🚀 Automated OCR deployment from GitHub Actions

=0.1.4

@@ -20,6 +20,6 @@ Requirement already satisfied: exceptiongroup>=1.0.2 in /opt/hostedtoolcache/Pyt
 Requirement already satisfied: sniffio>=1.1 in /opt/hostedtoolcache/Python/3.10.19/x64/lib/python3.10/site-packages (from anyio->httpx<1,>=0.23.0->huggingface-hub>=0.30) (1.3.1)
 Requirement already satisfied: click>=8.0.0 in /opt/hostedtoolcache/Python/3.10.19/x64/lib/python3.10/site-packages (from typer-slim->huggingface-hub>=0.30) (8.3.1)
 Downloading hf_transfer-0.1.9-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.6 MB)
-   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.6/3.6 MB 35.2 MB/s  0:00:00
+   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.6/3.6 MB 175.7 MB/s  0:00:00
 Installing collected packages: hf-transfer
 Successfully installed hf-transfer-0.1.9

app.py

@@ -142,7 +142,7 @@ with gr.Blocks(title="OCR Text Detection", theme=gr.themes.Soft(), css=css) as d
             # Demo images gallery
             if sample_images:
                 gr.Markdown("### Demo Images (Click to load)")
-                demo_gallery = gr.Gallery(value=sample_images, columns=3, rows=1, height=150, show_label=False, container=True, preview=False, object_fit="scale-down")
+                demo_gallery = gr.Gallery(value=sample_images, columns=3, rows=1, height=210, show_label=False, container=True, preview=False, object_fit="scale-down")
         
         # Column 2: Processed image and confidence slider
         with gr.Column(scale=1):
@@ -191,8 +191,20 @@ with gr.Blocks(title="OCR Text Detection", theme=gr.themes.Soft(), css=css) as d
         annot, text = process_ocr(img, conf_thresh)
         return annot, gr.update(visible=True, value=text or "")
     
-    image_input.change(fn=on_change, inputs=[image_input, confidence_slider], outputs=[annotated_output, text_output])
-    confidence_slider.change(fn=on_change, inputs=[image_input, confidence_slider], outputs=[annotated_output, text_output])
+    # Process image when it changes - store event to allow cancellation
+    process_event = image_input.change(
+        fn=on_change, 
+        inputs=[image_input, confidence_slider], 
+        outputs=[annotated_output, text_output]
+    )
+    
+    # Confidence slider cancels previous processing to avoid queue buildup
+    confidence_slider.change(
+        fn=on_change, 
+        inputs=[image_input, confidence_slider], 
+        outputs=[annotated_output, text_output],
+        cancels=[process_event]  # Cancel previous image processing
+    )
 
 
 if __name__ == "__main__":