OpenClaw Backup
149 lines
2.8 KiB
Markdown
149 lines
2.8 KiB
Markdown
# Image Restoration
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Fix damaged, blurry, or degraded images with AI.
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## Face Restoration
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### GFPGAN
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```bash
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pip install gfpgan
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# CLI
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python inference_gfpgan.py -i inputs/ -o results/ -v 1.4 -s 2
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```
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```python
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from gfpgan import GFPGANer
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restorer = GFPGANer(
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model_path="GFPGANv1.4.pth",
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upscale=2,
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arch="clean",
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channel_multiplier=2
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)
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_, _, output = restorer.enhance(
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input_img,
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has_aligned=False,
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only_center_face=False,
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paste_back=True
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)
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```
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### CodeFormer
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```python
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from codeformer import CodeFormer
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model = CodeFormer()
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result = model.restore(
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image,
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fidelity=0.5 # 0=quality, 1=fidelity to original
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)
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```
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**Fidelity slider:**
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- Low (0.1-0.3) — more enhancement, may change face
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- High (0.7-0.9) — preserves original, less enhancement
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### Replicate
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```python
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import replicate
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output = replicate.run(
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"tencentarc/gfpgan:9283608cc6b7be6b65a8e44983db012355fde4132009bf99d976b2f0896856a3",
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input={"img": open("face.jpg", "rb"), "scale": 2}
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)
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```
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## Old Photo Restoration
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### Bringing Old Photos Back to Life
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```python
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import replicate
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output = replicate.run(
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"microsoft/bringing-old-photos-back-to-life:c75db81db6cbd809d93b27b0f3e88a4c88aec3ed9be33b8c0f7f0c98d14f1d34",
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input={
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"image": open("old_photo.jpg", "rb"),
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"with_scratch": True
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}
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)
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```
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**Features:**
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- Scratch removal
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- Face restoration
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- Color enhancement
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## Denoising
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### Real-ESRGAN Denoise
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```python
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from realesrgan import RealESRGAN
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model = RealESRGAN(device, scale=1) # scale=1 for denoise only
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model.load_weights("realesr-general-x4v3.pth")
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```
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### OpenCV Denoising
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```python
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import cv2
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# For color images
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denoised = cv2.fastNlMeansDenoisingColored(
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image,
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None,
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h=10, # Filter strength
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hForColorComponents=10,
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templateWindowSize=7,
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searchWindowSize=21
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)
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```
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## Colorization
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### DeOldify
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```python
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from deoldify import device
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from deoldify.visualize import get_image_colorizer
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colorizer = get_image_colorizer(artistic=True)
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result = colorizer.get_transformed_image(
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"bw_photo.jpg",
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render_factor=35
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)
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```
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### Replicate
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```python
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output = replicate.run(
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"arielreplicate/deoldify_image:0da600fab0c45a66211339f1c16b71345d22f26ef5fea3dca1bb90bb5711e950",
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input={"input_image": open("bw.jpg", "rb")}
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)
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```
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## Restoration Pipeline
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1. **Remove scratches/damage** — Old Photos model
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2. **Denoise** — if grainy
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3. **Restore faces** — GFPGAN/CodeFormer
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4. **Colorize** — if B&W
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5. **Upscale** — to final resolution
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6. **Sharpen** — light enhancement
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## Quality Tips
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- **Preserve original** — always keep unedited copy
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- **Gradual enhancement** — don't over-process
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- **Check faces** — restoration can change features
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- **Manual touchup** — AI may miss spots
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- **Add grain** — restored images can look too clean
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