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title: CanvasAI
emoji: 📚
colorFrom: red
colorTo: indigo
sdk: gradio
sdk_version: 6.22.0
python_version: '3.12'
app_file: app.py
pinned: false
short_description: AI Image Enhancer, Colourizer and Outpainter
startup_duration_timeout: 1h
---
# CanvasAI
Three AI image tools in one interface — upscale and sharpen any photo, colorize black and white images automatically, or extend a scene beyond its original borders.
---
## Tools
### ✨ Enhancement
Real-ESRGAN upscales images 2× or 4×, reconstructing fine detail rather than stretching pixels. Processes large images in tiles to stay within VRAM limits.
### 🎨 Colorization
DDColor adds natural color to black and white images without changing structure or composition. Post-processed with LAB color space smoothing to reduce color patchiness, and a saturation boost to compensate for DDColor's tendency to under-saturate. Fully automatic — no prompt needed.
### 🔲 Outpainting
Extends your image in any direction using Stable Diffusion 2 Inpainting. BLIP reads the image and generates an appropriate prompt automatically. Uses a multi-pass 64px incremental approach with feathered mask blending for coherent results.
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## How the Outpainting Works
The pipeline extends 64 pixels at a time rather than all at once. Each small pass gives SD 87%+ original image context — SD extrapolates naturally from what it can see. One large extension gives SD only 60-70% context, and the generated content becomes incoherent.
The mask uses GaussianBlur feathering so the boundary between original and generated content is a soft gradient rather than a hard cut. The mask is resized with LANCZOS (not NEAREST) to preserve this gradient when scaling to SD's 768×768 input size.
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## Honest Limitations
**Enhancement** does not deblur. It upscales and sharpens existing detail. Blurry input produces larger blurry output.
**Colorization** works well on portraits, street scenes, and landscapes. Complex fabric patterns and heavily degraded photographs may produce inconsistent colors. Results will not match commercial colorization tools.
**Outpainting** quality varies by input. Works best on simple consistent backgrounds at 25% extension or below. Struggles with complex foreground subjects near edges and high extension percentages. The multi-pass approach significantly improves over single-pass but does not eliminate the underlying model's limitations.
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## Tips for Best Results
- Enhancement: works on any image, best on photographs with existing sharp detail
- Colorization: portraits and outdoor scenes colorize most consistently
- Outpainting: use Horizontal or Vertical (not Both), keep extension at 25%, use the custom prompt field if BLIP misreads your image
---
## Models Used
| Model | Purpose |
|---|---|
| RealESRGAN_x4plus | Super resolution |
| stable-diffusion-2-inpainting | Scene extension |
| blip-image-captioning-base | Auto prompt generation |
| cv_ddcolor_image-colorization | B&W colorization |
---
## Privacy
Images are processed in memory and not stored permanently. Uploaded images are deleted when your session ends. Do not upload sensitive or private images.
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## GitHub
Full code, architecture notes, and documentation:
[github.com/Mohit485/CanvasAI](https://github.com/Mohit485/CanvasAI) |