Update app.py

app.py

@@ -15,7 +15,10 @@ processor = AutoProcessor.from_pretrained(checkpoint)
 
 def classify_image(image, candidate_labels):
     messages = []
-    candidate_labels = [label.strip() for label in candidate_labels.split(",")] + ["other"]
+    candidate_labels = [label.strip() for label in candidate_labels.split(",") if label.strip()] + ["other"]
+    
+    if len(candidate_labels) == 1:
+        candidate_labels.append("other")
     
     # Blur the image
     image = image.filter(ImageFilter.GaussianBlur(radius=5))
@@ -42,11 +45,11 @@ def classify_image(image, candidate_labels):
 
     # Decision-making logic
     top_label = results[0]["label"]
-    second_label = results[1]["label"]
+    second_label = results[1]["label"] if len(results) > 1 else "None"
 
     # Add messages to understand the scores
     messages.append(f"Top label: {top_label} with score: {results[0]['score']:.2f}")
-    messages.append(f"Second label: {second_label} with score: {results[1]['score']:.2f}")
+    messages.append(f"Second label: {second_label} with score: {results[1]['score']:.2f}" if len(results) > 1 else "")
 
     # Example decision logic for specific scenarios (can be customized further)
     if top_label == candidate_labels[0] and results[0]["score"] >= 0.58 and second_label != "other":
@@ -63,11 +66,19 @@ def classify_image(image, candidate_labels):
 
     return result, top_label, results_for_df, messages
 
+# Default values
+default_labels = "human with beverage,human,beverage"
+default_image_url = "F50tIRvbsAAKHzW.jpeg"
+
+# Download default image
+response = requests.get(default_image_url)
+default_image = Image.open(BytesIO(response.content))
+
 iface = gr.Interface(
     fn=classify_image,
     inputs=[
-        gr.Image(type="pil", label="Upload an Image"),
-        gr.Textbox(label="Candidate Labels (comma separated)")
+        gr.Image(type="pil", label="Upload an Image", value=default_image),
+        gr.Textbox(label="Candidate Labels (comma separated)", value=default_labels)
     ],
     outputs=[
         gr.Label(label="Result"),
@@ -79,12 +90,13 @@ iface = gr.Interface(
     description="""
     **Instructions:**
     
-    1. **Upload an Image**: Drag and drop an image or click to upload an image file.
+    1. **Upload an Image**: Drag and drop an image or click to upload an image file. A default image is provided.
     
     2. **Enter Candidate Labels**: 
        - Provide candidate labels separated by commas. 
        - For example: `human with beverage,human,beverage`
        - The label "other" will automatically be added to the list of candidate labels.
+       - You can enter just one label, and "other" will still be added automatically. Default labels are provided.
     
     3. **View Results**: 
        - The result will indicate whether the specified action (top label) is present in the image.
@@ -94,4 +106,4 @@ iface = gr.Interface(
 )
 
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch()