Update app.py

app.py

@@ -18,11 +18,8 @@ import PIL.Image
 import PIL.ImageDraw
 
 # Creating a UDF to draw bounding boxes
-
 @pxt.udf
-def draw_boxes(
-    img: PIL.Image.Image, boxes: list[list[float]]
-) -> PIL.Image.Image:
+def draw_boxes(img: PIL.Image.Image, boxes: list[list[float]]) -> PIL.Image.Image:
     result = img.copy()  # Create a copy of `img`
     d = PIL.ImageDraw.Draw(result)
     for box in boxes:
@@ -52,11 +49,7 @@ def process_video(video_file, model_id, threshold, progress=gr.Progress()):
     )
     
     # Insert video into Pixeltable table
-    videos_table.insert([
-        {
-            'video': video_file.name
-        }
-    ])
+    videos_table.insert([{'video': video_file.name}])
 
     progress(0.3, desc="Running Model...")
 
@@ -113,39 +106,37 @@ with gr.Blocks(theme=Soft()) as demo:
     )
 
     with gr.Row():
-      with gr.Column():
-          with gr.Accordion("What This Demo Does", open=True):
-              gr.Markdown("""
-                1. **Ingests Videos**: Uploads your Video.
-                2. **Process and Retrieve Data**: Store, version, chunk, and retrieve video and frames.
-                3. **Detects Objects**: Leverages Pixeltable's YOLOX integration to produce object detection results.
-                4. **Visualizes Output**: Displays the processed video alongside a sample of the original frames.
-                """)
+        with gr.Column():
+            with gr.Accordion("What This Demo Does", open=True):
+                gr.Markdown("""
+                    1. **Ingests Videos**: Uploads your Video.
+                    2. **Process and Retrieve Data**: Store, version, chunk, and retrieve video and frames.
+                    3. **Detects Objects**: Leverages Pixeltable's YOLOX integration to produce object detection results.
+                    4. **Visualizes Output**: Displays the processed video alongside a sample of the original frames.
+                    """)
 
     # File upload components for ground truth and PDF documents
     with gr.Row():
         video_file = gr.File(label="Upload Video", file_count="single")
 
-  # Add controls for chunking parameters
+    # Add controls for chunking parameters
     with gr.Row():
-          model_id = gr.Dropdown(
+        model_id = gr.Dropdown(
             choices=['yolox_tiny', 'yolox_m', 'yolox_x'],
             value='yolox_tiny',
             label="YOLOX Model"
-      )
+        )
+        threshold = gr.Slider(minimum=0.1, maximum=0.9, value=0.25, step=0.05, label="Threshold")
     
-          threshold = gr.Slider(minimum=0.1, maximum=0.9, value=0.25, step=0.05, label="Threshold")
-     
-      with gr.Column():
-            gr.Examples(
-                examples=[
+    gr.Examples(
+        examples=[
             ["bangkok.mp4", "yolox_tiny", 0.25],
             ["lotr.mp4", "yolox_m", 0.3],
             ["mi.mp4", "yolox_tiny", 0.5],
-                ],
-                inputs=[video_file, model_id, threshold],
-                fn=process_video
-            )
+        ],
+        inputs=[video_file, model_id, threshold],
+        fn=process_video
+    )
     
     # Button to trigger file processing
     process_button = gr.Button("Process Video")
@@ -156,11 +147,11 @@ with gr.Blocks(theme=Soft()) as demo:
     with gr.Row():
         frame_gallery = gr.Gallery(label="Frame Gallery", show_label=True, elem_id="gallery")
 
-    process_button.click(process_video,
-                         inputs=[video_file,
-                                 model_id,
-                                 threshold],
-                         outputs=[output_video, frame_gallery])
+    process_button.click(
+        process_video,
+        inputs=[video_file, model_id, threshold],
+        outputs=[output_video, frame_gallery]
+    )
 
 if __name__ == "__main__":
     demo.launch(debug=True)