Upload app.py

app.py

@@ -7,6 +7,9 @@ import os
 import pandas as pd
 import logging
 
+# Disable GPU if not available (for Hugging Face Spaces)
+os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
+
 # Setup logging
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
@@ -30,7 +33,9 @@ def load_model():
         )
         logger.info(f"Model path: {model_path}")
         
-        model = tf.keras.models.load_model(model_path)
+        # Explicitly disable GPU
+        with tf.device('/CPU:0'):
+            model = tf.keras.models.load_model(model_path)
         logger.info("Model loaded successfully!")
     except Exception as e:
         logger.error(f"Model loading failed: {str(e)}")
@@ -46,7 +51,7 @@ def classify_image(image):
             
         # Convert to PIL Image if numpy array
         if isinstance(image, np.ndarray):
-            image = Image.fromarray(image)
+            image = Image.fromarray(image.astype('uint8'))
             
         # Preprocess
         image = image.resize((150, 150))
@@ -56,7 +61,8 @@ def classify_image(image):
             
         # Predict
         if model is not None:
-            pred = model.predict(img_array, verbose=0)
+            with tf.device('/CPU:0'):
+                pred = model.predict(img_array, verbose=0)
             confidence = float(pred[0][0])
         else:
             confidence = 0.75  # Demo value
@@ -75,7 +81,7 @@ def classify_image(image):
         
     except Exception as e:
         logger.error(f"Error: {str(e)}")
-        return {"Error": str(e)}, pd.DataFrame()
+        return {"Error": str(e)}, pd.DataFrame({'Class': ['Cat', 'Dog'], 'Confidence': [0.5, 0.5]})
 
 # Interface
 with gr.Blocks() as demo:
@@ -93,9 +99,8 @@ with gr.Blocks() as demo:
                 x="Class", y="Confidence", y_lim=[0,1]
             )
     
-    # Fixed button click handler - removed api_name
     classify_btn.click(
-        fn=classify_image,
+        classify_image,
         inputs=img_input,
         outputs=[label_out, plot_out]
     )
@@ -113,4 +118,4 @@ with gr.Blocks() as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(server_name="0.0.0.0", server_port=7860)