Update app.py

app.py

@@ -1,19 +1,27 @@
-import gradio as gr
+from flask import Flask, request, jsonify
 from huggingface_hub import from_pretrained_fastai
+from PIL import Image
+import io
 
-# Load the model from Hugging Face Hub
+app = Flask(__name__)
+
+# Load the model
 learn = from_pretrained_fastai("hugginglearners/brain-tumor-detection-mri")
 
-# Define the prediction function
-def predict(img):
-    # Assuming input is an image, convert it into the format required by the model
+@app.route('/predict', methods=['POST'])
+def predict():
+    # Get image from the request
+    file = request.files['file']
+    img = Image.open(io.BytesIO(file.read()))
+    
+    # Make a prediction
     pred_class, _, probs = learn.predict(img)
-    return {str(pred_class): float(probs.max())}
-
-# Create the Gradio interface
-iface = gr.Interface(fn=predict, inputs="image", outputs="label", 
-                     title="Brain Tumor Detection",
-                     description="Upload an MRI scan to detect brain tumors")
+    
+    # Return the result as JSON
+    return jsonify({
+        'prediction': str(pred_class),
+        'confidence': float(probs.max())
+    })
 
-# Launch the interface
-iface.launch()
+if __name__ == '__main__':
+    app.run(debug=True)