每日备份 2026-03-27

2026-03-27 23:38:45 +08:00
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+# Image Restoration
+
+Fix damaged, blurry, or degraded images with AI.
+
+## Face Restoration
+
+### GFPGAN
+
+```bash
+pip install gfpgan
+
+# CLI
+python inference_gfpgan.py -i inputs/ -o results/ -v 1.4 -s 2
+```
+
+```python
+from gfpgan import GFPGANer
+
+restorer = GFPGANer(
+    model_path="GFPGANv1.4.pth",
+    upscale=2,
+    arch="clean",
+    channel_multiplier=2
+)
+
+_, _, output = restorer.enhance(
+    input_img,
+    has_aligned=False,
+    only_center_face=False,
+    paste_back=True
+)
+```
+
+### CodeFormer
+
+```python
+from codeformer import CodeFormer
+
+model = CodeFormer()
+result = model.restore(
+    image,
+    fidelity=0.5  # 0=quality, 1=fidelity to original
+)
+```
+
+**Fidelity slider:**
+- Low (0.1-0.3) — more enhancement, may change face
+- High (0.7-0.9) — preserves original, less enhancement
+
+### Replicate
+
+```python
+import replicate
+
+output = replicate.run(
+    "tencentarc/gfpgan:9283608cc6b7be6b65a8e44983db012355fde4132009bf99d976b2f0896856a3",
+    input={"img": open("face.jpg", "rb"), "scale": 2}
+)
+```
+
+## Old Photo Restoration
+
+### Bringing Old Photos Back to Life
+
+```python
+import replicate
+
+output = replicate.run(
+    "microsoft/bringing-old-photos-back-to-life:c75db81db6cbd809d93b27b0f3e88a4c88aec3ed9be33b8c0f7f0c98d14f1d34",
+    input={
+        "image": open("old_photo.jpg", "rb"),
+        "with_scratch": True
+    }
+)
+```
+
+**Features:**
+- Scratch removal
+- Face restoration
+- Color enhancement
+
+## Denoising
+
+### Real-ESRGAN Denoise
+
+```python
+from realesrgan import RealESRGAN
+
+model = RealESRGAN(device, scale=1)  # scale=1 for denoise only
+model.load_weights("realesr-general-x4v3.pth")
+```
+
+### OpenCV Denoising
+
+```python
+import cv2
+
+# For color images
+denoised = cv2.fastNlMeansDenoisingColored(
+    image,
+    None,
+    h=10,           # Filter strength
+    hForColorComponents=10,
+    templateWindowSize=7,
+    searchWindowSize=21
+)
+```
+
+## Colorization
+
+### DeOldify
+
+```python
+from deoldify import device
+from deoldify.visualize import get_image_colorizer
+
+colorizer = get_image_colorizer(artistic=True)
+result = colorizer.get_transformed_image(
+    "bw_photo.jpg",
+    render_factor=35
+)
+```
+
+### Replicate
+
+```python
+output = replicate.run(
+    "arielreplicate/deoldify_image:0da600fab0c45a66211339f1c16b71345d22f26ef5fea3dca1bb90bb5711e950",
+    input={"input_image": open("bw.jpg", "rb")}
+)
+```
+
+## Restoration Pipeline
+
+1. **Remove scratches/damage** — Old Photos model
+2. **Denoise** — if grainy
+3. **Restore faces** — GFPGAN/CodeFormer
+4. **Colorize** — if B&W
+5. **Upscale** — to final resolution
+6. **Sharpen** — light enhancement
+
+## Quality Tips
+
+- **Preserve original** — always keep unedited copy
+- **Gradual enhancement** — don't over-process
+- **Check faces** — restoration can change features
+- **Manual touchup** — AI may miss spots
+- **Add grain** — restored images can look too clean