Update app.py

app.py

@@ -1,39 +1,28 @@
-import fastapi
+from fastapi import FastAPI
+from transformers import pipeline
+import numpy as np
 
-from fastapi import FastAPI, UploadFile, File
-from transformers import AutoModelForImageClassification
+app = FastAPI(docs_url="/")
 
-
-app = FastAPI()
-
-
-app.add_route("/", lambda scope: {"message": "Hello, world!"})
-
-def preprocess_image(image: UploadFile):
+def preprocess_image(image: np.ndarray):
     # Resize the image to a fixed size
     image = image.resize((224, 224))
-
-    # Convert the image to a NumPy array
-    image = np.array(image)
-
     # Normalize the image
     image = image / 255.0
-
     # Return the image
     return image
 
-
 @app.post("/predict")
-async def predict_endpoint(
-    image: UploadFile = File(...)
-):  
+def predict_endpoint(image: np.ndarray):
+    # Preprocess the image
     image = preprocess_image(image)
 
+    # Create a pipeline for image classification
+    classifier = pipeline("andupets/real-estate-image-classification-30classes")
 
-    return JSONResponse({"prediction": "0.67 %"})
-
+    # Classify the image
+    result = classifier(image)
 
-if __name__ == "__main__":
-    import uvicorn
+    # Return the classification result
+    return result
 
-    uvicorn.run(app, host="0.0.0.0", port=8000)