Update FastAPI.py
Browse files- FastAPI.py +31 -15
FastAPI.py
CHANGED
@@ -37,8 +37,13 @@ class ImgInput(BaseModel):
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image_url: HttpUrl
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class ImgOutput(BaseModel):
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label: str
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def recognize_face(image_url: HttpUrl) -> ImgOutput:
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storage.child().download("Faces/pkl/face_encodings.pkl","face_encodings.pkl")
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@@ -53,28 +58,38 @@ def recognize_face(image_url: HttpUrl) -> ImgOutput:
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face_encodings = data["encodings"]
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labels = data["labels"]
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# Load a new image you want to recognize
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new_image = cv2.imread("examp.jpg")
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# Compare the new face encoding to the stored encodings
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results = face_recognition.compare_faces(face_encodings, new_face_encoding[0])
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if result:
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return ImgOutput(label=labels[i])
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def add_face(image_url: HttpUrl,user_name : str)
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# Downloading image
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response = requests.get(image_url)
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with open("examp.jpg", 'wb') as file:
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@@ -118,4 +133,5 @@ async def scoring_endpoint(item:ImgInput):
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@app.post('/user/')
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async def scoring_endpoint(item:ImgSave):
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add_face(item.image_url, item.user_name)
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image_url: HttpUrl
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class ImgOutput(BaseModel):
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label: list
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class UserSaved(BaseModel):
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label: str
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def recognize_face(image_url: HttpUrl) -> ImgOutput:
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storage.child().download("Faces/pkl/face_encodings.pkl","face_encodings.pkl")
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face_encodings = data["encodings"]
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labels = data["labels"]
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# Load the new image you want to recognize
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new_image = cv2.imread("examp.jpg")
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# Find face encodings in the new image
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new_face_encodings = face_recognition.face_encodings(new_image)
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if len(new_face_encodings) == 0:
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print("No faces found in the new image.")
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return ImgOutput(label=["unable to detect"])
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else:
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output_labels = []
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for new_face_encoding in new_face_encodings:
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# Compare the new face encoding to the stored encodings
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results = face_recognition.compare_faces(face_encodings, new_face_encoding)
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for i, result in enumerate(results):
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if result:
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output_labels.append(labels[i])
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os.remove("examp.jpg")
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if output_labels:
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return ImgOutput(label=output_labels)
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else:
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out = ["unable to detect"]
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return ImgOutput(label=out)
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def add_face(image_url: HttpUrl,user_name : str):
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# Downloading image
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response = requests.get(image_url)
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with open("examp.jpg", 'wb') as file:
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@app.post('/user/')
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async def scoring_endpoint(item:ImgSave):
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add_face(item.image_url, item.user_name)
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results = ["User Saved"]
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return ImgOutput(label=results)
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