Update app.py

app.py

@@ -4,31 +4,53 @@ import gradio as gr
 import tensorflow as tf
 import numpy as np
 from PIL import Image
+import traceback
 
 # Load model
 model = tf.keras.models.load_model("MobileNet_model.h5")
 class_names = ["Fake", "Low", "Medium", "High"]
 
 def predict_image(img):
-    if img is None:
-        return {"error": "No image provided"}
     try:
+        if img is None:
+            return {"error": "No image provided"}
+            
+        # If img is a file path, open it
+        if isinstance(img, str):
+            img = Image.open(img)
+            
+        # Ensure it's a PIL Image
+        if not isinstance(img, Image.Image):
+            return {"error": f"Expected PIL Image, got {type(img)}"}
+            
         img = img.resize((128, 128))
         img_array = np.array(img) / 255.0
+        
+        # Handle grayscale images
+        if len(img_array.shape) == 2:
+            img_array = np.stack((img_array,) * 3, axis=-1)
+        # Handle RGBA images
+        elif img_array.shape[2] == 4:
+            img_array = img_array[:, :, :3]
+            
         img_array = np.expand_dims(img_array, axis=0)
         predictions = model.predict(img_array)
         class_index = np.argmax(predictions, axis=1)[0]
         confidence_scores = {class_names[i]: float(predictions[0][i]) for i in range(len(class_names))}
         return {"Predicted Class": class_names[class_index], "Confidence Scores": confidence_scores}
     except Exception as e:
-        return {"error": str(e)}
+        return {"error": str(e), "traceback": traceback.format_exc()}
 
+# Create interface with explicit input type
 iface = gr.Interface(
     fn=predict_image,
-    inputs=gr.Image(type="pil"),
-    outputs="json"
+    inputs=gr.Image(type="pil", label="Upload Image"),
+    outputs=gr.JSON(),
+    examples=[["example1.jpg"], ["example2.jpg"]],
+    title="Fire Detection API",
+    description="Upload an image to detect fire presence and intensity"
 )
 
-# Add show_error=True to enable verbose error reporting
-iface.launch(server_name="0.0.0.0", server_port=7860, show_error=True)  # Fix for Hugging Face
+# Launch with debugging enabled
+iface.launch(server_name="0.0.0.0", server_port=7860, share=True, debug=True, show_error=True)