of medical masks, identifies if masks are being worn correctly | 0.1 | Detect faces and med masks | 200 | OK Example | {"status": "success", "result": [{"box": {"bottom": 186, "left": 795, "right": 902, "top": 55}, "medmask": [{"confidence": 1, "name": "incorrect"}, {"confidence": 7.375238e-09, "name": "correct"}, {"confidence": 8.7846475e-12, "name": "none"}]}, {"box": {"bottom": 314, "left": 704, "right": 809, "top": 191}, "medmask": [{"confidence": 1, "name": "incorrect"}, {"confidence": 3.6062854e-08, "name": "correct"}, {"confidence": 1.4148969e-09, "name": "none"}]}, {"box": {"bottom": 275, "left": 47, "right": 156, "top": 147}, "medmask": [{"confidence": 1, "name": "correct"}, {"confidence": 3.4107838e-11, "name": "none"}, {"confidence": 1.5513642e-11, "name": "incorrect"}]}, {"box": {"bottom": 293, "left": 396, "right": 509, "top": 165}, "medmask": [{"confidence": 1, "name": "incorrect"}, {"confidence": 2.0485738e-08, "name": "correct"}, {"confidence": 1.912905e-10, "name": "none"}]}, {"box": {"bottom": 285, "left": 212, "right": 319, "top": 154}, "medmask": [{"confidence": 0.99999917, "name": "incorrect"}, {"confidence": 6.8569113e-07, "name": "correct"}, {"confidence": 9.8483575e-08, "name": "none"}]}, {"box": {"bottom": 338, "left": 592, "right": 690, "top": 215}, "medmask": [{"confidence": 1, "name": "correct"}, {"confidence": 1.4383935e-12, "name": "none"}, {"confidence": 2.6899996e-13, "name": "incorrect"}]}, {"box": {"bottom": 246, "left": 579, "right": 685, "top": 122}, "medmask": [{"confidence": 0.95955884, "name": "correct"}, {"confidence": 0.04041219, "name": "none"}, {"confidence": 2.9026376e-05, "name": "incorrect"}]}, {"box": {"bottom": 284, "left": 296, "right": 364, "top": 187}, "medmask": [{"confidence": 0.99989057, "name": "correct"}, {"confidence": 0.000104147104, "name": "incorrect"}, {"confidence": 5.2193473e-06, "name": "none"}]}, {"box": {"bottom": 283, "left": 1035, "right": 1136, "top": 154}, "medmask": [{"confidence": 0.68013155, "name": "correct"}, {"confidence": 0.29739606, "name": "incorrect"}, {"confidence": 0.022472344, "name": "none"}]}, {"box": {"bottom": 340, "left": 947, "right": 1014, "top": 219}, "medmask": [{"confidence": 0.99989855, "name": "incorrect"}, {"confidence": 0.000100513374, "name": "correct"}, {"confidence": 9.1663736e-07, "name": "none"}]}], "message": "10 faces detected"} | {"type": "object", "properties": {"status": {"type": "string"}, "result": {"type": "array", "items": {"type": "object", "properties": {"box": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}}, "medmask": {"type": "array", "items": {"type": "object", "properties": {"confidence": {"type": "number"}, "name": {"type": "string"}}}}}}}, "message": {"type": "string"}}} |
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c3b4bf30-f930-4094-b29c-ffb1b8d8af1b/56d50eec-e65b-4d99-8ea6-408d4da629bd/0/0 | NSFW Image Classification | Use our Content Moderation API to flag possible inappropriate/ nude / adult content in your images. | 8.4 | NSFW Image Classification (Upload file) | Use our Content Moderation API to flag possible inappropriate content in your images. | 200 | New Example | [{"className": "Porn", "probability": 0.9929075241088867}, {"className": "Sexy", "probability": 0.002984800608828664}, {"className": "Hentai", "probability": 0.002632501535117626}, {"className": "Neutral", "probability": 0.0014369783457368612}, {"className": "Drawing", "probability": 3.809928966802545e-05}] | {"type": "array", "items": {"type": "object", "properties": {"className": {"type": "string"}, "probability": {"type": "number"}}}} |
c3b4bf30-f930-4094-b29c-ffb1b8d8af1b/c5f5806e-db74-4ecf-a8a6-0664f6e8930d/0/0 | NSFW Image Classification | Use our Content Moderation API to flag possible inappropriate/ nude / adult content in your images. | 8.4 | NSFW Image Classification | Use our Content Moderation API to flag possible inappropriate content in your images. | 200 | Response | [{"className": "Porn", "probability": 0.9929075241088867}, {"className": "Sexy", "probability": 0.002984800608828664}, {"className": "Hentai", "probability": 0.002632501535117626}, {"className": "Neutral", "probability": 0.0014369783457368612}, {"className": "Drawing", "probability": 3.809928966802545e-05}] | {"$schema": "http://json-schema.org/schema#", "type": "array", "items": {"type": "object", "properties": {"className": {"type": "string"}, "probability": {"type": "number"}}, "required": ["className", "probability"]}} |
abcdd064-b897-40a8-8bbe-c69359211e5e/b399676b-fcf8-48a2-91ba-a864766614ce/0/0 | Color Detection | Detect Colors of the Objects in a Image | null | Image Color Analysis | This endpoint responds with all the colors present in an image. Since white and black are prominent colors, it is advisable to consider the next color apart from White and Black. | 200 | Colors in Image | {"colors": {"black": 0.4, "blue": 0.3, "silver": 0.2, "white": 0.1}, "status": "success"} | {"type": "object", "properties": {"colors": {"type": "object", "properties": {"black": {"type": "number"}, "blue": {"type": "number"}, "silver": {"type": "number"}, "white": {"type": "number"}}}, "status": {"type": "string"}}} |
9b9106be-ecf1-491c-a21b-1fc72657a3ef/dd26ddb0-c16c-420f-a709-c1871a3f23b6/0/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | analytics | 200 | null | {"errorCode": 0, "errorMessage": "", "faces": [{"quality": 0, "faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}, "faceAnalytics": {"age": "", "gender": "", "emotion": ""}}]} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "faces": {"type": ["array", "null"], "items": {"type": "object", "properties": {"quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}, "faceAnalytics": {"type": "object", "properties": {"age": {"type": ["string", "null"]}, "gender": {"type": ["string", "null"]}, "emotion": {"type": ["string", "null"]}}, "additionalProperties": false}}, "additionalProperties": false}}}, "additionalProperties": false} |
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9b9106be-ecf1-491c-a21b-1fc72657a3ef/dd26ddb0-c16c-420f-a709-c1871a3f23b6/1/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | analytics | 200 | null | {"errorCode": 0, "errorMessage": "", "faces": [{"quality": 0, "faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}, "faceAnalytics": {"age": "", "gender": "", "emotion": ""}}]} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "faces": {"type": ["array", "null"], "items": {"type": "object", "properties": {"quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}, "faceAnalytics": {"type": "object", "properties": {"age": {"type": ["string", "null"]}, "gender": {"type": ["string", "null"]}, "emotion": {"type": ["string", "null"]}}, "additionalProperties": false}}, "additionalProperties": false}}}, "additionalProperties": false} |
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9b9106be-ecf1-491c-a21b-1fc72657a3ef/91a19dbc-c297-45b5-bc6b-cb8cf52bdebd/0/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | landmark | 200 | null | {"errorCode": 0, "errorMessage": "", "faces": [{"quality": 0, "faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}, "faceLandmark": {"mouthLeft": {"x": 0, "y": 0}, "mouthRight": {"x": 0, "y": 0}, "nose": {"x": 0, "y": 0}, "eye_left": {"x": 0, "y": 0}, "eye_right": {"x": 0, "y": 0}}}]} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "faces": {"type": ["array", "null"], "items": {"type": "object", "properties": {"quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}, "faceLandmark": {"type": "object", "properties": {"mouthLeft": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}, "mouthRight": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}, "nose": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}, "eye_left": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}, "eye_right": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}}, "additionalProperties": false}}, "additionalProperties": false}}}, "additionalProperties": false} |
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9b9106be-ecf1-491c-a21b-1fc72657a3ef/91a19dbc-c297-45b5-bc6b-cb8cf52bdebd/1/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | landmark | 200 | null | {"errorCode": 0, "errorMessage": "", "faces": [{"quality": 0, "faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}, "faceLandmark": {"mouthLeft": {"x": 0, "y": 0}, "mouthRight": {"x": 0, "y": 0}, "nose": {"x": 0, "y": 0}, "eye_left": {"x": 0, "y": 0}, "eye_right": {"x": 0, "y": 0}}}]} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "faces": {"type": ["array", "null"], "items": {"type": "object", "properties": {"quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}, "faceLandmark": {"type": "object", "properties": {"mouthLeft": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}, "mouthRight": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}, "nose": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}, "eye_left": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}, "eye_right": {"type": "object", "properties": {"x": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}, "y": {"type": "number", "format": "double", "minimum": -1.7976931348623157e+308, "maximum": 1.7976931348623157e+308}}, "additionalProperties": false}}, "additionalProperties": false}}, "additionalProperties": false}}}, "additionalProperties": false} |
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9b9106be-ecf1-491c-a21b-1fc72657a3ef/a43d9add-14d6-430e-bda0-fcde95df4fae/0/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | CheckLiveness | 200 | null | {"errorCode": 0, "errorMessage": "", "quality": 0, "probability": 0} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "probability": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}}, "additionalProperties": false} |
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9b9106be-ecf1-491c-a21b-1fc72657a3ef/a43d9add-14d6-430e-bda0-fcde95df4fae/1/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | CheckLiveness | 200 | null | {"errorCode": 0, "errorMessage": "", "quality": 0, "probability": 0} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "probability": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}}, "additionalProperties": false} |
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9b9106be-ecf1-491c-a21b-1fc72657a3ef/95bfe5f8-eabb-46cf-a042-10c7466fcb45/0/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | verify | 200 | null | {"errorCode": 0, "errorMessage": "", "matchedFaces": [{"confidence": 0, "image1_face": {"faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}, "quality": 0}, "image2_face": {"faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}, "quality": 0}}]} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "matchedFaces": {"type": ["array", "null"], "items": {"type": "object", "properties": {"confidence": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "image1_face": {"type": "object", "properties": {"faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}, "quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}}, "additionalProperties": false}, "image2_face": {"type": "object", "properties": {"faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}, "quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}}, "additionalProperties": false}}, "additionalProperties": false}}}, "additionalProperties": false} |
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9b9106be-ecf1-491c-a21b-1fc72657a3ef/95bfe5f8-eabb-46cf-a042-10c7466fcb45/1/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | verify | 200 | null | {"errorCode": 0, "errorMessage": "", "matchedFaces": [{"confidence": 0, "image1_face": {"faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}, "quality": 0}, "image2_face": {"faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}, "quality": 0}}]} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "matchedFaces": {"type": ["array", "null"], "items": {"type": "object", "properties": {"confidence": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "image1_face": {"type": "object", "properties": {"faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}, "quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}}, "additionalProperties": false}, "image2_face": {"type": "object", "properties": {"faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}, "quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}}, "additionalProperties": false}}, "additionalProperties": false}}}, "additionalProperties": false} |
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9b9106be-ecf1-491c-a21b-1fc72657a3ef/a40598ec-d9b1-4210-8920-cfb8e8d759b4/0/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | detect | 200 | null | {"errorCode": 0, "errorMessage": "", "faces": [{"quality": 0, "faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}}]} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "faces": {"type": ["array", "null"], "items": {"type": "object", "properties": {"quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}}, "additionalProperties": false}}}, "additionalProperties": false} |
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9b9106be-ecf1-491c-a21b-1fc72657a3ef/a40598ec-d9b1-4210-8920-cfb8e8d759b4/1/0 | Face Detection | Our Face Detection API detects and finds human faces within an image, and returns with high accuracy face bordering boxes. The Face Detect API accepts only images as input and each Image can have multiple faces and the API will return results for each face. | null | detect | 200 | null | {"errorCode": 0, "errorMessage": "", "faces": [{"quality": 0, "faceRectangle": {"x": 0, "y": 0, "height": 0, "width": 0}}]} | {"type": "object", "properties": {"errorCode": {"type": ["integer", "null"], "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "errorMessage": {"type": ["string", "null"]}, "faces": {"type": ["array", "null"], "items": {"type": "object", "properties": {"quality": {"type": "number", "format": "float", "minimum": -3.402823669209385e+38, "maximum": 3.402823669209385e+38}, "faceRectangle": {"type": "object", "properties": {"x": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "y": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "height": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}, "width": {"type": "integer", "format": "int32", "minimum": -2147483648, "maximum": 2147483647}}, "additionalProperties": false}}, "additionalProperties": false}}}, "additionalProperties": false} |
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b7cb203a-b8f6-4cfe-a671-cdf4dd3542f2/5ec0bfd8-80a0-45c1-b262-3eb3d19c884b/0/0 | Auther Check | Plug and play the facial authentication into: point of sale, mobile app, self-checkouts, kiosk, ATM. | 0.2 | Compare person | Compares the face on the sourceImage with the largest face detected on the targetImage.
By default, the submitted sourceImage will be compared the targetImage with the 80% of similarity threshold. If you want to compare images with a custom similarity threshold (for example, 98%), specify this number in the request body [option]. In response, you get the similarity value of the facesMatched images. | 200 | Example_1 | {"similarity": 97.84321} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"similarity": {"type": "number"}}, "required": ["similarity"]} |
b7cb203a-b8f6-4cfe-a671-cdf4dd3542f2/9553ecd1-3268-4aa5-a45a-bc45363d4db5/0/0 | Auther Check | Plug and play the facial authentication into: point of sale, mobile app, self-checkouts, kiosk, ATM. | 0.2 | Verify person | Comparison of the face of a person who declares that his face belongs to the known person_id. With this request, we start 1:1 matching for the enrolled person in our system. If the submitted person's face matches to 80% with the person's image that belongs to the declared person_id, then the verification result is successful. | 200 | Example_1 | {"personId": "string", "created": "2020-09-03T16:05:08.938Z", "updated": "2020-09-04T16:05:08.938Z"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"personId": {"type": "string"}, "created": {"type": "string"}, "updated": {"type": "string"}}, "required": ["created", "personId", "updated"]} |
b7cb203a-b8f6-4cfe-a671-cdf4dd3542f2/4dd8f2f1-88c4-4b20-816a-48183cb0974f/0/0 | Auther Check | Plug and play the facial authentication into: point of sale, mobile app, self-checkouts, kiosk, ATM. | 0.2 | Identify person | Submit the Base64-encoded image. With this request, we start 1:N searching for the most similar enrolled person in our system. The search result will be person_id, which matches the searched one by 98%.
To improve the quality and speed of recognition, follow the image requirements for the submitted images. | 200 | Example_1 | {"personId": "string", "created": "2020-09-03T16:05:08.938Z", "updated": "2020-09-04T16:05:08.938Z"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"personId": {"type": "string"}, "created": {"type": "string"}, "updated": {"type": "string"}}, "required": ["created", "personId", "updated"]} |
b7cb203a-b8f6-4cfe-a671-cdf4dd3542f2/9626d201-352f-4225-895f-9f50562b7246/0/0 | Auther Check | Plug and play the facial authentication into: point of sale, mobile app, self-checkouts, kiosk, ATM. | 0.2 | Get person by id | To check if the person_id already exists in the system, just specify the path with person_id. If the person_id exists in response you will get the same person_id and information when a person was created and updated. | 200 | Example_1 | {"personId": "string", "created": "2020-09-03T16:05:08.938Z", "updated": "2020-09-04T16:05:08.938Z"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"personId": {"type": "string"}, "created": {"type": "string"}, "updated": {"type": "string"}}, "required": ["created", "personId", "updated"]} |
36cb67a9-7970-487e-a19f-0ada32216639/16931bd6-ae6b-42eb-b782-ad2e48cd2de5/0/0 | Facial Landmark Detection | Supports 72 key points, 150 key points, and 201 key points of face detection. Key points include face, eyes, eyebrows, lips and nose contour, etc. This service has the following three business functions: | null | Facial Landmark Detection | Facial Landmark Detection | 200 | Success | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 0, "result": {"face_num": 1, "face_list": [{"face_token": "d80fc864a9f11ca97f753b7fd6ef3092", "location": {"left": 148.2, "top": 207.76, "width": 293, "height": 265, "rotation": 0}, "face_probability": 1, "angle": {"yaw": 19.13, "pitch": 17.13, "roll": -3.5}, "landmark201": [{"cheek_right_1": {"x": 152.91139221191, "y": 234.10575866699}, "cheek_right_3": {"x": 153.21405029297, "y": 275.29922485352}, "cheek_right_5": {"x": 159.1178894043, "y": 317.43710327148}, "cheek_right_7": {"x": 171.67828369141, "y": 359.82891845703}, "cheek_right_9": {"x": 187.34191894531, "y": 402.29333496094}, "cheek_right_11": {"x": 209.47039794922, "y": 448.70611572266}, "chin_2": {"x": 244.76583862305, "y": 480.13912963867}, "cheek_left_11": {"x": 300.36502075195, "y": 472.90335083008}, "cheek_left_9": {"x": 355.99075317383, "y": 439.84826660156}, "cheek_left_7": {"x": 402.11898803711, "y": 393.20904541016}, "cheek_left_5": {"x": 427.60656738281, "y": 340.88400268555}, "cheek_left_3": {"x": 442.78765869141, "y": 287.72296142578}, "cheek_left_1": {"x": 453.259765625, "y": 234.46209716797}, "eye_right_corner_right": {"x": 166.43855285645, "y": 245.62696838379}, "eye_right_eyelid_upper_2": {"x": 178.73571777344, "y": 233.48094177246}, "eye_right_eyelid_upper_4": {"x": 194.54188537598, "y": 231.23136901855}, "eye_right_eyelid_upper_6": {"x": 209.59561157227, "y": 238.01022338867}, "eye_right_corner_left": {"x": 219.60101318359, "y": 252.86766052246}, "eye_right_eyelid_lower_6": {"x": 206.45573425293, "y": 256.78121948242}, "eye_right_eyelid_lower_4": {"x": 191.26301574707, "y": 257.60192871094}, "eye_right_eyelid_lower_2": {"x": 177.1402130127, "y": 253.22375488281}, "eye_right_eyeball_center": {"x": 197.69207763672, "y": 242.78115844727}, "eyebrow_right_corner_right": {"x": 152.5193939209, "y": 218.0311126709}, "eyebrow_right_upper_2": {"x": 166.62945556641, "y": 206.35087585449}, "eyebrow_right_upper_3": {"x": 183.5559387207, "y": 209.04162597656}, "eyebrow_right_upper_4": {"x": 200.37629699707, "y": 216.20118713379}, "eyebrow_right_corner_left": {"x": 215.19021606445, "y": 231.66654968262}, "eyebrow_right_lower_3": {"x": 197.2017364502, "y": 226.71070861816}, "eyebrow_right_lower_2": {"x": 180.5466003418, "y": 221.2080078125}, "eyebrow_right_lower_1": {"x": 165.50422668457, "y": 217.85374450684}, "eye_left_corner_right": {"x": 284.4423828125, "y": 253.46418762207}, "eye_left_eyelid_upper_2": {"x": 299.30715942383, "y": 238.99905395508}, "eye_left_eyelid_upper_4": {"x": 316.24237060547, "y": 233.8639831543}, "eye_left_eyelid_upper_6": {"x": 333.67279052734, "y": 238.54011535645}, "eye_left_corner_left": {"x": 347.63455200195, "y": 252.36630249023}, "eye_left_eyelid_lower_6": {"x": 333.91830444336, "y": 257.90979003906}, "eye_left_eyelid_lower_4": {"x": 316.63473510742, "y": 260.21624755859}, "eye_left_eyelid_lower_2": {"x": 299.55313110352, "y": 257.49395751953}, "eye_left_eyeball_center": {"x": 320.76895141602, "y": 244.34625244141}, "eyebrow_left_corner_right": {"x": 275.39828491211, "y": 230.90559387207}, "eyebrow_left_upper_2": {"x": 296.08618164062, "y": 216.02331542969}, "eyebrow_left_upper_3": {"x": 319.22418212891, "y": 210.38291931152}, "eyebrow_left_upper_4": {"x": 345.15350341797, "y": 209.21328735352}, "eyebrow_left_corner_left": {"x": 372.05294799805, "y": 222.89102172852}, "eyebrow_left_lower_3": {"x": 345.80990600586, "y": 220.7686920166}, "eyebrow_left_lower_2": {"x": 321.57382202148, "y": 223.06295776367}, "eyebrow_left_lower_1": {"x": 298.73480224609, "y": 227.94213867188}, "nose_right_contour_1": {"x": 229.40553283691, "y": 257.50231933594}, "nose_right_contour_2": {"x": 221.8087310791, "y": 283.46823120117}, "nose_right_contour_3": {"x": 214.45086669922, "y": 309.3616027832}, "nose_right_contour_4": {"x": 207.43621826172, "y": 334.99829101562}, "nose_right_contour_6": {"x": 216.9593963623, "y": 342.42492675781}, "nose_left_contour_6": {"x": 253.02030944824, "y": 342.05941772461}, "nose_left_contour_4": {"x": 276.26602172852, "y": 338.05661010742}, "nose_left_contour_3": {"x": 267.28646850586, "y": 311.75662231445}, "nose_left_contour_2": {"x": 265.51040649414, "y": 285.46475219727}, "nose_left_contour_1": {"x": 264.02905273438, "y": 258.85943603516}, "nose_tip": {"x": 225.04518127441, "y": 328.64370727539}, "mouth_corner_right_outer": {"x": 206.5617980957, "y": 385.76031494141}, "mouth_lip_upper_outer_3": {"x": 219.67320251465, "y": 375.18218994141}, "mouth_lip_upper_outer_6": {"x": 239.92309570312, "y": 374.76977539062}, "mouth_lip_upper_outer_9": {"x": 270.28350830078, "y": 376.16665649414}, "mouth_corner_left_outer": {"x": 303.98645019531, "y": 385.67404174805}, "mouth_lip_lower_outer_9": {"x": 273.26431274414, "y": 404.86437988281}, "mouth_lip_lower_outer_6": {"x": 240.91514587402, "y": 410.22521972656}, "mouth_lip_lower_outer_3": {"x": 219.5506439209, "y": 403.01010131836}, "mouth_lip_upper_inner_3": {"x": 221.61395263672, "y": 384.23931884766}, "mouth_lip_upper_inner_6": {"x": 240.56512451172, "y": 385.11706542969}, "mouth_lip_upper_inner_9": {"x": 269.63024902344, "y": 384.37921142578}, "mouth_lip_lower_inner_9": {"x": 269.86450195312, "y": 391.81661987305}, "mouth_lip_lower_inner_6": {"x": 241.16767883301, "y": 392.5026550293}, "mouth_lip_lower_inner_3": {"x": 223.11337280273, "y": 390.59606933594}}]}]}} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "result": {"type": "object", "required": false, "properties": {"face_num": {"type": "integer", "required": true, "example": 1, "description": "The number of faces in the picture."}, "face_list": {"type": "array", "required": true, "description": "Face information."}}}} |
36cb67a9-7970-487e-a19f-0ada32216639/16931bd6-ae6b-42eb-b782-ad2e48cd2de5/0/1 | Facial Landmark Detection | Supports 72 key points, 150 key points, and 201 key points of face detection. Key points include face, eyes, eyebrows, lips and nose contour, etc. This service has the following three business functions: | null | Facial Landmark Detection | Facial Landmark Detection | 200 | Error | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 400, "error_code_str": "ERROR_PARAMETERS", "error_msg": "image cannot be empty"} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "result": {"type": "object", "required": false, "properties": {"face_num": {"type": "integer", "required": true, "example": 1, "description": "The number of faces in the picture."}, "face_list": {"type": "array", "required": true, "description": "Face information."}}}} |
36cb67a9-7970-487e-a19f-0ada32216639/16931bd6-ae6b-42eb-b782-ad2e48cd2de5/1/0 | Facial Landmark Detection | Supports 72 key points, 150 key points, and 201 key points of face detection. Key points include face, eyes, eyebrows, lips and nose contour, etc. This service has the following three business functions: | null | Facial Landmark Detection | Facial Landmark Detection | 401 | Example | {"message": "Invalid API key in request"} | {"type": "object", "properties": {"message": {"type": "string", "required": true, "example": "Invalid API key in request", "description": "Error Message."}}} |
cf6973e3-cd94-42b0-be89-6dd1c1333983/e409f0a7-152a-4880-99bf-c17dde4861a9/0/0 | The form recognition | Form recognition and extrac key-value | null | get key value | get key value | 200 | New Example | {"data": "value"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"data": {"type": "string"}}, "required": ["data"]} |
cf6973e3-cd94-42b0-be89-6dd1c1333983/e409f0a7-152a-4880-99bf-c17dde4861a9/1/0 | The form recognition | Form recognition and extrac key-value | null | get key value | get key value | 200 | Response | {"erroNo": 0, "errMsg": "", "data": {"textLines": [{"x0": 53, "x1": 108, "top": 42, "bottom": 72, "text": "TO\uff1a", "label": "KEY"}, {"x0": 108, "x1": 345, "top": 42, "bottom": 72, "text": "\u5929\u6d25\u5916\u4ee3\u8d27\u8fd0\u6709\u9650\u516c\u53f8", "label": "MARKER"}, {"x0": 640, "x1": 803, "top": 44, "bottom": 68, "text": "HZHSE21114259", "label": "VALUE"}, {"x0": 840, "x1": 961, "top": 48, "bottom": 67, "text": "2021/11/30", "label": "VALUE"}, {"x0": 53, "x1": 423, "top": 88, "bottom": 116, "text": "Shipper\uff08Full Name \uff06Address\uff09\uff08\u6258\u8fd0\u4eba\uff09\uff1a", "label": "KEY"}, {"x0": 696, "x1": 1061, "top": 115, "bottom": 146, "text": "\u5929\u6d25\u6d69\u4e4b\u822a\u56fd\u9645\u8d27\u8fd0\u4ee3\u7406\u6709\u9650\u516c\u53f8", "label": "MARKER"}, {"x0": 52, "x1": 488, "top": 126, "bottom": 141, "text": "RUNTON INTERNATIONAL TRADING CO.,LIMITED.", "label": "VALUE"}, {"x0": 52, "x1": 334, "top": 155, "bottom": 171, "text": "NO.25,BAODING ROAD,HEPING", "label": "VALUE"}, {"x0": 661, "x1": 752, "top": 158, "bottom": 208, "text": "HH", "label": "MARKER"}, {"x0": 784, "x1": 988, "top": 171, "bottom": 205, "text": "\u51fa\u53e3\u8d27\u7269\u6258\u8fd0\u5355", "label": "MARKER"}, {"x0": 52, "x1": 274, "top": 185, "bottom": 201, "text": "DISTRICT,TIANJIN,CHINA", "label": "VALUE"}, {"x0": 663, "x1": 749, "top": 203, "bottom": 214, "text": "S4E01L000748", "label": "VALUE"}, {"x0": 734, "x1": 1006, "top": 224, "bottom": 243, "text": "Sea Freight Shipping Instructions", "label": "MARKER"}, {"x0": 53, "x1": 237, "top": 292, "bottom": 320, "text": "Consignee\uff08\u6536\u8d27\u4eba\uff09\uff1a", "label": "KEY"}, {"x0": 640, "x1": 741, "top": 302, "bottom": 330, "text": "OP\uff08\u64cd\u4f5c\uff09\uff1a", "label": "KEY"}, {"x0": 741, "x1": 804, "top": 302, "bottom": 330, "text": "\u51af\u5176\u4f73", "label": "VALUE"}, {"x0": 54, "x1": 287, "top": 325, "bottom": 350, "text": "STL MARKETING SDN BHD", "label": "VALUE"}, {"x0": 54, "x1": 303, "top": 355, "bottom": 379, "text": "NO.93,JALAN KERISI,SUNGAI", "label": "VALUE"}, {"x0": 640, "x1": 798, "top": 365, "bottom": 392, "text": "SEALES\uff08\u4e1a\u52a1\u5458\uff09\uff1a", "label": "KEY"}, {"x0": 798, "x1": 858, "top": 365, "bottom": 392, "text": "\u5218\u632f\u5b87", "label": "VALUE"}, {"x0": 54, "x1": 369, "top": 384, "bottom": 409, "text": "RENGIT,81620 PENGERANG, JOHOR.", "label": "VALUE"}, {"x0": 639, "x1": 732, "top": 438, "bottom": 457, "text": "TEL\uff08\u7535\u8bdd\uff09\uff1a", "label": "KEY"}, {"x0": 732, "x1": 969, "top": 438, "bottom": 457, "text": "24385813,13821677174", "label": "VALUE"}, {"x0": 52, "x1": 252, "top": 489, "bottom": 508, "text": "Notify Party\uff08\u901a\u77e5\u4eba\uff09\uff1a", "label": "KEY"}, {"x0": 640, "x1": 864, "top": 500, "bottom": 527, "text": "Service Term\uff08\u8fd0\u8f93\u6761\u6b3e\uff09\uff1a", "label": "KEY"}, {"x0": 864, "x1": 922, "top": 500, "bottom": 527, "text": "CY-CY", "label": "VALUE"}, {"x0": 52, "x1": 289, "top": 522, "bottom": 538, "text": "STL MARKETING SDN BHD", "label": "VALUE"}, {"x0": 54, "x1": 303, "top": 547, "bottom": 572, "text": "NO.93,JALAN KERISI,SUNGAI", "label": "VALUE"}, {"x0": 639, "x1": 862, "top": 567, "bottom": 595, "text": "Freight Term\uff08\u8fd0\u8d39\u6761\u6b3e\uff09\uff1a", "label": "KEY"}, {"x0": 862, "x1": 1033, "top": 567, "bottom": 595, "text": "FREIGHT PREPAID", "label": "VALUE"}, {"x0": 54, "x1": 369, "top": 577, "bottom": 601, "text": "RENGIT,81620 PENGERANG, JOHOR.", "label": "VALUE"}, {"x0": 640, "x1": 789, "top": 636, "bottom": 662, "text": "ETD\uff08\u9884\u5b9a\u8239\u671f\uff09\uff1a", "label": "KEY"}, {"x0": 789, "x1": 905, "top": 636, "bottom": 662, "text": "2021\uff0f12\uff0f24", "label": "VALUE"}, {"x0": 52, "x1": 301, "top": 691, "bottom": 707, "text": "Ocean Vessel\uff0fVoy\uff08\u8239\u540d\u822a\u6b21\uff09\uff1a", "label": "KEY"}, {"x0": 346, "x1": 556, "top": 691, "bottom": 707, "text": "Port of Loading\uff08\u8d77\u8fd0\u6e2f\uff09\uff1a", "label": "KEY"}, {"x0": 640, "x1": 812, "top": 699, "bottom": 725, "text": "CARRIER\uff08\u8239\u516c\u53f8\uff09\uff1a", "label": "KEY"}, {"x0": 812, "x1": 861, "top": 699, "bottom": 725, "text": "EMC", "label": "VALUE"}, {"x0": 345, "x1": 503, "top": 724, "bottom": 738, "text": "XINGANG,CHINA", "label": "VALUE"}, {"x0": 639, "x1": 886, "top": 759, "bottom": 779, "text": "Cargo Quantity\uff08\u8d27\u91cf\u63cf\u8ff0\uff09\uff1a", "label": "KEY"}, {"x0": 349, "x1": 563, "top": 766, "bottom": 790, "text": "Place of Delivery\uff08\u4ea4\u8d27\u5730\uff09\uff1a", "label": "KEY"}, {"x0": 886, "x1": 959, "top": 759, "bottom": 779, "text": "1\uff0a20GP", "label": "VALUE"}, {"x0": 52, "x1": 277, "top": 770, "bottom": 789, "text": "Part of Discharge\uff08\u5378\u8d27\u6e2f\uff09\uff1a", "label": "KEY"}, {"x0": 52, "x1": 199, "top": 803, "bottom": 817, "text": "PASIR GUDANG", "label": "VALUE"}, {"x0": 346, "x1": 491, "top": 803, "bottom": 817, "text": "PASIR GUDANG", "label": "VALUE"}, {"x0": 804, "x1": 826, "top": 805, "bottom": 832, "text": "\u5426", "label": "O"}, {"x0": 878, "x1": 1035, "top": 805, "bottom": 831, "text": "Batch\uff08\u53ef\u5426\u5206\u6279\uff09\uff1a", "label": "KEY"}, {"x0": 639, "x1": 776, "top": 810, "bottom": 827, "text": "T\uff0fS\uff08\u53ef\u5426\u8f6c\u8239\uff09\uff1a", "label": "KEY"}, {"x0": 1055, "x1": 1083, "top": 809, "bottom": 828, "text": "\u5426", "label": "O"}, {"x0": 98, "x1": 220, "top": 849, "bottom": 863, "text": "Marks & Nos", "label": "KEY"}, {"x0": 269, "x1": 466, "top": 849, "bottom": 868, "text": "Quantity&Packaging", "label": "KEY"}, {"x0": 533, "x1": 719, "top": 845, "bottom": 869, "text": "Description of Goods", "label": "KEY"}, {"x0": 777, "x1": 1128, "top": 849, "bottom": 865, "text": "Gross Weight(KGS) Measurement(CBM)", "label": "KEY"}, {"x0": 312, "x1": 420, "top": 875, "bottom": 899, "text": "\uff08\u4ef6\u6570\u53ca\u5305\u88c5\uff09", "label": "KEY"}, {"x0": 103, "x1": 213, "top": 879, "bottom": 895, "text": "\uff08\u6807\u5fd7\u548c\u53f7\u7801\uff09", "label": "KEY"}, {"x0": 598, "x1": 654, "top": 879, "bottom": 895, "text": "\uff08\u54c1\u540d\uff09", "label": "KEY"}, {"x0": 819, "x1": 907, "top": 875, "bottom": 899, "text": "\u6bdb\u91cd\uff08\u516c\u65a4\uff09", "label": "KEY"}, {"x0": 981, "x1": 1093, "top": 879, "bottom": 895, "text": "\u4f53\u79ef\uff08\u7acb\u65b9\u7c73\uff09", "label": "KEY"}, {"x0": 346, "x1": 390, "top": 900, "bottom": 913, "text": "1300", "label": "VALUE"}, {"x0": 817, "x1": 935, "top": 900, "bottom": 922, "text": "20000.00KGS", "label": "VALUE"}, {"x0": 992, "x1": 1094, "top": 899, "bottom": 924, "text": "25.000CBM", "label": "VALUE"}, {"x0": 468, "x1": 725, "top": 927, "bottom": 942, "text": "FIBER GLASS YARN C-GRADE", "label": "VALUE"}, {"x0": 470, "x1": 548, "top": 952, "bottom": 976, "text": "\u73bb\u7483\u7ea4\u7ef4", "label": "VALUE"}, {"x0": 470, "x1": 559, "top": 981, "bottom": 1006, "text": "HS CODE:", "label": "KEY"}, {"x0": 559, "x1": 642, "top": 981, "bottom": 1006, "text": "70191200", "label": "VALUE"}, {"x0": 53, "x1": 337, "top": 1228, "bottom": 1256, "text": "On Board Date\uff08\u5b9e\u9645\u88c5\u8239\u65e5\u671f\uff09\uff1a", "label": "KEY"}, {"x0": 483, "x1": 542, "top": 1241, "bottom": 1262, "text": "CY-CY", "label": "VALUE"}, {"x0": 479, "x1": 641, "top": 1277, "bottom": 1293, "text": "FREIGHT PREPAID", "label": "VALUE"}, {"x0": 842, "x1": 1126, "top": 1273, "bottom": 1297, "text": "SHIPPER'S LOAD,COUNT & SEAL", "label": "VALUE"}, {"x0": 52, "x1": 356, "top": 1318, "bottom": 1335, "text": "Total Packages\uff08in words\uff09\uff08\u4ef6\u6570\u5927\u5199\uff09\uff1a", "label": "KEY"}, {"x0": 356, "x1": 771, "top": 1318, "bottom": 1335, "text": "SAY ONE THOUSAND THREE HUNDRED ONLY.", "label": "VALUE"}, {"x0": 54, "x1": 188, "top": 1353, "bottom": 1379, "text": "Ramark\uff08\u5907\u6ce8\uff09\uff1a", "label": "KEY"}, {"x0": 54, "x1": 270, "top": 1386, "bottom": 1412, "text": "\u7533\u8bf7\u76ee\u7684\u6e2f\u514d\u7528\u7bb114\u5929", "label": "VALUE"}, {"x0": 53, "x1": 131, "top": 1419, "bottom": 1445, "text": "\u5b9a0619", "label": "VALUE"}, {"x0": 54, "x1": 363, "top": 1452, "bottom": 1478, "text": "F321646\uff0fCNT008439 \u5b59\u5bb6\u7426\u786e\u8ba4", "label": null}], "keyValuePair": [{"key": {"text": "SEALES\uff08\u4e1a\u52a1\u5458\uff09\uff1a", "textLines": [{"text": "SEALES\uff08\u4e1a\u52a1\u5458\uff09\uff1a", "bbox": [640, 365, 798, 392]}]}, "value": {"text": "\u51af\u5176\u4f73*****\u5218\u632f\u5b87", "textLines": [{"text": "\u51af\u5176\u4f73", "bbox": [741, 302, 804, 330]}, {"text": "\u5218\u632f\u5b87", "bbox": [798, 365, 858, 392]}]}}, {"key": {"text": "Total Packages\uff08in words\uff09\uff08\u4ef6\u6570\u5927\u5199\uff09\uff1a", "textLines": [{"text": "Total Packages\uff08in words\uff09\uff08\u4ef6\u6570\u5927\u5199\uff09\uff1a", "bbox": [52, 1318, 356, 1335]}]}, "value": {"text": "SAY ONE THOUSAND THREE HUNDRED ONLY.", "textLines": [{"text": "SAY ONE THOUSAND THREE HUNDRED ONLY.", "bbox": [356, 1318, 771, 1335]}]}}, {"key": {"text": "Notify Party\uff08\u901a\u77e5\u4eba\uff09\uff1a", "textLines": [{"text": "Notify Party\uff08\u901a\u77e5\u4eba\uff09\uff1a", "bbox": [52, 489, 252, 508]}]}, "value": {"text": "STL MARKETING SDN BHD\nNO.93,JALAN KERISI,SUNGAI\nRENGIT,81620 PENGERANG, JOHOR.", "textLines": [{"text": "STL MARKETING SDN BHD\nNO.93,JALAN KERISI,SUNGAI\nRENGIT,81620 PENGERANG, JOHOR.", "bbox": [52, 522, 369, 601]}]}}, {"key": {"text": "Consignee\uff08\u6536\u8d27\u4eba\uff09\uff1a", "textLines": [{"text": "Consignee\uff08\u6536\u8d27\u4eba\uff09\uff1a", "bbox": [53, 292, 237, 320]}]}, "value": {"text": "STL MARKETING SDN BHD\nNO.93,JALAN KERISI,SUNGAI\nRENGIT,81620 PENGERANG, JOHOR.", "textLines": [{"text": "STL MARKETING SDN BHD\nNO.93,JALAN KERISI,SUNGAI\nRENGIT,81620 PENGERANG, JOHOR.", "bbox": [54, 325, 369, 409]}]}}, {"key": {"text": "Gross Weight(KGS) Measurement(CBM)\n\u6bdb\u91cd\uff08\u516c\u65a4\uff09", "textLines": [{"text": "Gross Weight(KGS) Measurement(CBM)\n\u6bdb\u91cd\uff08\u516c\u65a4\uff09", "bbox": [777, 849, 1128, 899]}]}, "value": {"text": "20000.00KGS", "textLines": [{"text": "20000.00KGS", "bbox": [817, 900, 935, 922]}]}}, {"key": {"text": "HS CODE:", "textLines": [{"text": "HS CODE:", "bbox": [470, 981, 559, 1006]}]}, "value": {"text": "70191200", "textLines": [{"text": "70191200", "bbox": [559, 981, 642, 1006]}]}}, {"key": {"text": "Freight Term\uff08\u8fd0\u8d39\u6761\u6b3e\uff09\uff1a", "textLines": [{"text": "Freight Term\uff08\u8fd0\u8d39\u6761\u6b3e\uff09\uff1a", "bbox": [639, 567, 862, 595]}]}, "value": {"text": "CY-CY*****FREIGHT PREPAID*****EMC", "textLines": [{"text": "CY-CY", "bbox": [864, 500, 922, 527]}, {"text": "FREIGHT PREPAID", "bbox": [862, 567, 1033, 595]}, {"text": "EMC", "bbox": [812, 699, 861, 725]}]}}, {"key": {"text": "Service Term\uff08\u8fd0\u8f93\u6761\u6b3e\uff09\uff1a", "textLines": [{"text": "Service Term\uff08\u8fd0\u8f93\u6761\u6b3e\uff09\uff1a", "bbox": [640, 500, 864, 527]}]}, "value": {"text": "CY-CY*****FREIGHT PREPAID*****EMC", "textLines": [{"text": "CY-CY", "bbox": [864, 500, 922, 527]}, {"text": "FREIGHT PREPAID", "bbox": [862, 567, 1033, 595]}, {"text": "EMC", "bbox": [812, 699, 861, 725]}]}}, {"key": {"text": "OP\uff08\u64cd\u4f5c\uff09\uff1a", "textLines": [{"text": "OP\uff08\u64cd\u4f5c\uff09\uff1a", "bbox": [640, 302, 741, 330]}]}, "value": {"text": "\u51af\u5176\u4f73", "textLines": [{"text": "\u51af\u5176\u4f73", "bbox": [741, 302, 804, 330]}]}}, {"key": {"text": "Ramark\uff08\u5907\u6ce8\uff09\uff1a", "textLines": [{"text": "Ramark\uff08\u5907\u6ce8\uff09\uff1a", "bbox": [54, 1353, 188, 1379]}]}, "value": {"text": "\u7533\u8bf7\u76ee\u7684\u6e2f\u514d\u7528\u7bb114\u5929\n\u5b9a0619", "textLines": [{"text": "\u7533\u8bf7\u76ee\u7684\u6e2f\u514d\u7528\u7bb114\u5929\n\u5b9a0619", "bbox": [53, 1386, 270, 1445]}]}}, {"key": {"text": "ETD\uff08\u9884\u5b9a\u8239\u671f\uff09\uff1a", "textLines": [{"text": "ETD\uff08\u9884\u5b9a\u8239\u671f\uff09\uff1a", "bbox": [640, 636, 789, 662]}]}, "value": {"text": "2021\uff0f12\uff0f24", "textLines": [{"text": "2021\uff0f12\uff0f24", "bbox": [789, 636, 905, 662]}]}}, {"key": {"text": "Part of Discharge\uff08\u5378\u8d27\u6e2f\uff09\uff1a", "textLines": [{"text": "Part of Discharge\uff08\u5378\u8d27\u6e2f\uff09\uff1a", "bbox": [52, 770, 277, 789]}]}, "value": {"text": "PASIR GUDANG", "textLines": [{"text": "PASIR GUDANG", "bbox": [52, 803, 199, 817]}]}}, {"key": {"text": "Cargo Quantity\uff08\u8d27\u91cf\u63cf\u8ff0\uff09\uff1a", "textLines": [{"text": "Cargo Quantity\uff08\u8d27\u91cf\u63cf\u8ff0\uff09\uff1a", "bbox": [639, 759, 886, 779]}]}, "value": {"text": "1\uff0a20GP", "textLines": [{"text": "1\uff0a20GP", "bbox": [886, 759, 959, 779]}]}}, {"key": {"text": "Port of Loading\uff08\u8d77\u8fd0\u6e2f\uff09\uff1a", "textLines": [{"text": "Port of Loading\uff08\u8d77\u8fd0\u6e2f\uff09\uff1a", "bbox": [346, 691, 556, 707]}]}, "value": {"text": "XINGANG,CHINA", "textLines": [{"text": "XINGANG,CHINA", "bbox": [345, 724, 503, 738]}]}}, {"key": {"text": "CARRIER\uff08\u8239\u516c\u53f8\uff09\uff1a", "textLines": [{"text": "CARRIER\uff08\u8239\u516c\u53f8\uff09\uff1a", "bbox": [640, 699, 812, 725]}]}, "value": {"text": "FREIGHT PREPAID*****EMC", "textLines": [{"text": "FREIGHT PREPAID", "bbox": [862, 567, 1033, 595]}, {"text": "EMC", "bbox": [812, 699, 861, 725]}]}}, {"key": {"text": "TEL\uff08\u7535\u8bdd\uff09\uff1a", "textLines": [{"text": "TEL\uff08\u7535\u8bdd\uff09\uff1a", "bbox": [639, 438, 732, 457]}]}, "value": {"text": "24385813,13821677174", "textLines": [{"text": "24385813,13821677174", "bbox": [732, 438, 969, 457]}]}}, {"key": {"text": "Quantity&Packaging\n\uff08\u4ef6\u6570\u53ca\u5305\u88c5\uff09", "textLines": [{"text": "Quantity&Packaging\n\uff08\u4ef6\u6570\u53ca\u5305\u88c5\uff09", "bbox": [269, 849, 466, 899]}]}, "value": {"text": "1300", "textLines": [{"text": "1300", "bbox": [346, 900, 390, 913]}]}}, {"key": {"text": "\u4f53\u79ef\uff08\u7acb\u65b9\u7c73\uff09", "textLines": [{"text": "\u4f53\u79ef\uff08\u7acb\u65b9\u7c73\uff09", "bbox": [981, 879, 1093, 895]}]}, "value": {"text": "25.000CBM", "textLines": [{"text": "25.000CBM", "bbox": [992, 899, 1094, 924]}]}}, {"key": {"text": "Shipper\uff08Full Name \uff06Address\uff09\uff08\u6258\u8fd0\u4eba\uff09\uff1a", "textLines": [{"text": "Shipper\uff08Full Name \uff06Address\uff09\uff08\u6258\u8fd0\u4eba\uff09\uff1a", "bbox": [53, 88, 423, 116]}]}, "value": {"text": "RUNTON INTERNATIONAL TRADING CO.,LIMITED.\nNO.25,BAODING ROAD,HEPING\nDISTRICT,TIANJIN,CHINA", "textLines": [{"text": "RUNTON INTERNATIONAL TRADING CO.,LIMITED.\nNO.25,BAODING ROAD,HEPING\nDISTRICT,TIANJIN,CHINA", "bbox": [52, 126, 488, 201]}]}}, {"key": {"text": "Description of Goods\n\uff08\u54c1\u540d\uff09", "textLines": [{"text": "Description of Goods\n\uff08\u54c1\u540d\uff09", "bbox": [533, 845, 719, 895]}]}, "value": {"text": "FIBER GLASS YARN C-GRADE\n\u73bb\u7483\u7ea4\u7ef4", "textLines": [{"text": "FIBER GLASS YARN C-GRADE\n\u73bb\u7483\u7ea4\u7ef4", "bbox": [468, 927, 725, 976]}]}}, {"key": {"text": "Place of Delivery\uff08\u4ea4\u8d27\u5730\uff09\uff1a", "textLines": [{"text": "Place of Delivery\uff08\u4ea4\u8d27\u5730\uff09\uff1a", "bbox": [349, 766, 563, 790]}]}, "value": {"text": "XINGANG,CHINA*****PASIR GUDANG", "textLines": [{"text": "XINGANG,CHINA", "bbox": [345, 724, 503, 738]}, {"text": "PASIR GUDANG", "bbox": [346, 803, 491, 817]}]}}]}} | {"type": "object", "properties": {"data": {"type": "string"}}} |
922aa39e-d7c8-4ac2-96e6-298f4f0f6abd/9e2de926-d595-4c91-82f0-0d9be8ee0312/0/0 | AccuFace Detector | Precise and speedy face detection, as well as analysis of age and gender in images. | null | Face Detection | Detects faces in images and offers optional age and gender detection.
Request needs to have content-type "multipart/form-data".
Check out about tab to get started. | 200 | New Example | {"detected_faces": 1, "faces": [{"score": "1.00000", "bounding_box": {"x": 107, "y": 10, "width": 103, "height": 122}, "landmarks": {"x_right_eye": 139, "y_right_eye": 62, "x_left_eye": 174, "y_left_eye": 61, "x_nose_tip": 155, "y_nose_tip": 82, "x_right_corner_mouse": 142, "y_right_corner_mouse": 95, "x_left_corner_mouse": 173, "y_left_corner_mouse": 94}, "age": 37, "gender": "male", "gender_score": {"male": "0.99815", "female": "0.00185"}}]} | {"type": "object", "properties": {"detected_faces": {"type": "integer"}, "faces": {"type": "array", "items": {"type": "object", "properties": {"score": {"type": "string"}, "bounding_box": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}, "width": {"type": "integer"}, "height": {"type": "integer"}}}, "landmarks": {"type": "object", "properties": {"x_right_eye": {"type": "integer"}, "y_right_eye": {"type": "integer"}, "x_left_eye": {"type": "integer"}, "y_left_eye": {"type": "integer"}, "x_nose_tip": {"type": "integer"}, "y_nose_tip": {"type": "integer"}, "x_right_corner_mouse": {"type": "integer"}, "y_right_corner_mouse": {"type": "integer"}, "x_left_corner_mouse": {"type": "integer"}, "y_left_corner_mouse": {"type": "integer"}}}, "age": {"type": "integer"}, "gender": {"type": "string"}, "gender_score": {"type": "object", "properties": {"male": {"type": "string"}, "female": {"type": "string"}}}}}}}} |
922aa39e-d7c8-4ac2-96e6-298f4f0f6abd/9e2de926-d595-4c91-82f0-0d9be8ee0312/1/0 | AccuFace Detector | Precise and speedy face detection, as well as analysis of age and gender in images. | null | Face Detection | Detects faces in images and offers optional age and gender detection.
Request needs to have content-type "multipart/form-data".
Check out about tab to get started. | 400 | New Example | {"code": "400", "error": "One of image_file or image_base64 must be provided."} | {"type": "object", "properties": {"code": {"type": "string"}, "error": {"type": "string"}}} |
be12461e-9c05-4295-95b2-254395122179/d5f67dc5-602b-4eb0-bfdd-d1fa6b1671b9/0/0 | Japan My Number Card OCR | Extract name, date of birth, card number, status and other text from the front and back of my "My Number" card (Japan's social security and tax number system). | 6 | Japan My Number Card OCR | Support jpg, png, bmp, pdf, tiff, single-frame gif and other formats, the image size does not exceed 10M. | 200 | Response | {"code": "200", "status": "SUCCESS", "date": "11/22/2023 10:29:45 PM", "result": {"rotated_image_height": 384, "image_angle": 0, "rotated_image_width": 660, "item_list": [{"value": "123456789012", "position": {"bottom": 132, "left": 293, "right": 549, "top": 102}, "key": "subpage_number", "confidence": 0.983}, {"value": " \u756a\u53f7 \u82b1\u5b50", "position": {"bottom": 154, "left": 277, "right": 359, "top": 140}, "key": "subpage_name", "confidence": 0.983}, {"value": "\u5e73\u6210\u5143\u5e743\u670831\u65e5\u751f", "position": {"bottom": 201, "left": 411, "right": 541, "top": 183}, "key": "subpage_date_of_birth", "confidence": 0.999}, {"value": "", "key": "homepage_name", "confidence": 0.9}, {"value": "", "key": "homepage_address", "confidence": 0.9}, {"value": "", "key": "homepage_gender", "confidence": 0.9}, {"value": "", "key": "homepage_date_of_birth", "confidence": 0.9}, {"value": "", "key": "homepage_valid_term", "confidence": 0.9}, {"value": "", "key": "homepage_issued_by", "confidence": 0.9}, {"value": "", "key": "homepage_data_of_remark", "confidence": 0.9}], "type": "japan_mynumber_card"}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"code": {"type": "string"}, "status": {"type": "string"}, "date": {"type": "string"}, "result": {"type": "object", "properties": {"rotated_image_height": {"type": "integer"}, "image_angle": {"type": "integer"}, "rotated_image_width": {"type": "integer"}, "item_list": {"type": "array", "items": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}, "key": {"type": "string"}, "confidence": {"type": "number"}}, "required": ["confidence", "key", "value"]}}, "type": {"type": "string"}}, "required": ["image_angle", "item_list", "rotated_image_height", "rotated_image_width", "type"]}}, "required": ["code", "date", "result", "status"]} |
241bb4fd-e153-4725-aec5-3fae8ef79052/a0c248c4-e513-4044-ba7a-d0be62bcd6e3/0/0 | Age Detector | Age detection can be a challenging problem due to the variations in the aging of every individual depending on one’s health, lifestyle, etc. Analyzing the face of humans using computer vision can help estimate the age of humans as the face holds most of the important attributes showing the age of a person. The model estimates a person’s age from a picture. | 8.8 | Age detection from image |
For more details contact us | 200 | Response | [{"face_coordinate": [225, 28, 322, 157], "age": 55}] | {"$schema": "http://json-schema.org/schema#", "type": "array", "items": {"type": "object", "properties": {"face_coordinate": {"type": "array", "items": {"type": "integer"}}, "age": {"type": "integer"}}, "required": ["age", "face_coordinate"]}} |
61033125-6967-47d8-b2e8-80c800effc98/98f73d53-8f46-425c-802b-6c8951224463/1/0 | Fashion | This Fashion API offers an image class-prediction algorithm for clothes and accessories. [ or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 200 | Successful detection | {"results": [{"status": {"code": "ok", "message": "Success"}, "name": "image.jpg", "md5": "6ea449c4645b8811eef1342040725687", "width": 1024, "height": 768, "entities": [{"kind": "classes", "name": "fashion-classes", "classes": {"top, t-shirt, sweatshirt": 0.04409244656562805, "outwear": 0.008208364248275757, "vest": 0.3351793885231018, "shorts": 0.009493917226791382}}]}]} | {"type": "object", "properties": {"results": {"type": "array", "items": {"type": "object", "properties": {"status": {"type": "object", "properties": {"code": {"type": "string"}, "message": {"type": "string"}}}, "name": {"type": "string"}, "md5": {"type": "string"}, "entities": {"type": "array", "items": {"type": "object", "properties": {"kind": {"type": "string"}, "name": {"type": "string"}, "classes": {"type": "object"}}}}}}}}} |
61033125-6967-47d8-b2e8-80c800effc98/98f73d53-8f46-425c-802b-6c8951224463/1/1 | Fashion | This Fashion API offers an image class-prediction algorithm for clothes and accessories. [ or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 200 | Unsupported media type | {"results": [{"status": {"code": "failure", "message": "Unsupported media type. Expected one of ['image/jpeg', 'image/png']. Got 'text/plain'."}, "name": "file.txt", "md5": "d41d8cd98f00b204e9800998ecf8427e", "entities": []}]} | {"type": "object", "properties": {"results": {"type": "array", "items": {"type": "object", "properties": {"status": {"type": "object", "properties": {"code": {"type": "string"}, "message": {"type": "string"}}}, "name": {"type": "string"}, "md5": {"type": "string"}, "entities": {"type": "array", "items": {"type": "object", "properties": {"kind": {"type": "string"}, "name": {"type": "string"}, "classes": {"type": "object"}}}}}}}}} |
61033125-6967-47d8-b2e8-80c800effc98/98f73d53-8f46-425c-802b-6c8951224463/2/0 | Fashion | This Fashion API offers an image class-prediction algorithm for clothes and accessories. [ or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 422 | Missing image/url | {"detail": "Missing image or url field."} | {"type": "object", "properties": {"detail": {"type": "string"}}} |
071eb531-0b48-4a56-bf4b-126c54797635/b3fff70f-9eab-4723-899d-2d83c9e45a44/0/0 | Free AI OCR Optical Character Recognition | Free AI OCR Optical Character Recognition | 5 | /recognize-character | 200 | null | {"status": 1, "url": "http://vibktprfx-prod-prod-damo-eas-cn-shanghai.oss-cn-shanghai.aliyuncs.com/generative-cartoon/2023-09-09/1d73851a-7d53-416b-8606-01dc2f09db52/20230909_235408006889_dmbpxu56o3.jpg?Expires=1694276651&OSSAccessKeyId=LTAI4FoLmvQ9urWXgSRpDvh1&Signature=%2FcT4QU5F7%2FIR2J9Z9a3lvUnwdbI%3D"} | {"type": "object", "properties": {"status": {"type": "integer"}, "url": {"type": "string"}}, "required": ["status", "url"], "x-apifox-ignore-properties": [], "x-apifox-orders": ["status", "url"]} |
|
c6bc5191-1f8f-4511-8978-fcf186e40729/5777662b-8c5c-436a-ac56-71a6c2015df3/0/0 | U.S. Driver License OCR | Extract the 15 key forms on the front of your driver's license from 51 U.S. state driver's licenses, including DL class, date of birth, issued date, gender, height, expiry date, license number, restrictions, eys, END, DD, first name, last name, address, building. | 6 | U.S. Driver License OCR | Support jpg, png, bmp, pdf, tiff, single-frame gif and other formats, the image size does not exceed 10M. | 200 | Response | {"code": "200", "status": "SUCCESS", "date": "11/22/2023 11:25:52 PM", "result": {"rotated_image_height": 341, "image_angle": 0, "rotated_image_width": 533, "item_list": [{"value": "NONE", "position": {"bottom": 292, "left": 217, "right": 257, "top": 280}, "key": "endorsement"}, {"value": "06-09-85", "position": {"bottom": 260, "left": 246, "right": 317, "top": 244}, "key": "date_of_birth"}, {"value": "ANYTOWN", "position": {"bottom": 241, "left": 198, "right": 289, "top": 224}, "key": "city"}, {"value": "09-30-08", "position": {"bottom": 319, "left": 250, "right": 298, "top": 307}, "key": "issue_date"}, {"value": "SAMPLE,LICENSE", "position": {"bottom": 205, "left": 201, "right": 348, "top": 189}, "key": "given_name"}, {"value": "DOCUMENT", "position": {"bottom": 188, "left": 199, "right": 296, "top": 175}, "key": "family_name"}, {"value": "NY", "position": {"bottom": 239, "left": 282, "right": 311, "top": 223}, "key": "state"}, {"value": "", "key": "sex"}, {"value": "10-01-16", "position": {"bottom": 320, "left": 356, "right": 408, "top": 307}, "key": "date_of_expiry"}, {"value": "2345", "position": {"bottom": 224, "left": 198, "right": 245, "top": 208}, "key": "building_number"}, {"value": "", "key": "eyes"}, {"value": "ANYPLACE AVE", "position": {"bottom": 224, "left": 235, "right": 364, "top": 209}, "key": "street"}, {"value": "", "key": "identification_number"}, {"value": "5-09", "position": {"bottom": 281, "left": 288, "right": 354, "top": 264}, "key": "height"}, {"value": "12345", "position": {"bottom": 241, "left": 312, "right": 363, "top": 224}, "key": "post_code"}, {"value": "NONE", "position": {"bottom": 292, "left": 217, "right": 257, "top": 280}, "key": "restriction"}, {"value": "012 345 678", "position": {"bottom": 169, "left": 234, "right": 372, "top": 148}, "key": "driver_license_number"}, {"value": "D", "position": {"bottom": 172, "left": 489, "right": 516, "top": 146}, "key": "class"}], "type": ""}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"code": {"type": "string"}, "status": {"type": "string"}, "date": {"type": "string"}, "result": {"type": "object", "properties": {"rotated_image_height": {"type": "integer"}, "image_angle": {"type": "integer"}, "rotated_image_width": {"type": "integer"}, "item_list": {"type": "array", "items": {"type": "object", "properties": {"value": {"type": "string"}, "position": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}, "required": ["bottom", "left", "right", "top"]}, "key": {"type": "string"}}, "required": ["key", "value"]}}, "type": {"type": "string"}}, "required": ["image_angle", "item_list", "rotated_image_height", "rotated_image_width", "type"]}}, "required": ["code", "date", "result", "status"]} |
9a8129ba-2305-4acc-8036-73c2cc04be54/a9c0e56e-fe35-4d85-bf0a-fba415a18e27/0/0 | Regim | API for extracting data from image: colors, objects, face recognition and etc. | 8.8 | Dominant colors | Get colors service | 422 | Example_1 | {"detail": [{"loc": [], "msg": "", "type": ""}]} | {"title": "HTTPValidationError", "type": "object", "properties": {"detail": {"title": "Detail", "type": "array", "items": {"title": "ValidationError", "required": ["loc", "msg", "type"], "type": "object", "properties": {"loc": {"title": "Location", "type": "array", "items": {"type": "string"}}, "msg": {"title": "Message", "type": "string"}, "type": {"title": "Error Type", "type": "string"}}}}}} |
9a8129ba-2305-4acc-8036-73c2cc04be54/a9c0e56e-fe35-4d85-bf0a-fba415a18e27/1/0 | Regim | API for extracting data from image: colors, objects, face recognition and etc. | 8.8 | Dominant colors | Get colors service | 200 | Example_1 | {"data": {"exif": {}, "colors": [], "closestColors": [], "geodata": {}, "objects": [], "segments": [], "objectsShortList": [], "objectsCount": {}, "translated": {}, "faces": [], "img_res": "", "rotation": {}, "orientation": ""}, "info": {"args": {}, "exectime": "", "error": "", "def_palette": {}}} | {"title": "remoC", "type": "object", "properties": {"data": {"title": "dataC", "type": "object", "properties": {"exif": {"title": "Exif", "type": "object"}, "colors": {"title": "Colors", "type": "array", "items": {}}, "closestColors": {"title": "Closestcolors", "type": "array", "items": {}}, "geodata": {"title": "Geodata", "type": "object"}, "objects": {"title": "Objects", "type": "array", "items": {"type": "object"}}, "segments": {"title": "Segments", "type": "array", "items": {}}, "objectsShortList": {"title": "Objectsshortlist", "type": "array", "items": {}}, "objectsCount": {"title": "Objectscount", "type": "object"}, "translated": {"title": "Translated", "type": "object"}, "faces": {"title": "Faces", "type": "array", "items": {}}, "img_res": {"title": "Img Res", "type": "string"}, "rotation": {"title": "Rotation", "type": "object"}, "orientation": {"title": "Orientation", "type": "string"}}}, "info": {"title": "infoC", "type": "object", "properties": {"args": {"title": "Args", "type": "object"}, "exectime": {"title": "Exectime", "type": "string"}, "error": {"title": "Error", "type": "string"}, "def_palette": {"title": "Def Palette", "type": "object"}}}}} |
9a8129ba-2305-4acc-8036-73c2cc04be54/e009d30e-14b6-45bd-ba77-d3fe81a636b4/0/0 | Regim | API for extracting data from image: colors, objects, face recognition and etc. | 8.8 | Object recognition and segmentation | Object segmentation | 422 | Example_1 | {"detail": [{"loc": [], "msg": "", "type": ""}]} | {"title": "HTTPValidationError", "type": "object", "properties": {"detail": {"title": "Detail", "type": "array", "items": {"title": "ValidationError", "required": ["loc", "msg", "type"], "type": "object", "properties": {"loc": {"title": "Location", "type": "array", "items": {"type": "string"}}, "msg": {"title": "Message", "type": "string"}, "type": {"title": "Error Type", "type": "string"}}}}}} |
9a8129ba-2305-4acc-8036-73c2cc04be54/e009d30e-14b6-45bd-ba77-d3fe81a636b4/1/0 | Regim | API for extracting data from image: colors, objects, face recognition and etc. | 8.8 | Object recognition and segmentation | Object segmentation | 200 | Example_1 | {"data": {"exif": {}, "colors": [], "geodata": {}, "objects": [], "segments": [], "objectsShortList": [], "objectsCount": {}, "translated": {}, "faces": [], "img_res": "", "rotation": {}, "orientation": ""}, "info": {"args": {}, "exectime": "", "error": ""}} | {"title": "remo", "type": "object", "properties": {"data": {"title": "data", "type": "object", "properties": {"exif": {"title": "Exif", "type": "object"}, "colors": {"title": "Colors", "type": "array", "items": {}}, "geodata": {"title": "Geodata", "type": "object"}, "objects": {"title": "Objects", "type": "array", "items": {"type": "object"}}, "segments": {"title": "Segments", "type": "array", "items": {}}, "objectsShortList": {"title": "Objectsshortlist", "type": "array", "items": {}}, "objectsCount": {"title": "Objectscount", "type": "object"}, "translated": {"title": "Translated", "type": "object"}, "faces": {"title": "Faces", "type": "array", "items": {}}, "img_res": {"title": "Img Res", "type": "string"}, "rotation": {"title": "Rotation", "type": "object"}, "orientation": {"title": "Orientation", "type": "string"}}}, "info": {"title": "info", "type": "object", "properties": {"args": {"title": "Args", "type": "object"}, "exectime": {"title": "Exectime", "type": "string"}, "error": {"title": "Error", "type": "string"}}}}} |
f739467e-1cc5-491d-a659-5a089651ed17/69aaf8ee-482b-48ee-9f7b-c72271dd1ef7/0/0 | Scene Classification | Scene Classification
This scene classification model identifies the scenes in images and videos at scale. The model checks the scene location (indoor/outdoor) and groups them under different categories based on their attributes. It returns multiple scene labels and detailed attributes.
Scene classification API is used to detect indoor and outdoor scenes in an image. | 7.4 | Scene classification from image |
For more details contact us | 200 | Response | {"Indoor": false, "categories": ["wheat_field", "hayfield", "corn_field", "farm", "pasture"], "attributes": ["open area", "natural", "natural light", "vegetation", "far-away horizon", "grass", "camping", "sunny", "foliage"]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"Indoor": {"type": "boolean"}, "categories": {"type": "array", "items": {"type": "string"}}, "attributes": {"type": "array", "items": {"type": "string"}}}, "required": ["Indoor", "attributes", "categories"]} |
44f5400d-14af-4abb-ad12-044a94611ffc/4d25038a-b13b-461b-8526-18bad17049b0/0/0 | Change facial expressions | Use advanced image processing technology to edit the expressions of human faces in images. Supports application scenarios such as real-time effects and photo editing. | 8.1 | Change facial expressions | Change facial expressions | 401 | Example | {"message": "Invalid API key in request"} | {"message": {"type": "String", "required": true, "example": "Invalid API key in request", "description": "Error Message."}} |
44f5400d-14af-4abb-ad12-044a94611ffc/4d25038a-b13b-461b-8526-18bad17049b0/1/0 | Change facial expressions | Use advanced image processing technology to edit the expressions of human faces in images. Supports application scenarios such as real-time effects and photo editing. | 8.1 | Change facial expressions | Change facial expressions | 200 | Success | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 0, "data": {"image": ""}} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image": {"type": "String", "required": false, "description": "The result image, returning the Base64 encoding of the image."}}}} |
44f5400d-14af-4abb-ad12-044a94611ffc/4d25038a-b13b-461b-8526-18bad17049b0/1/1 | Change facial expressions | Use advanced image processing technology to edit the expressions of human faces in images. Supports application scenarios such as real-time effects and photo editing. | 8.1 | Change facial expressions | Change facial expressions | 200 | Error | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 400, "error_code_str": "ERROR_PARAMETERS", "error_msg": "image cannot be empty"} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image": {"type": "String", "required": false, "description": "The result image, returning the Base64 encoding of the image."}}}} |
cc826ee7-97c6-4094-b23f-d27fc4a1656f/8654a659-baec-4f82-b78a-efefdf819e91/1/0 | NSFW | This API processes images and detects sexual content in them, marking the images as Safe For Work (SFW) or Not Safe For Work (NSFW). [ or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 422 | Missing image/url | {"detail": "Missing image or url field."} | {"type": "object", "properties": {"detail": {"type": "string"}}} |
cc826ee7-97c6-4094-b23f-d27fc4a1656f/8654a659-baec-4f82-b78a-efefdf819e91/2/0 | NSFW | This API processes images and detects sexual content in them, marking the images as Safe For Work (SFW) or Not Safe For Work (NSFW). [ or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 200 | Unsupported media type | {"results": [{"status": {"code": "failure", "message": "Unsupported media type. Expected one of ['image/jpeg', 'image/png']. Got 'text/plain'."}, "name": "file.txt", "md5": "d41d8cd98f00b204e9800998ecf8427e", "entities": []}]} | {"type": "object", "properties": {"results": {"type": "array", "items": {"type": "object", "properties": {"status": {"type": "object", "properties": {"code": {"type": "string"}, "message": {"type": "string"}}}, "name": {"type": "string"}, "md5": {"type": "string"}, "entities": {"type": "array", "items": {"type": "object", "properties": {"kind": {"type": "string"}, "name": {"type": "string"}, "classes": {"type": "object", "properties": {"nsfw": {"type": "number"}, "sfw": {"type": "number"}}}}}}}}}}} |
cc826ee7-97c6-4094-b23f-d27fc4a1656f/8654a659-baec-4f82-b78a-efefdf819e91/2/1 | NSFW | This API processes images and detects sexual content in them, marking the images as Safe For Work (SFW) or Not Safe For Work (NSFW). [ or PDF file.
Usually such images have extensions: .jpg, .jpeg, .png, .pdf. In case of PDF
each page will be converted to PNG image and processed separately.
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of image file must be less than 16Mb. | 200 | Successful classification | {"results": [{"status": {"code": "ok", "message": "Success"}, "name": "nsfw.jpg", "md5": "6ea449c4645b8811eef1342040725687", "width": 1024, "height": 768, "entities": [{"kind": "classes", "name": "nsfw-classes", "classes": {"nsfw": 0.9582930970937014, "sfw": 0.04170693515334278}}]}]} | {"type": "object", "properties": {"results": {"type": "array", "items": {"type": "object", "properties": {"status": {"type": "object", "properties": {"code": {"type": "string"}, "message": {"type": "string"}}}, "name": {"type": "string"}, "md5": {"type": "string"}, "entities": {"type": "array", "items": {"type": "object", "properties": {"kind": {"type": "string"}, "name": {"type": "string"}, "classes": {"type": "object", "properties": {"nsfw": {"type": "number"}, "sfw": {"type": "number"}}}}}}}}}}} |
735be234-4f1f-433b-9692-7bdeeb7f75e6/25c51e44-f522-4ab3-881f-c87fc8e33b7b/0/0 | Cloudlabs Image Object Detection | Detect multiple objects in an image, extract detected object names | 7.6 | objectDetection (by Image URL) | This endpoint is used to detect objects via image URL | 200 | Response | {"status": "success", "count": 4, "objects": [{"name": "Laptop", "score": 0.8891823, "bounding": {"startX": 135, "startY": 127, "endX": 296, "endY": 270}}, {"name": "Computer keyboard", "score": 0.8127809, "bounding": {"startX": 434, "startY": 190, "endX": 598, "endY": 255}}, {"name": "Table", "score": 0.7982011, "bounding": {"startX": 41, "startY": 138, "endX": 771, "endY": 391}}, {"name": "Computer keyboard", "score": 0.69485223, "bounding": {"startX": 160, "startY": 204, "endX": 274, "endY": 256}}]} | {"type": "object", "properties": {"status": {"type": "string"}, "count": {"type": "integer"}, "objects": {"type": "array", "items": {"type": "object", "properties": {"name": {"type": "string"}, "score": {"type": "number"}, "bounding": {"type": "object", "properties": {"startX": {"type": "integer"}, "startY": {"type": "integer"}, "endX": {"type": "integer"}, "endY": {"type": "integer"}}}}}}}} |
735be234-4f1f-433b-9692-7bdeeb7f75e6/f1094165-7efe-4240-a578-909fda362889/0/0 | Cloudlabs Image Object Detection | Detect multiple objects in an image, extract detected object names | 7.6 | objectDetection (by Image Upload) | This endpoint is used to detect objects via image File upload | 200 | Response | {"status": "success", "count": 4, "objects": [{"name": "Laptop", "score": 0.8891823, "bounding": {"startX": 135, "startY": 127, "endX": 296, "endY": 270}}, {"name": "Computer keyboard", "score": 0.8127809, "bounding": {"startX": 434, "startY": 190, "endX": 598, "endY": 255}}, {"name": "Table", "score": 0.7982011, "bounding": {"startX": 41, "startY": 138, "endX": 771, "endY": 391}}, {"name": "Computer keyboard", "score": 0.69485223, "bounding": {"startX": 160, "startY": 204, "endX": 274, "endY": 256}}]} | {"type": "object", "properties": {"status": {"type": "string"}, "count": {"type": "integer"}, "objects": {"type": "array", "items": {"type": "object", "properties": {"name": {"type": "string"}, "score": {"type": "number"}, "bounding": {"type": "object", "properties": {"startX": {"type": "integer"}, "startY": {"type": "integer"}, "endX": {"type": "integer"}, "endY": {"type": "integer"}}}}}}}} |
6a2132de-1c2d-4de6-abff-38e1e99f0a62/98389214-31c8-41d7-9024-3a3b3f539acb/0/0 | Hairstyle changer | Based on deep learning algorithm, it can add bangs, change long hair, increase the number of hair and other operations to the hairstyle of portrait. In addition to helping users intuitively experience a variety of hair designs and improving the personalized experience of customers in the beauty and hairdressing industry, it can also be used in short videos, social platforms, or integrated into album-type apps to add hair editing play to users' personalized photos to achieve interactive partic... | 8 | Hairstyle changer | Hairstyle changer | 200 | Success | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 0, "data": {"image": ""}} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image": {"type": "String", "required": false, "description": "The result image, returning the Base64 encoding of the image."}}}} |
6a2132de-1c2d-4de6-abff-38e1e99f0a62/98389214-31c8-41d7-9024-3a3b3f539acb/0/1 | Hairstyle changer | Based on deep learning algorithm, it can add bangs, change long hair, increase the number of hair and other operations to the hairstyle of portrait. In addition to helping users intuitively experience a variety of hair designs and improving the personalized experience of customers in the beauty and hairdressing industry, it can also be used in short videos, social platforms, or integrated into album-type apps to add hair editing play to users' personalized photos to achieve interactive partic... | 8 | Hairstyle changer | Hairstyle changer | 200 | Error | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 400, "error_code_str": "ERROR_PARAMETERS", "error_msg": "image cannot be empty"} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}, "data": {"type": "Object", "required": false, "description": "The content of the result data returned.", "properties": {"image": {"type": "String", "required": false, "description": "The result image, returning the Base64 encoding of the image."}}}} |
6a2132de-1c2d-4de6-abff-38e1e99f0a62/98389214-31c8-41d7-9024-3a3b3f539acb/1/0 | Hairstyle changer | Based on deep learning algorithm, it can add bangs, change long hair, increase the number of hair and other operations to the hairstyle of portrait. In addition to helping users intuitively experience a variety of hair designs and improving the personalized experience of customers in the beauty and hairdressing industry, it can also be used in short videos, social platforms, or integrated into album-type apps to add hair editing play to users' personalized photos to achieve interactive partic... | 8 | Hairstyle changer | Hairstyle changer | 401 | Example | {"message": "Invalid API key in request"} | {"message": {"type": "String", "required": true, "example": "Invalid API key in request", "description": "Error Message."}} |
1e7451f7-8747-4592-b7df-23cfacb0cd2d/fb855d97-9564-4889-9550-8e0e6a789a61/0/0 | Face Analyzer | Using cutting-edge AI technology, our API offers comprehensive facial analysis for a given image, providing detailed information about the detected face, including facial position, facial attributes (such as gender, age, expression, attractiveness, eyewear, hairstyle, mask presence, and pose), as well as facial quality metrics (including overall quality score, blur score, lighting score, and facial feature occlusion score). | 7.2 | Face Analyzer | Face Analyzer | 401 | Example | {"message": "Invalid API key in request"} | {"type": "object", "properties": {"message": {"type": "string", "required": true, "example": "Invalid API key in request", "description": "Error Message."}}} |
1e7451f7-8747-4592-b7df-23cfacb0cd2d/fb855d97-9564-4889-9550-8e0e6a789a61/1/0 | Face Analyzer | Using cutting-edge AI technology, our API offers comprehensive facial analysis for a given image, providing detailed information about the detected face, including facial position, facial attributes (such as gender, age, expression, attractiveness, eyewear, hairstyle, mask presence, and pose), as well as facial quality metrics (including overall quality score, blur score, lighting score, and facial feature occlusion score). | 7.2 | Face Analyzer | Face Analyzer | 200 | Success | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 0, "image_width": 0, "image_height": 0, "face_detail_infos": [{"face_rect": {"x": 0, "y": 0, "width": 0, "height": 0}, "face_detail_attributes_info": {"age": 0, "beauty": 0, "emotion": {"type": 0, "probability": 0}, "eye": {"glass": {"type": 0, "probability": 0.99936753511429}, "eye_open": {"type": 0, "probability": 0.99949336051941}, "eyelid_type": {"type": 1, "probability": 0.75467920303345}, "eye_size": {"type": 2, "probability": 0.59152442216873}}, "eyebrow": {"eyebrow_density": {"type": 0, "probability": 0}, "eyebrow_curve": {"type": 0, "probability": 0}, "eyebrow_length": {"type": 0, "probability": 0}}, "gender": {"type": 0, "probability": 0}, "hair": {"length": {"type": 0, "probability": 0}, "bang": {"type": 0, "probability": 0}, "color": {"type": 0, "probability": 0}}, "hat": {"style": {"type": 0, "probability": 0}, "color": {"type": 0, "probability": 0}}, "head_pose": {"pitch": 0, "yaw": 0, "roll": 0}, "mask": {"type": 0, "probability": 0}, "mouth": {"mouth_open": {"type": 0, "probability": 0}}, "moustache": {"type": 0, "probability": 0}, "nose": {"type": 2, "probability": 0.75233882665634}, "shape": {"type": 0, "probability": 0}, "skin": {"type": 0, "probability": 0}, "smile": 0}}]} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}} |
1e7451f7-8747-4592-b7df-23cfacb0cd2d/fb855d97-9564-4889-9550-8e0e6a789a61/1/1 | Face Analyzer | Using cutting-edge AI technology, our API offers comprehensive facial analysis for a given image, providing detailed information about the detected face, including facial position, facial attributes (such as gender, age, expression, attractiveness, eyewear, hairstyle, mask presence, and pose), as well as facial quality metrics (including overall quality score, blur score, lighting score, and facial feature occlusion score). | 7.2 | Face Analyzer | Face Analyzer | 200 | Error | {"request_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "log_id": "3A9BFC5E-3F7C-4D9A-9445-908C6D14AB5B", "error_code": 400, "error_code_str": "ERROR_PARAMETERS", "error_msg": "image cannot be empty"} | {"request_id": {"type": "string", "required": false, "description": "Request ID."}, "log_id": {"type": "string", "required": false, "description": "Log ID."}, "error_code": {"type": "integer", "required": false, "description": "Error Code."}, "error_code_str": {"type": "string", "required": false, "description": "Error Code."}, "error_msg": {"type": "string", "required": false, "description": "Error Message."}} |
644fb82d-3c8e-44a0-9466-8362b79a0a7d/79b147af-7aef-4eac-8a99-d6e208c1816f/0/0 | Object Detection | Extract list of text, boundingBox, score, locale and dimensions from image using (google vision object detection) | null | GET Logo Detection | the important thing is that you should use image as a query name
Example (url?image=“image_url”) | 200 | New Example | {"objects": [{"text": "Chair", "score": 0.843457818031311, "locale": "", "boundingBox": {"tl": {"x": 0.045202311128377914, "y": 0.6389181017875671}, "tr": {"x": 0.4727531671524048, "y": 0.6389181017875671}, "br": {"x": 0.4727531671524048, "y": 0.9685030579566956}, "bl": {"x": 0.045202311128377914, "y": 0.9685030579566956}}}, {"text": "Umbrella", "score": 0.6488758325576782, "locale": "", "boundingBox": {"tl": {"x": 0.18290652334690094, "y": 0.23769409954547882}, "tr": {"x": 0.9811277389526367, "y": 0.23769409954547882}, "br": {"x": 0.9811277389526367, "y": 0.9368109107017517}, "bl": {"x": 0.18290652334690094, "y": 0.9368109107017517}}}], "success": true, "dimensions": {"height": 1200, "width": 1020, "type": "webp"}} | {"type": "object", "properties": {"objects": {"type": "array", "items": {"type": "object", "properties": {"text": {"type": "string"}, "score": {"type": "number"}, "locale": {"type": "string"}, "boundingBox": {"type": "object", "properties": {"tl": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}}, "tr": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}}, "br": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}}, "bl": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}}}}}}}, "success": {"type": "boolean"}, "dimensions": {"type": "object", "properties": {"height": {"type": "integer"}, "width": {"type": "integer"}, "type": {"type": "string"}}}}} |
644fb82d-3c8e-44a0-9466-8362b79a0a7d/b0442ef5-c96c-4ae2-b8a6-776e57d4ca27/0/0 | Object Detection | Extract list of text, boundingBox, score, locale and dimensions from image using (google vision object detection) | null | POST Object Detection | the important thing is that you should use image as a form_data key
Example const data = new FormData(); data.append(‘image’, ‘image_path’); | 200 | New Example | {"objects": [{"text": "Chair", "score": 0.843457818031311, "locale": "", "boundingBox": {"tl": {"x": 0.045202311128377914, "y": 0.6389181017875671}, "tr": {"x": 0.4727531671524048, "y": 0.6389181017875671}, "br": {"x": 0.4727531671524048, "y": 0.9685030579566956}, "bl": {"x": 0.045202311128377914, "y": 0.9685030579566956}}}, {"text": "Umbrella", "score": 0.6488758325576782, "locale": "", "boundingBox": {"tl": {"x": 0.18290652334690094, "y": 0.23769409954547882}, "tr": {"x": 0.9811277389526367, "y": 0.23769409954547882}, "br": {"x": 0.9811277389526367, "y": 0.9368109107017517}, "bl": {"x": 0.18290652334690094, "y": 0.9368109107017517}}}], "success": true, "dimensions": {"height": 1200, "width": 1020, "type": "webp"}} | {"type": "object", "properties": {"objects": {"type": "array", "items": {"type": "object", "properties": {"text": {"type": "string"}, "score": {"type": "number"}, "locale": {"type": "string"}, "boundingBox": {"type": "object", "properties": {"tl": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}}, "tr": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}}, "br": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}}, "bl": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}}}}}}}, "success": {"type": "boolean"}, "dimensions": {"type": "object", "properties": {"height": {"type": "integer"}, "width": {"type": "integer"}, "type": {"type": "string"}}}}} |
a3b83cf2-6c5c-4028-848e-3d192b44af3e/a49b7647-fd90-4233-a3bd-e32eed8f4745/0/0 | Car License Plate Detection | Use an API to perform license plate or car recognition | 0.2 | Car recognition | Send a URL with the cars and get the coordinates of the boxes with the cars inside and license plates.
You can also get confidence, license plate number and country.
Note: Please REAM ME and documentation for more information. | 400 | BAD Example | {"status": "fail", "result": [], "message": "invalid image_url"} | {"type": "object", "properties": {"status": {"type": "string"}, "result": {"type": "array"}, "message": {"type": "string"}}} |
a3b83cf2-6c5c-4028-848e-3d192b44af3e/a49b7647-fd90-4233-a3bd-e32eed8f4745/1/0 | Car License Plate Detection | Use an API to perform license plate or car recognition | 0.2 | Car recognition | Send a URL with the cars and get the coordinates of the boxes with the cars inside and license plates.
You can also get confidence, license plate number and country.
Note: Please REAM ME and documentation for more information. | 200 | OK Example | {"status": "success", "result": [{"license_plate": {"number": "H222HH47", "confidence": 0.97848624, "license_plate_coordinates": {"bottom": 514, "left": 556, "right": 728, "top": 441}, "license_plate_visibility": [{"confidence": 0.9132972, "name": "fully_visible"}, {"confidence": 0.049986165, "name": "invisible"}, {"confidence": 0.016093468, "name": "partly_visible_no_text"}, {"confidence": 0.012294045, "name": "partly_visible"}, {"confidence": 0.008329197, "name": "fully_visible_no_text"}], "country": [{"confidence": 0.99999976, "name": "RU"}, {"confidence": 1.3062662e-07, "name": "BY"}, {"confidence": 4.773197e-08, "name": "AE"}, {"confidence": 2.299932e-08, "name": "UZ"}, {"confidence": 1.7414985e-08, "name": "LV"}, {"confidence": 6.135722e-09, "name": "KZ"}, {"confidence": 4.8630504e-09, "name": "TJ"}, {"confidence": 1.6597818e-09, "name": "EST"}, {"confidence": 1.3707686e-09, "name": "SA"}, {"confidence": 1.1437e-09, "name": "SRB"}, {"confidence": 9.423607e-10, "name": "TM"}, {"confidence": 6.842398e-10, "name": "KG"}, {"confidence": 4.10423e-10, "name": "AM"}, {"confidence": 2.733928e-10, "name": "LT"}, {"confidence": 2.0497787e-10, "name": "MD"}, {"confidence": 1.4537214e-10, "name": "FIN"}, {"confidence": 1.2323746e-10, "name": "GE"}, {"confidence": 7.907517e-11, "name": "AZ"}, {"confidence": 7.140562e-11, "name": "MX"}, {"confidence": 3.9685043e-11, "name": "UA"}, {"confidence": 1.9218491e-11, "name": "AR"}, {"confidence": 1.6187543e-11, "name": "BR"}, {"confidence": 7.3318435e-12, "name": "IN"}, {"confidence": 1.5106668e-12, "name": "VN"}]}, "car": {"car_coordinates": {"bottom": 635, "left": 28, "right": 821, "top": 24}, "orientation": [{"confidence": 0.8820999, "name": "front"}, {"confidence": 0.06136949, "name": "back"}, {"confidence": 0.056530543, "name": "side"}]}}], "message": "1 cars detected"} | {"type": "object", "properties": {"status": {"type": "string"}, "result": {"type": "array", "items": {"type": "object", "properties": {"license_plate": {"type": "object", "properties": {"number": {"type": "string"}, "confidence": {"type": "number"}, "license_plate_coordinates": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}}, "license_plate_visibility": {"type": "array", "items": {"type": "object", "properties": {"confidence": {"type": "number"}, "name": {"type": "string"}}}}, "country": {"type": "array", "items": {"type": "object", "properties": {"confidence": {"type": "number"}, "name": {"type": "string"}}}}}}, "car": {"type": "object", "properties": {"car_coordinates": {"type": "object", "properties": {"bottom": {"type": "integer"}, "left": {"type": "integer"}, "right": {"type": "integer"}, "top": {"type": "integer"}}}, "orientation": {"type": "array", "items": {"type": "object", "properties": {"confidence": {"type": "number"}, "name": {"type": "string"}}}}}}}}}, "message": {"type": "string"}}} |
78474dc8-4c7e-407c-bb84-01fc49b90e28/d1eb7677-c948-4409-ab5f-4d179f0cbda9/0/0 | Free Recognized Video Content | Free Recognized Video Content | null | /recognize-video-detail | 200 | null | {"status": 1, "url": "http://vibktprfx-prod-prod-damo-eas-cn-shanghai.oss-cn-shanghai.aliyuncs.com/generative-cartoon/2023-09-09/1d73851a-7d53-416b-8606-01dc2f09db52/20230909_235408006889_dmbpxu56o3.jpg?Expires=1694276651&OSSAccessKeyId=LTAI4FoLmvQ9urWXgSRpDvh1&Signature=%2FcT4QU5F7%2FIR2J9Z9a3lvUnwdbI%3D"} | {"type": "object", "properties": {"status": {"type": "integer"}, "url": {"type": "string"}}, "required": ["status", "url"], "x-apifox-ignore-properties": [], "x-apifox-orders": ["status", "url"]} |
|
78474dc8-4c7e-407c-bb84-01fc49b90e28/45e5f066-3271-4525-a5de-62ce74f8f625/0/0 | Free Recognized Video Content | Free Recognized Video Content | null | /recognize-video | 200 | null | {"status": 1, "url": "http://vibktprfx-prod-prod-damo-eas-cn-shanghai.oss-cn-shanghai.aliyuncs.com/generative-cartoon/2023-09-09/1d73851a-7d53-416b-8606-01dc2f09db52/20230909_235408006889_dmbpxu56o3.jpg?Expires=1694276651&OSSAccessKeyId=LTAI4FoLmvQ9urWXgSRpDvh1&Signature=%2FcT4QU5F7%2FIR2J9Z9a3lvUnwdbI%3D"} | {"type": "object", "properties": {"status": {"type": "integer"}, "url": {"type": "string"}}, "required": ["status", "url"], "x-apifox-ignore-properties": [], "x-apifox-orders": ["status", "url"]} |
|
ee87db13-900a-4635-a44a-07acb6cb3762/a841600a-2ec5-4b88-a5fa-53022728efd6/0/0 | Logo Detection | Extract text, boundingBox, score, locale and dimensions from image using (google vision logo detection) | 5.1 | GET Logo Detection | the important thing is that you should use image as a query name
Example (url?image=“image_url”) | 200 | New Example | {"logos": [{"text": "Apple Inc.", "score": 0.9511095881462097, "locale": "", "boundingBox": {"tl": {"x": 919, "y": 38}, "tr": {"x": 2998, "y": 38}, "br": {"x": 2998, "y": 2066}, "bl": {"x": 919, "y": 2066}}}], "success": true, "dimensions": {"height": 2160, "width": 3840, "type": "png"}} | {"type": "object", "properties": {"logos": {"type": "array", "items": {"type": "object", "properties": {"text": {"type": "string"}, "score": {"type": "number"}, "locale": {"type": "string"}, "boundingBox": {"type": "object", "properties": {"tl": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}}}, "tr": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}}}, "br": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}}}, "bl": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}}}}}}}}, "success": {"type": "boolean"}, "dimensions": {"type": "object", "properties": {"height": {"type": "integer"}, "width": {"type": "integer"}, "type": {"type": "string"}}}}} |
ee87db13-900a-4635-a44a-07acb6cb3762/f9181c4f-06f2-4440-bea4-add416f01036/0/0 | Logo Detection | Extract text, boundingBox, score, locale and dimensions from image using (google vision logo detection) | 5.1 | POST Logo Detection | the important thing is that you should use image as a form_data key
Example const data = new FormData(); data.append(‘image’, ‘image_path’); | 200 | New Example | {"logos": [{"text": "Apple Inc.", "score": 0.9511095881462097, "locale": "", "boundingBox": {"tl": {"x": 919, "y": 38}, "tr": {"x": 2998, "y": 38}, "br": {"x": 2998, "y": 2066}, "bl": {"x": 919, "y": 2066}}}], "success": true, "dimensions": {"height": 2160, "width": 3840, "type": "png"}} | {"type": "object", "properties": {"logos": {"type": "array", "items": {"type": "object", "properties": {"text": {"type": "string"}, "score": {"type": "number"}, "locale": {"type": "string"}, "boundingBox": {"type": "object", "properties": {"tl": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}}}, "tr": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}}}, "br": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}}}, "bl": {"type": "object", "properties": {"x": {"type": "integer"}, "y": {"type": "integer"}}}}}}}}, "success": {"type": "boolean"}, "dimensions": {"type": "object", "properties": {"height": {"type": "integer"}, "width": {"type": "integer"}, "type": {"type": "string"}}}}} |
719dc5e9-1ffc-4b97-b8e7-d939d4275369/bbf9ef82-a01f-4a32-9bb8-8168192bc34e/0/0 | Webit Face | Face Detection, Verification, Similarity, Age, Gender, Race, Emotion, Landmarks and Parts analysis. | 6 | Face Parts and Landmarks | Perform A.I. powered Face Landmarks detection in order to extract face parts coordinates, lines and landmarks from multiple faces in bounding boxes. | 200 | Response | {"status": "success", "data": {"input_source": "url", "faces": [{"face_id": 1, "landmarks": [{"confidence": 0.80371, "part": "nose", "coordinates": {"x": 47.23809523809524, "y": 40.714285714285715}, "adiacent_parts": ["right_eye", "left_eye"]}, {"confidence": 0.34216, "part": "neck", "coordinates": {"x": 43.04761904761905, "y": 53.857142857142854}, "adiacent_parts": ["nose"]}, {"confidence": 0.75839, "part": "right_eye", "coordinates": {"x": 44, "y": 33.714285714285715}, "adiacent_parts": ["right_ear"]}, {"confidence": 0.79953, "part": "left_eye", "coordinates": {"x": 50.476190476190474, "y": 35.285714285714285}, "adiacent_parts": []}, {"confidence": 0.55166, "part": "right_ear", "coordinates": {"x": 38.38095238095238, "y": 35.285714285714285}, "adiacent_parts": []}], "bounding_box": {"start": {"x": 38.38095238095238, "y": 33.714285714285715}, "end": {"x": 50.476190476190474, "y": 53.857142857142854}}}, {"face_id": 2, "landmarks": [{"confidence": 0.6995, "part": "nose", "coordinates": {"x": 59.714285714285715, "y": 31.571428571428573}, "adiacent_parts": ["right_eye", "left_eye"]}, {"confidence": 0.29553, "part": "neck", "coordinates": {"x": 64.85714285714286, "y": 51.142857142857146}, "adiacent_parts": ["nose"]}, {"confidence": 0.38189, "part": "right_eye", "coordinates": {"x": 56.95238095238095, "y": 26.571428571428573}, "adiacent_parts": []}, {"confidence": 0.57546, "part": "left_eye", "coordinates": {"x": 64.38095238095238, "y": 29.285714285714285}, "adiacent_parts": ["left_ear"]}, {"confidence": 0.37704, "part": "left_ear", "coordinates": {"x": 70.38095238095238, "y": 33.142857142857146}, "adiacent_parts": []}], "bounding_box": {"start": {"x": 56.95238095238095, "y": 26.571428571428573}, "end": {"x": 70.38095238095238, "y": 51.142857142857146}}}], "faces_count": 2}, "message": null} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"status": {"type": "string"}, "data": {"type": "object", "properties": {"input_source": {"type": "string"}, "faces": {"type": "array", "items": {"type": "object", "properties": {"face_id": {"type": "integer"}, "landmarks": {"type": "array", "items": {"type": "object", "properties": {"confidence": {"type": "number"}, "part": {"type": "string"}, "coordinates": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}, "required": ["x", "y"]}, "adiacent_parts": {"type": "array", "items": {"type": "string"}}}, "required": ["adiacent_parts", "confidence", "coordinates", "part"]}}, "bounding_box": {"type": "object", "properties": {"start": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}, "required": ["x", "y"]}, "end": {"type": "object", "properties": {"x": {"type": "number"}, "y": {"type": "number"}}, "required": ["x", "y"]}}, "required": ["end", "start"]}}, "required": ["bounding_box", "face_id", "landmarks"]}}, "faces_count": {"type": "integer"}}, "required": ["faces", "faces_count", "input_source"]}, "message": {"type": "null"}}, "required": ["data", "message", "status"]} |
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