149 lines
4.0 KiB
Markdown
149 lines
4.0 KiB
Markdown
# Custom Annotation GUI
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A simple, **fully customizable** annotation tool built with Gradio (pure Python).
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## Features
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✅ **Auto-labeling** with your trained RF-DETR model
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✅ **Manual annotation** by entering box coordinates
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✅ **Edit/delete** annotations easily
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✅ **Navigation** between images
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✅ **Export** to COCO JSON format
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✅ **100% Python** - easy to modify and extend
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## Quick Start
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### 1. Install dependencies
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```bash
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/home/dillon/_code/saw_mill_knot_detection/.venv/bin/python -m pip install gradio>=4.0.0
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```
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### 2. Run the GUI
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**With auto-labeling (requires trained model):**
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```bash
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/home/dillon/_code/saw_mill_knot_detection/.venv/bin/python annotation_gui.py \
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--images-dir /path/to/images \
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--model-weights runs/knot_rfdetr_medium/checkpoint_best_total.pth
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```
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**Manual annotation only:**
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```bash
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/home/dillon/_code/saw_mill_knot_detection/.venv/bin/python annotation_gui.py \
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--images-dir /path/to/images
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```
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### 3. Open in browser
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Opens automatically at http://localhost:7860
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## Usage
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1. **Auto-Label**: Click "🤖 Auto-Label" to detect knots with your model
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2. **Adjust threshold**: Lower = more detections, Higher = only confident ones
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3. **Manual boxes**: Enter coordinates (x1, y1, x2, y2) and click "➕ Add Box"
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4. **Delete mistakes**: Click "🗑️ Delete Last" to remove last box
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5. **Navigate**: Use "Previous" / "Next" buttons
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6. **Export**: Click "💾 Export COCO" when done
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## Customization Examples
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### Add keyboard shortcuts
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```python
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# In create_ui(), add:
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image_display.keyboard_shortcuts = {
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"d": delete_btn.click, # Press 'd' to delete
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"n": next_btn.click, # Press 'n' for next
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}
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```
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### Add interactive drawing
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```python
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# Replace manual coordinates with image annotator:
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from gradio_image_annotation import image_annotator
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annotator = image_annotator(
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label="Draw boxes",
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type="numpy"
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)
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```
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### Change box colors by confidence
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```python
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# In draw_boxes_on_image():
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color = "green" if conf > 0.8 else "yellow" if conf > 0.5 else "red"
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draw.rectangle([x1, y1, x2, y2], outline=color, width=3)
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```
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### Add multiple label classes
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```python
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# Add a dropdown:
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label_choice = gr.Dropdown(
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choices=["knot", "crack", "hole"],
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value="knot",
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label="Label Type"
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)
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# Update box dict:
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box = {
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"bbox": [x1, y1, x2, y2],
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"label": label_choice_value, # from the dropdown
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"confidence": 1.0
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}
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```
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### Save checkpoints automatically
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```python
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# In _save_annotations(), add:
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import shutil
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backup_path = self.ann_file.with_suffix('.backup.json')
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shutil.copy(self.ann_file, backup_path)
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```
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### Add image filters/preprocessing
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```python
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# Add before annotation:
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def preprocess_image(img: Image.Image) -> Image.Image:
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from PIL import ImageEnhance
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enhancer = ImageEnhance.Contrast(img)
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return enhancer.enhance(1.5) # Increase contrast
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```
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## File Structure
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```
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annotation_gui.py
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├── AnnotationApp # Main logic (easy to extend)
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│ ├── auto_label_current() # Modify for different models
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│ ├── add_box_manual() # Customize annotation format
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│ ├── export_to_coco() # Change export format
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│ └── draw_boxes_on_image() # Customize visualization
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└── create_ui() # Gradio interface (add components)
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```
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## Advantages vs Label Studio
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| Feature | Custom GUI | Label Studio |
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|---------|-----------|--------------|
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| **Modify code** | ✅ Easy (pure Python) | ❌ Complex (React + Python) |
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| **Add features** | ✅ ~10-50 lines | ❌ Hundreds of lines |
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| **Custom models** | ✅ Direct integration | ⚠️ Need ONNX export |
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| **Learning curve** | ✅ Simple Gradio | ⚠️ Larger codebase |
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| **Setup** | ✅ pip install | ⚠️ Docker/complex |
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## Troubleshooting
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**Port already in use:**
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```bash
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python annotation_gui.py --images-dir /path --port 7861
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```
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**Model not loading:**
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- Check the weights path exists
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- Verify it's a valid checkpoint file
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- Try without `--model-weights` for manual-only mode
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**Need more features?**
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- Check Gradio docs: https://www.gradio.app/docs/
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- Add custom components easily
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- Fork and modify the code freely!
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