GIF Compressor 🎬

A high-quality GIF compression model for Replicate using gifsicle. Fast CPU-based compression with minimal quality loss.

Features

• Fast CPU compression - No GPU needed, runs quickly on any machine
• Smart defaults - Optimized for quality with level 3 optimization
• Lossless or lossy - Choose between perfect quality or smaller files
• Advanced options - Color reduction, resizing, and more
• Detailed logging - Progress bars and compression statistics
• Production-ready - Proper error handling and Cog integration

Basic Options

• optimization_level (1-3, default: 3)
• Level 1: Fast, basic optimization
• Level 2: Balanced optimization

• Level 3: Maximum optimization (recommended)

• lossy_compression (20-200, optional)

• Leave empty for lossless compression
• 80 = good balance of quality and size
• 50 = high quality, moderate compression
• 100-150 = lower quality, better compression
• Lower numbers = better quality

Advanced Options

• colors (2-256, optional)
• Reduce color palette to this many colors
• Useful for further size reduction

• 128 or 64 work well for most GIFs

• scale (0.1-1.0, optional)

• Scale the GIF by this factor

• 0.5 = half size, 0.75 = 75% size

• resize_width / resize_height (optional)

• Resize to specific dimensions in pixels
• Maintains aspect ratio

• Overrides scale option

• unoptimize (boolean, default: false)

• Unoptimize before compressing
• Useful for already-optimized GIFs that need reprocessing

Example Usage

Simple compression (lossless)

cog predict -i gif=@input.gif

Balanced quality and size

cog predict -i gif=@input.gif -i lossy_compression=80 -i colors=128

Maximum compression

cog predict -i gif=@input.gif \
  -i lossy_compression=150 \
  -i colors=64 \
  -i scale=0.75

Resize to specific width

cog predict -i gif=@input.gif \
  -i resize_width=500 \
  -i lossy_compression=80

Using with Python

import replicate

output = replicate.run(
    "unityaisolutions/gif-compressor",
    input={
        "gif": open("input.gif", "rb"),
        "optimization_level": 3,
        "lossy_compression": 80,
        "colors": 128
    }
)

# Save the compressed GIF
with open("output.gif", "wb") as f:
    f.write(output.read())

Output Logs

The model provides detailed logging including:

• Input/output file sizes
• Compression ratio and reduction percentage
• GIF dimensions, frames, and colors
• Processing status and progress

Example output:

============================================================
GIF COMPRESSION STARTING
============================================================

📊 Input file: animation.gif
📦 Input size: 2.45 MB
🎬 Frames: 60
📐 Dimensions: 500x500
🎨 Colors: 256

⚙️  Optimization level: 3
💥 Lossy compression: 80
🎨 Reducing to 128 colors

============================================================
PROCESSING...
============================================================

gifsicle: optimizing...

============================================================
COMPRESSION COMPLETE
============================================================

📦 Output size: 487.32 KB
💾 Size reduction: 80.1%
📉 Compression ratio: 5.03x
🎬 Output frames: 60
📐 Output dimensions: 500x500
🎨 Output colors: 128

✅ Success!
============================================================

Tips for Best Results

1. Start with defaults - The default settings work well for most GIFs
2. Use lossy_compression=80 - Great balance for most use cases
3. Reduce colors gradually - Try 128 first, then 64 if needed
4. Combine techniques - lossy + color reduction = best compression
5. Test different values - Every GIF is different!

Technical Details

• Engine: gifsicle (industry-standard GIF optimizer)
• Speed: Extremely fast on CPU (no GPU needed)
• Quality: Minimal perceptible quality loss with default settings
• Format: Input and output both GIF

License

This Cog model wrapper is open source. Gifsicle is GPL-licensed.