eval, readme

README.md

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 ---
 license: cc-by-nc-sa-4.0
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+
+**Restore missing RGB channels**
+
+Restore a missing channel of a RGB image by using ControlNet to guide image generation of Stable Diffusion to infer missing channel from the other two channels.
+* See accompanying discussion at [github.com - Channels RGB](https://github.com/lllyasviel/ControlNet/discussions/567) with detailed report and evaluations.
+* To restore images with missing channels you can use [this space](https://huggingface.co/spaces/GeroldMeisinger/channels).
+* For evaluation images see the corresponding .zip's at "files".
+* To run your own evaluations you can use [this script at gitlab.com](https://gitlab.com/-/snippets/3602096).
+
+# Training
+
+```  
+accelerate launch train_controlnet.py \
+  --pretrained_model_name_or_path="runwayml/stable-diffusion-v1-5" \
+  --train_batch_size=4 \
+  --gradient_accumulation_steps=8 \
+  --proportion_empty_prompts=0.5
+  --mixed_precision="fp16" \
+  --learning_rate=1e-5 \
+  --enable_xformers_memory_efficient_attention \
+  --use_8bit_adam \
+  --set_grads_to_none \
+  --seed=0 \
+  --num_train_epochs=2
+```
+
+# Image dataset
+
+* laion2B-en aesthetics>=6.5 dataset
+* --min_image_size 512 --max_aspect_ratio 2 --resize_mode="center_crop" --image_size 512
+* Cleaned with `fastdup` default settings
+* Data augmented with right-left flipped images
+* Resulting in 214244 images
+* Set whole channel to 0 by alternating between R-G-B channels
+

eval.zip

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