Delete clothes_detect.py

clothes_detect.py

@@ -1,57 +0,0 @@
-import supervision as sv
-import urllib.request
-import numpy as np
-import cv2
-import base64
-from inference_sdk import InferenceHTTPClient
-
-class Image_detect:
-    def __init__(self, key): #pass api key to model
-        self.CLIENT = InferenceHTTPClient(
-            api_url="https://detect.roboflow.com",
-            api_key=key
-        )
-        
-    def __call__(self, path , isurl):    
-###########################  Load Image  #################################       
-        if(isurl): # for url set isurl = 1
-            req = urllib.request.urlopen(path)
-            arr = np.asarray(bytearray(req.read()), dtype=np.uint8)
-            img = cv2.imdecode(arr, -1) # 'Load it as it is'
-        else: # for image file
-            img = cv2.imread(path)
-###########################################################################       
-            
-        
-###########################  Model Detection  #################################
-        # change model_id to use a different model 
-        # can try: 
-        # clothing-segmentation-dataset/1
-        # t-shirts-detector/1
-        # mainmodel/2
-        result = self.CLIENT.infer(path, model_id="mainmodel/2")
-        detections = sv.Detections.from_inference(result)
-        # print(detections)
-###########################################################################
-
-
-###########################  Data proccessing  #################################
-        # only pass the first detection
-        # change 1 -> to len(detections.xyxy) to pass all photos
-        if(detections.confidence.size == 0): 
-            return "Not Found"
-        else:
-            x1, y1, x2, y2 = int(detections.xyxy[0][0]), int(detections.xyxy[0][1]), int(detections.xyxy[0][2]), int(detections.xyxy[0][3])
-            clothes = img[y1: y2, x1: x2]
-            retval , buffer = cv2.imencode('.jpg', clothes)     
-        # create base 64 object
-        jpg_as_text = base64.b64encode(buffer)
-###########################################################################
-        return jpg_as_text
-###########################################################################    
-    
-    
-    
-#  test run  
-# Model = Image_detect("api key")
-# print(Model("test_images/test5.jpg", 0))