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| """ | |
| Gradio interface for TextLens OCR application. | |
| """ | |
| import gradio as gr | |
| from .styles import get_custom_css | |
| from .handlers import extract_text_from_image, get_model_status | |
| def create_interface(): | |
| """Create and configure the Gradio interface.""" | |
| with gr.Blocks(css=get_custom_css(), title="TextLens - AI OCR", theme=gr.themes.Soft()) as interface: | |
| # Header | |
| with gr.Row(): | |
| gr.HTML(""" | |
| <div class="header"> | |
| <h1>🔍 TextLens - AI-Powered OCR</h1> | |
| <p style="margin: 10px 0; font-size: 18px;"> | |
| Extract text from images using Microsoft Florence-2 Vision-Language Model | |
| </p> | |
| <p style="margin: 5px 0; opacity: 0.9;"> | |
| Supports multiple image formats • GPU accelerated • High accuracy | |
| </p> | |
| </div> | |
| """) | |
| # Model status | |
| with gr.Row(): | |
| with gr.Column(): | |
| model_status = gr.Markdown( | |
| value=get_model_status(), | |
| elem_classes=["status-box"] | |
| ) | |
| refresh_status_btn = gr.Button("🔄 Refresh Status", size="sm") | |
| # Main interface | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📁 Upload Image", elem_classes=["markdown-text"]) | |
| image_input = gr.Image( | |
| label="Drop image here or click to upload", | |
| type="pil", | |
| sources=["upload", "webcam", "clipboard"], | |
| elem_classes=["upload-box"] | |
| ) | |
| extract_btn = gr.Button( | |
| "🚀 Extract Text", | |
| variant="primary", | |
| size="lg" | |
| ) | |
| gr.Markdown("### 📖 Try with examples:", elem_classes=["markdown-text"]) | |
| gr.Markdown(""" | |
| **Try uploading an image with text:** | |
| • Screenshots of documents | |
| • Photos of signs or billboards | |
| • Handwritten notes | |
| • Menu cards or receipts | |
| • Book pages or articles | |
| """, elem_classes=["markdown-text"]) | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📝 Extracted Text", elem_classes=["markdown-text"]) | |
| text_output = gr.Textbox( | |
| label="Text Output", | |
| lines=15, | |
| max_lines=25, | |
| placeholder="Extracted text will appear here...\n\n• Upload an image to get started\n• The first run may take a few minutes to download the model\n• Subsequent runs will be much faster", | |
| show_copy_button=True | |
| ) | |
| gr.Markdown(""" | |
| **💡 Tips:** | |
| - Higher resolution images generally give better results | |
| - Ensure text is clearly visible and not blurry | |
| - The model works best with printed text but also supports handwriting | |
| - First-time model loading may take 2-3 minutes | |
| """, | |
| elem_classes=["tips-section"] | |
| ) | |
| # Usage instructions | |
| with gr.Row(): | |
| gr.Markdown(""" | |
| ### 🔧 How to Use | |
| 1. **Upload an Image**: Drag and drop, use webcam, or paste from clipboard | |
| 2. **Extract Text**: Click the "Extract Text" button or text extraction will start automatically | |
| 3. **Copy Results**: Use the copy button to copy extracted text | |
| 4. **Try Different Images**: Upload multiple images to test various scenarios | |
| ### ⚡ Features | |
| - **Vision-Language Model**: Uses Microsoft Florence-2 for accurate text recognition | |
| - **Multiple Input Methods**: Upload files, use webcam, or paste from clipboard | |
| - **Auto-Processing**: Text extraction starts automatically when you upload an image | |
| - **GPU Acceleration**: Automatically uses GPU if available for faster processing | |
| - **Copy Functionality**: Easy one-click copying of extracted text | |
| """, elem_classes=["instructions-section"]) | |
| # Event handlers | |
| image_input.upload( | |
| fn=extract_text_from_image, | |
| inputs=image_input, | |
| outputs=text_output | |
| ) | |
| extract_btn.click( | |
| fn=extract_text_from_image, | |
| inputs=image_input, | |
| outputs=text_output | |
| ) | |
| refresh_status_btn.click( | |
| fn=get_model_status, | |
| outputs=model_status | |
| ) | |
| return interface |