Update app.py

app.py

@@ -14,12 +14,17 @@ def predict_regression(image):
     # Preprocess image
     image = Image.fromarray(image.astype('uint8'))  # Convert numpy array to PIL image
     image = image.resize((150, 150)).convert('RGB')  # Resize the image to 150x150 and convert it to RGB
-    image = np.array(image)
-    image = image / 255.0  # Normalize image to [0, 1] range
+    image = np.array(image) / 255.0  # Normalize image to [0, 1] range
     image = np.expand_dims(image, axis=0)  # Add batch dimension
 
+    # Print statements for debugging
+    print(f"Image shape (after preprocessing): {image.shape}")
+    print(f"Image data (sample): {image[0, :5, :5, 0]}")  # Print a small sample of the data for inspection
+
     # Predict
     prediction = model.predict(image)  # Assuming single regression value
+    print(f"Raw model prediction: {prediction}")
+
     confidences = {labels[i]: np.round(float(prediction[0][i]), 2) for i in range(len(labels))}
     return confidences