Upload app.py

app.py

@@ -12,28 +12,43 @@ app = FastAPI()
 
 # Initialize MediaPipe Face Detection
 mp_face_detection = mp.solutions.face_detection
-face_detection = mp_face_detection.FaceDetection(min_detection_confidence=0.2)
+face_detection = mp_face_detection.FaceDetection(min_detection_confidence=0.5)
 
 def buscar_existe(image):
-    existe = "no"
-    print("resultado: ", image.shape)
-    
-    # Convert the image to RGB
+    # Convert the image to RGB (MediaPipe requires RGB input)
     image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    
+    # Process the image
     results = face_detection.process(image_rgb)
 
+    # Check if any faces were detected
     if results.detections:
-        existe = "si"
-    
-    return existe
-  
+        return "si"
+    else:
+        return "no"
+
 # Ruta de predicción
 @app.post('/predict/')
 async def predict(file: UploadFile = File(...)):
     try:
-        image = Image.open(BytesIO(await file.read()))
-        image = np.asarray(image)
-        prediction = buscar_existe(image)        
+        # Read the file
+        contents = await file.read()
+        image = Image.open(BytesIO(contents))
+        
+        # Convert PIL Image to numpy array
+        image_np = np.array(image)
+        
+        # If the image is RGB, convert to BGR (OpenCV uses BGR)
+        if image_np.shape[-1] == 3:
+            image_np = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
+        
+        # Perform face detection
+        prediction = buscar_existe(image_np)
+        
         return {"prediction": prediction}
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/")
+async def root():
+    return {"message": "Face Detection API is running"}