add rest of the functionality

app.py

@@ -1,6 +1,10 @@
 from fastai.vision.all import *
 from fastapi import FastAPI
 from fastapi.responses import HTMLResponse
+from pydantic import BaseModel
+from PIL import Image
+import io
+import base64
 
 app = FastAPI()
 
@@ -22,48 +26,30 @@ def read_root():
     html_content = "<p>This is a model inference point for the <a href='https://huggingface.co/spaces/vishalbakshi/isitadigit'>isitadigit</a> space</p>"
     return HTMLResponse(content=html_content)
 
+class ImageData(BaseModel):
+    image: str
+
+def predict_image(img):
+    img = img.convert("L")
+    img = img.resize((28, 28))
+    img = np.array(img)
+    return f"{learn.predict(img)[0][0]:.2f}"
+
+@app.post("/predict")
+async def predict(data: ImageData):
+    try:
+        image_data = base64.b64decode(data.image)
+        img = Image.open(io.BytesIO(image_data))
+        probability = predict_image(img)
+        return {"probability": probability}
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    
 if __name__ == "__main__":
     import uvicorn
     uvicorn.run(app, host="0.0.0.0", port=7860)
 
 
-# from fastapi import FastAPI, HTTPException
-# from pydantic import BaseModel
-# from PIL import Image
-# import io
-# import base64
-# import uvicorn
-
-
-
-# # Load the model
-# learn = load_learner('model.pkl')
 
-# app = FastAPI()
 
-# class ImageData(BaseModel):
-#     image: str
 
-# def predict_image(img):
-#     img = img.convert("L")
-#     img = img.resize((28, 28))
-#     img = np.array(img)
-#     return f"{learn.predict(img)[0][0]:.2f}"
-
-# @app.get("/")
-# def read_root():
-#     return {"message": "Hello World"}
-
-# @app.post("/predict")
-# async def predict(data: ImageData):
-#     try:
-#         image_data = base64.b64decode(data.image)
-#         img = Image.open(io.BytesIO(image_data))
-#         probability = predict_image(img)
-#         return {"probability": probability}
-#     except Exception as e:
-#         raise HTTPException(status_code=400, detail=str(e))
-    
-# if __name__ == "__main__":
-#     import uvicorn
-#     uvicorn.run(app, host="0.0.0.0", port=7860)