# 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.

---

## 📦 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

---

## 🚀 GitHub Release Instructions

### Step 1: Prepare Repository

```bash
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

```bash
# 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

```bash
# 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

```bash
# 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"

---

## 📝 GitHub Release Description

```markdown
# 🎉 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](README.md) - Complete guide
- [CHANGELOG](CHANGELOG.md) - Full version history
- [Quick Start](QUICKSTART.md) - Getting started
- [Performance](PERFORMANCE.md) - 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](https://github.com/yyang181/colormnet) by Yixin Yang et al.
- [Deep Exemplar](https://github.com/zhangmozhe/Deep-Exemplar-based-Video-Colorization) by Bo Zhang et al.

---

**Full Changelog**: [v1.0.0...v2.0.0](https://github.com/jonstreeter/ComfyUI-Reference-Based-Video-Colorization/compare/v1.0.0...v2.0.0)
```

---

## 🎯 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

---

## 📋 Pre-Release Checklist

### Code
- [x] All nodes tested and working
- [x] Auto-download working for all models
- [x] Progress bars working
- [x] Performance reports generating correctly
- [x] No import errors
- [x] Example workflow loads correctly

### Documentation
- [x] README.md updated
- [x] CHANGELOG.md created
- [x] Version info in __init__.py
- [x] Release notes prepared
- [x] Workflow example included
- [x] 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

---

## 🎬 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

---

## 📊 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

---

## 🔮 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

---

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