Created classify image API

app.py

@@ -177,19 +177,8 @@ async def upload_image(file: UploadFile = File(...)):
         # Read and convert the image to a PIL Image
         contents = await file.read()
         image = Image.open(io.BytesIO(contents)).convert("RGB")
-
-        # Optional: Transform the image into a tensor for PyTorch
-        transform = transforms.Compose([
-            transforms.Resize((224, 224)),  # Resize to your model's expected input
-            transforms.ToTensor(),          # Convert to tensor
-        ])
-        tensor = transform(image).unsqueeze(0)  # Add batch dimension
-
-        # Dummy model prediction
-        # Replace this with your actual PyTorch model
-        prediction = torch.rand(1).item()
-
-        return JSONResponse(content={"message": "Image received", "prediction": prediction})
+     
+        return JSONResponse(content=classify_img(image), status_code=201)
 
     except Exception as e:
         return JSONResponse(content={"error": str(e)}, status_code=500)