Eduardo Ottone
ee92581211
- Implements YOLOv8-based object detection with batch output - Supports multiple YOLOv8 model sizes (nano to extra-large) - Configurable confidence threshold, IoU threshold, and padding - Outputs separate images for each detected object - Includes installation scripts for Windows, Linux, and Mac - Complete documentation and example workflow - MIT license for open source distribution
44 lines
1.3 KiB
Bash
44 lines
1.3 KiB
Bash
#!/bin/bash
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# ComfyUI YOLOv8 Detection Node Installation Script
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echo "Installing ComfyUI YOLOv8 Detection Node..."
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# Check if pip is available
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if ! command -v pip &> /dev/null; then
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echo "Error: pip is not installed. Please install Python and pip first."
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exit 1
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fi
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# Install required packages
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echo "Installing required Python packages..."
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pip install -r requirements.txt
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# Check if ultralytics is properly installed
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python -c "import ultralytics; print('✓ ultralytics installed successfully')" 2>/dev/null || {
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echo "Error: Failed to install ultralytics. Trying alternative installation..."
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pip install ultralytics --upgrade
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}
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# Download default YOLOv8 model (optional)
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echo "Downloading default YOLOv8 nano model..."
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python -c "
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from ultralytics import YOLO
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try:
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model = YOLO('yolov8n.pt')
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print('✓ YOLOv8 nano model downloaded successfully')
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except Exception as e:
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print(f'Warning: Could not download model: {e}')
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print('Model will be downloaded automatically on first use')
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"
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echo ""
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echo "Installation completed!"
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echo ""
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echo "To use this node in ComfyUI:"
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echo "1. Copy this folder to your ComfyUI/custom_nodes/ directory"
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echo "2. Restart ComfyUI"
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echo "3. Look for 'YOLOv8 Object Detection' in the image/object_detection category"
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echo ""
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echo "For more information, see the README.md file."
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