jonstreeter-ComfyUI-Reference-Based-Video-Colorization/RELEASE_NOTES_v2.0.0.md

Release Notes v2.0.0 - Dual Implementation Release

🎉 Major Release Summary

This is a major version release that transforms the project into a dual-implementation package featuring both modern and classic exemplar-based colorization methods.

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📦 What's Included

New Implementations

1. ColorMNet (2024) - Modern DINOv2-based approach

   • 2 new nodes: Video + Image colorization
   • Memory-based temporal propagation
   • FP16 support
   • Multiple memory modes

2. Deep Exemplar (Enhanced) - Original CVPR 2019 method

   • Enhanced with auto-download
   • Fixed bugs and import issues
   • Added performance reports
   • Improved progress tracking

Key Features

• ✅ 4 total nodes: 2 ColorMNet + 2 Deep Exemplar
• ✅ Auto-download: All models download automatically (~700MB)
• ✅ Progress bars: Real-time feedback in ComfyUI
• ✅ Performance reports: Compare speed/quality between methods
• ✅ Example workflow: Side-by-side comparison included

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🚀 GitHub Release Instructions

Step 1: Prepare Repository

cd ComfyUI/custom_nodes/ComfyUI-Reference-Based-Video-Colorization

# Remove backup files (not needed in repo)
rm -f *_old_backup.py *_new.py requirements_*_backup.txt

# Add all important files
git add .
git add colormnet/
git add core/
git add nodes.py
git add workflows/
git add CHANGELOG.md
git add README.md
git add __init__.py

# Add other essential files
git add DeepExemplarColorizationNodes.py
git add models/
git add requirements.txt

# Check what will be committed
git status

Step 2: Create Commit

# Create comprehensive commit
git commit -m "Release v2.0.0: Dual implementation with ColorMNet + Deep Exemplar

Major Features:
- Add ColorMNet implementation (DINOv2-based, 2024)
- Enhanced Deep Exemplar with auto-download
- Performance reports for all 4 nodes
- Real-time progress bars in ComfyUI
- Automatic model downloading (~700MB total)
- Example workflow with both methods

Bug Fixes:
- Fix ColorMNet greyscale output
- Fix color saturation issues
- Fix progress bar updates
- Fix import path issues
- Fix VGG model loading
- Fix Deep Exemplar checkpoint extraction

Documentation:
- Complete README rewrite
- Add CHANGELOG.md
- Add version info to __init__.py
- Add example workflow

Technical:
- Proper LAB color space normalization
- Lazy VGG model loading
- Relative imports throughout
- Auto-download for all models"

Step 3: Tag Release

# Create annotated tag
git tag -a v2.0.0 -m "Version 2.0.0 - Dual Implementation Release

This release includes:
- ColorMNet (2024) implementation
- Enhanced Deep Exemplar (2019)
- 4 total colorization nodes
- Automatic model downloads
- Performance benchmarking
- Complete documentation

Breaking changes:
- Node display names changed (IDs unchanged)
- New performance_report output (optional)

See CHANGELOG.md for full details."

Step 4: Push to GitHub

# Push commits and tags
git push origin main
git push origin v2.0.0

# Or push all tags
git push origin main --tags

Step 5: Create GitHub Release

1. Go to: https://github.com/jonstreeter/ComfyUI-Reference-Based-Video-Colorization/releases
2. Click "Draft a new release"
3. Select tag: v2.0.0
4. Release title: v2.0.0 - Dual Implementation: ColorMNet + Deep Exemplar
5. Description: Use content from section below
6. Attach workflow image: workflows/ColorizeVideoWorkflow.png
7. Click "Publish release"

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📝 GitHub Release Description

# 🎉 v2.0.0 - Dual Implementation Release

Transform your black & white videos with **two powerful colorization methods** in one package!

## What's New

### 🎨 ColorMNet (2024) - NEW!
Modern memory-based approach featuring:
- DINOv2 feature extraction
- Temporal consistency through memory propagation
- Multiple memory modes (balanced/low/high quality)
- FP16 mixed precision support
- ~5.3 FPS at 768x432

### 🎬 Deep Exemplar (2019) - Enhanced
Classic CVPR method with improvements:
- Automatic model downloading
- Fixed bugs and import issues
- Enhanced progress tracking
- WLS filtering for smoothing
- ~4.6 FPS at 768x432

## ✨ Features

✅ **4 Colorization Nodes** - 2 video + 2 image nodes
✅ **Auto-Download** - All models download automatically (~700MB)
✅ **Progress Bars** - Real-time feedback in ComfyUI
✅ **Performance Reports** - Timing and FPS metrics
✅ **Example Workflow** - Compare both methods side-by-side

## 📦 Installation

### Via ComfyUI Manager (Recommended)
1. Open ComfyUI → Manager → Install Custom Nodes
2. Search "Deep Exemplar Video Colorization"
3. Click Install → Restart

### Manual Installation
```bash
cd ComfyUI/custom_nodes/
git clone https://github.com/jonstreeter/ComfyUI-Reference-Based-Video-Colorization.git
cd ComfyUI-Reference-Based-Video-Colorization/
pip install -r requirements.txt

Models download automatically on first use!

🚀 Quick Start

1. Load the example workflow: workflows/Colorize Video Workflow.json
2. Load your grayscale video
3. Load a color reference image
4. Try both ColorMNet and Deep Exemplar
5. Compare performance reports!

📊 Performance

Example benchmark (768x432, 240 frames, RTX 5090):

• ColorMNet (balanced, FP16): 45.2s, 5.31 FPS
• Deep Exemplar (half-res, propagation): 52.3s, 4.59 FPS

🔧 What's Fixed

• ✅ ColorMNet greyscale output → proper RGB reference
• ✅ Color oversaturation → correct LAB normalization
• ✅ Missing progress bars → added UI updates
• ✅ Import errors → fixed relative imports
• ✅ VGG loading → lazy initialization
• ✅ Missing models → auto-download

📚 Documentation

• README - Complete guide
• CHANGELOG - Full version history
• Quick Start - Getting started
• Performance - Optimization guide

⚠️ Breaking Changes

• Node display names changed (internal IDs unchanged)
• New optional performance_report output
• Model paths changed (handled by auto-download)

Existing workflows will work - just reconnect to see new names!

🙏 Acknowledgments

Based on:

• ColorMNet by Yixin Yang et al.
• Deep Exemplar by Bo Zhang et al.

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Full Changelog: v1.0.0...v2.0.0

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## 🎯 ComfyUI Manager Update

### Update Custom Node List

The ComfyUI Manager pulls from: `https://github.com/ltdrdata/ComfyUI-Manager/blob/main/custom-node-list.json`

#### Option 1: Create Pull Request

1. Fork `https://github.com/ltdrdata/ComfyUI-Manager`
2. Edit `custom-node-list.json`
3. Find your node entry or add new one:

```json
{
    "author": "Jon Streeter",
    "title": "ComfyUI Reference-Based Video Colorization",
    "reference": "https://github.com/jonstreeter/ComfyUI-Reference-Based-Video-Colorization",
    "files": [
        "https://github.com/jonstreeter/ComfyUI-Reference-Based-Video-Colorization"
    ],
    "install_type": "git-clone",
    "description": "Dual implementation of reference-based video colorization: ColorMNet (2024) with DINOv2 features + Deep Exemplar (2019) CVPR method. Features 4 nodes (2 video, 2 image), auto-download models, progress bars, and performance reports. Transform B&W videos using color reference images!",
    "nodename_pattern": "(ColorMNet|DeepExemplar)",
    "pip": ["einops", "progressbar2", "gdown", "opencv-contrib-python"]
}

4. Create PR with title: "Update Deep Exemplar Video Colorization to v2.0.0"
5. Description: "Major update with dual implementation (ColorMNet + Deep Exemplar)"

Option 2: Open Issue

If PR is too complex, open an issue requesting update:

• Repository: ltdrdata/ComfyUI-Manager
• Title: "Update Deep Exemplar Video Colorization node"
• Body: Provide updated JSON entry and changelog link

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📋 Pre-Release Checklist

Code

• All nodes tested and working
• Auto-download working for all models
• Progress bars working
• Performance reports generating correctly
• No import errors
• Example workflow loads correctly

Documentation

• README.md updated
• CHANGELOG.md created
• Version info in __init__.py
• Release notes prepared
• Workflow example included
• Workflow image captured

Git

• All changes committed
• Version tagged (v2.0.0)
• Pushed to GitHub
• GitHub release created
• Release assets uploaded

Distribution

• ComfyUI Manager PR submitted
• Installation tested via Manager
• Manual installation tested
• Models auto-download verified

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🎬 Post-Release

Announce Release

ComfyUI Discord:

🎉 ComfyUI Deep Exemplar v2.0 Released!

Now featuring TWO colorization methods:
• ColorMNet (2024) - Modern DINOv2-based
• Deep Exemplar (2019) - Classic CVPR method

✨ New Features:
- Auto-download all models (~700MB)
- Real-time progress bars
- Performance benchmarking
- 4 total nodes (2 video, 2 image)

Try both methods and compare! Example workflow included.

📦 Install via ComfyUI Manager or:
https://github.com/jonstreeter/ComfyUI-Reference-Based-Video-Colorization

Feedback welcome! 🙏

Reddit r/StableDiffusion or r/ComfyUI: Title: "ComfyUI Reference-Based Video Colorization v2.0 - Dual Implementation"

• Include workflow screenshot
• Link to repo
• Highlight key features

Monitor

• Watch for issues on GitHub
• Monitor Discord for questions
• Check Manager installation reports
• Gather performance feedback

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📊 Success Metrics

Track after release:

• GitHub stars/forks
• Installation count (if available from Manager)
• Issue reports (bugs vs features)
• Community feedback
• Performance comparisons from users

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🔮 Future Roadmap

Add to GitHub issues for community input:

• Batch processing optimization
• Streaming mode for long videos
• Additional colorization methods
• Color palette tools
• Real-time preview

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Questions? Open an issue on GitHub or ask in ComfyUI Discord!