init

.gitignore

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+venv
+flagged
+

README.md

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 ---
-title: Channels
+title: Restore RGB Channels
 emoji: 🐠
-colorFrom: red
-colorTo: green
+colorFrom: indigo
+colorTo: yellow
 sdk: gradio
-sdk_version: 3.50.2
+sdk_version: 3.44.4
 app_file: app.py
 pinned: false
 license: agpl-3.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+

app.py

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+import gradio as gr
+import cv2
+import os
+
+def restore(image_missing, image_inference, channel):
+    if len(image_missing.shape) != 3 or len(image_inference.shape) != 3:
+        return None #[None, "Error: Please provide RGB images!"]
+    c = { "R": 0, "G": 1, "B": 2 }[channel] # cv2 uses BGR order
+    image_missing[:,:,c] = image_inference[:,:,c]
+    return image_missing
+
+examples=[
+        [os.path.join(os.path.dirname(__file__), "missing/bird_r.webp"  ), os.path.join(os.path.dirname(__file__), "inference/bird_r.webp"  ), "R"],
+        [os.path.join(os.path.dirname(__file__), "missing/bird_g.webp"  ), os.path.join(os.path.dirname(__file__), "inference/bird_g.webp"  ), "G"],
+        [os.path.join(os.path.dirname(__file__), "missing/bird_b.webp"  ), os.path.join(os.path.dirname(__file__), "inference/bird_b.webp"  ), "B"],
+        [os.path.join(os.path.dirname(__file__), "missing/dog2_r.webp"  ), os.path.join(os.path.dirname(__file__), "inference/dog2_r.webp"  ), "R"],
+        [os.path.join(os.path.dirname(__file__), "missing/dog2_g.webp"  ), os.path.join(os.path.dirname(__file__), "inference/dog2_g.webp"  ), "G"],
+        [os.path.join(os.path.dirname(__file__), "missing/dog2_b.webp"  ), os.path.join(os.path.dirname(__file__), "inference/dog2_b.webp"  ), "B"],
+        [os.path.join(os.path.dirname(__file__), "missing/house2_r.webp"), os.path.join(os.path.dirname(__file__), "inference/house2_r.webp"), "R"],
+        [os.path.join(os.path.dirname(__file__), "missing/house2_g.webp"), os.path.join(os.path.dirname(__file__), "inference/house2_g.webp"), "G"],
+        [os.path.join(os.path.dirname(__file__), "missing/house2_b.webp"), os.path.join(os.path.dirname(__file__), "inference/house2_b.webp"), "B"],
+    ]
+
+app = gr.Interface(
+    fn=restore,
+    inputs=[
+            gr.Image("missing/dog2_r.webp", type="numpy", label="Missing channel"), 
+            gr.Image("inference/dog2_r.webp", type="numpy", label="Inference"), 
+            gr.Radio(["R", "G", "B"], label="Restore channel"),
+        ],    
+    outputs="image",
+    examples=examples,
+    title="Restore missing RGB channel",
+    description="Restore missing channel of a RGB image by using a ControlNet to guide image generation of Stable Diffusion to infer missing channel from the other two channels https://huggingface.co/GeroldMeisinger/control-channels . Examples are missing one channel each (use `decompose.py`) and inference examples are cherry-picked from generation with ControlNet. The submit button replaces the missing channel from the inference. To generate your own inferences you have to set up Stable Diffusion with ControlNet 'channels-rgb'. Note: While the inference images look fine on their own and you might as well use them, we are only interested in one of their channels.")
+
+if __name__ == "__main__":
+    app.launch()
+

decompose.py

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+import numpy as np
+import cv2
+
+for basename in ["bird", "dog2", "house2"]:
+    img = cv2.imread(f"{basename}.png")
+    for c, suffix in enumerate(["b", "g", "r"]):
+        img_c = img.copy()
+        img_c[:,:,c] = 0        
+        cv2.imwrite(f"missing/{basename}_{suffix}.webp", img_c, [cv2.IMWRITE_WEBP_QUALITY, 100])
+

packages.txt

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+python3-opencv

requirements.txt

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+gradio==3.44.4
+opencv-contrib-python==4.8.0.76