Update app.py

app.py

@@ -1,294 +1,31 @@
 import gradio as gr
-import pandas as pd
-from detector import (
-    yolov8_detect,
-    download_sample_images,
-    get_ocr_status,
-    ADVANCED_OCR_AVAILABLE,
-    OCR_AVAILABLE
-)
+from ui import UIComponents
 
-try:
-    from advanced_ocr import get_available_models
-except ImportError:
-    def get_available_models():
-        return {}
-
-download_sample_images()
-
-ocr_status = get_ocr_status()
-custom_css = """
-.gradio-container {
-    max-width: 1200px !important;
-    margin: 0 auto;
-}
-
-.main-header {
-    text-align: center;
-    margin-bottom: 2rem;
-    padding: 1rem;
-}
-
-.main-title {
-    font-size: 2rem;
-    font-weight: 600;
-    color: #333;
-    margin: 0;
-}
-
-.subtitle {
-    color: #666;
-    font-size: 1rem;
-    margin: 0.5rem 0;
-}
-
-.status-info {
-    font-size: 0.9rem;
-    color: #888;
-    margin: 0.5rem 0;
-}
-
-.section-gap {
-    margin: 1.5rem 0;
-}
-"""
-
-def toggle_sections(extract_text_checked, crop_checked):
-    show_gallery = bool(extract_text_checked and crop_checked)
-    show_ocr = bool(extract_text_checked)
-    return (
-        gr.update(visible=show_gallery),
-        gr.update(visible=show_ocr),
-    )
-
-def get_ocr_status_text():
-    if ADVANCED_OCR_AVAILABLE:
-        return "Advanced OCR Available"
-    elif OCR_AVAILABLE:
-        return "Basic OCR Available"
-    else:
-        return "OCR Not Available"
-
-with gr.Blocks(css=custom_css, title="AI Helmet Detection System") as demo:
+def create_app():
+    ui = UIComponents()
     
-    gr.HTML(f"""
-        <div class="main-header">
-            <h1 class="main-title">AI Helmet Detection System</h1>
-            <p class="subtitle">Motorcyclist safety monitoring with license plate recognition</p>
-            <p class="status-info">YOLOv11 • {get_ocr_status_text()} • Real-time Processing</p>
-        </div>
-    """)
-
-    with gr.Tabs():
-        with gr.TabItem("Detection"):
-            with gr.Row():
-                with gr.Column(scale=1):
-                    gr.Markdown("### Settings")
-                    
-                    input_image = gr.Image(
-                        type="filepath", 
-                        label="Upload Image", 
-                        sources=["upload", "webcam"]
-                    )
-                    
-                    with gr.Row():
-                        image_size = gr.Slider(
-                            minimum=320, maximum=1280, value=640, step=32,
-                            label="Image Size"
-                        )
-                    
-                    with gr.Row():
-                        conf_threshold = gr.Slider(
-                            minimum=0.0, maximum=1.0, value=0.4, step=0.05,
-                            label="Confidence"
-                        )
-                        iou_threshold = gr.Slider(
-                            minimum=0.0, maximum=1.0, value=0.5, step=0.05,
-                            label="IoU Threshold"
-                        )
-                    
-                    show_stats = gr.Checkbox(
-                        value=True, 
-                        label="Show Statistics"
-                    )
-                    crop_plates = gr.Checkbox(
-                        value=True, 
-                        label="Extract License Plates"
-                    )
-                    
-                    if ocr_status["any_available"]:
-                        extract_text = gr.Checkbox(
-                            value=False,
-                            label="Enable OCR"
-                        )
-                        ocr_on_no_helmet = gr.Checkbox(
-                            value=True,
-                            label="Auto-OCR for No Helmet"
-                        )
-
-                        if ADVANCED_OCR_AVAILABLE:
-                            models = get_available_models()
-                            model_choices = [("Auto (Recommended)", "auto"), ("Basic EasyOCR", "basic")]
-                            for key, info in models.items():
-                                model_choices.append((info['name'], key))
-                            selected_ocr_model = gr.Dropdown(
-                                choices=model_choices,
-                                value="auto",
-                                label="OCR Model"
-                            )
-                        else:
-                            selected_ocr_model = gr.State("basic")
-
-                        gr.Markdown("*Note: OCR processing may increase detection time.*")
-                    else:
-                        extract_text = gr.Checkbox(
-                            value=False,
-                            label="OCR Not Available",
-                            interactive=False
-                        )
-                        ocr_on_no_helmet = gr.Checkbox(
-                            value=False,
-                            label="Auto-OCR (Not Available)",
-                            interactive=False
-                        )
-                        selected_ocr_model = gr.State("basic")
-                    
-                    with gr.Row():
-                        submit_btn = gr.Button("Start Detection", variant="primary")
-                        clear_btn = gr.Button("Clear")
-
-                with gr.Column(scale=2):
-                    gr.Markdown("### Results")
-                    
-                    output_image = gr.Image(
-                        type="pil", 
-                        label="Detection Results"
-                    )
-                    
-                    with gr.Row():
-                        output_table = gr.Dataframe(
-                            headers=["Object", "Confidence", "Position", "Dimensions"],
-                            label="Detection Details",
-                            interactive=False
-                        )
-                        output_stats = gr.Textbox(
-                            label="Statistics",
-                            interactive=False,
-                            lines=6
-                        )
-
-                    license_gallery = gr.Gallery(
-                        label="License Plates",
-                        columns=3,
-                        visible=False
-                    )
-
-                    ocr_group = gr.Group(visible=False)
-                    with ocr_group:
-                        plate_text_output = gr.Textbox(
-                            label="OCR Results",
-                            lines=4,
-                            interactive=False
-                        )
-
-                    download_file = gr.File(
-                        label="Download Results (ZIP)",
-                        interactive=False
-                    )
-
-        with gr.TabItem("Examples"):
-            gr.Markdown("### Sample Images")
-            gr.Markdown("Click any example to test the detection system:")
-            
-            gr.Examples(
-                examples=[
-                    ["sample_1.jpg"], 
-                    ["sample_2.jpg"], 
-                    ["sample_3.jpg"], 
-                    ["sample_4.jpg"], 
-                    ["sample_6.jpg"],
-                    ["sample_7.jpg"],
-                    ["sample_8.jpg"],
-                ],
-                inputs=input_image,
-                outputs=[
-                    output_image,
-                    output_table,
-                    output_stats,
-                    license_gallery,
-                    download_file,
-                    plate_text_output,
-                ],
-                fn=lambda img: yolov8_detect(
-                    img, 640, 0.4, 0.5, True, True, True, False
-                ),
-                cache_examples=True
+    with gr.Blocks(css=ui.custom_css, title="AI Helmet Detection System") as demo:
+        ui.create_header()
+
+        with gr.Tabs():
+            with gr.TabItem("Detection"):
+                with gr.Row():
+                    settings_components = ui.create_settings_panel()
+                    results_components = ui.create_results_panel()
+
+            ui.create_examples_tab(
+                settings_components['input_image'], 
+                results_components
             )
+            ui.create_info_tab()
 
-        with gr.TabItem("Info"):
-            gr.Markdown("### System Information")
-            
-            gr.Markdown(f"""
-            **AI Model:** YOLOv11  
-            **Classes:** Helmet, No Helmet, License Plate  
-            **OCR Status:** {get_ocr_status_text()}  
-            **Features:** Detection, extraction, text recognition  
-            
-            **Privacy:** All processing is local. No data stored.  
-            **Usage:** For demonstration and research purposes only.
-            """)
-
-    submit_btn.click(
-        fn=yolov8_detect,
-        inputs=[
-            input_image,
-            image_size,
-            conf_threshold,
-            iou_threshold,
-            show_stats,
-            gr.State(True),
-            crop_plates,
-            extract_text,
-            ocr_on_no_helmet,
-            selected_ocr_model,
-        ],
-        outputs=[
-            output_image,
-            output_table,
-            output_stats,
-            license_gallery,
-            download_file,
-            plate_text_output,
-        ],
-    )
-
-    clear_btn.click(
-        fn=lambda: [None, None, None, None, None, None],
-        inputs=[],
-        outputs=[
-            input_image,
-            output_image,
-            output_table,
-            output_stats,
-            license_gallery,
-            download_file,
-            plate_text_output,
-        ],
-    )
-
-    extract_text.change(
-        fn=toggle_sections,
-        inputs=[extract_text, crop_plates],
-        outputs=[license_gallery, ocr_group],
-    )
-    crop_plates.change(
-        fn=toggle_sections,
-        inputs=[extract_text, crop_plates],
-        outputs=[license_gallery, ocr_group],
-    )
+        ui.setup_event_handlers(settings_components, results_components)
+    
+    return demo
 
 if __name__ == "__main__":
-    demo.launch(
+    app = create_app()
+    app.launch(
         debug=True, 
         share=True,
         server_name="0.0.0.0",