init commit

.gitignore

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+/venv
+__pycache__
+/test_*
+/.idea

main.py

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+import os
+
+import cv2
+import gradio as gr
+import numpy as np
+from PIL import Image
+from cv2.ximgproc import guidedFilter
+from imgutils.data import load_image
+from imgutils.restore import restore_with_nafnet, restore_with_scunet
+
+
+def clean_adverse(
+        input_image: Image.Image,
+        diameter: float = 5,
+        sigma_color: float = 8,
+        sigma_space: float = 8,
+        radius: float = 4,
+        eps: float = 16,
+) -> Image.Image:
+    img = np.array(input_image).astype(np.float32)
+    y = img.copy()
+
+    for _ in range(64):
+        y = cv2.bilateralFilter(y, diameter, sigma_color, sigma_space)
+
+    for _ in range(4):
+        y = guidedFilter(img, y, radius, eps)
+
+    output_image = Image.fromarray(y.clip(0, 255).astype(np.uint8))
+    return output_image
+
+
+def clean(
+        image: Image.Image,
+        use_adverse_clean: bool = True,
+        use_scunet_clean: bool = True,
+        use_nafnet_clean: bool = False
+) -> Image.Image:
+    image = load_image(image)
+    if use_adverse_clean:
+        image = clean_adverse(image)
+    if use_scunet_clean:
+        image = restore_with_scunet(image)
+    if use_nafnet_clean:
+        image = restore_with_nafnet(image)
+    return image
+
+
+if __name__ == '__main__':
+    with gr.Blocks() as demo:
+        with gr.Row():
+            with gr.Column():
+                gr_input_image = gr.Image(label='Input Image', type="pil")
+                gr_submit = gr.Button(value='FUCK YOU MIST!')
+                gr_adverse = gr.Checkbox(label='Use Adverse Clean', value=True)
+                gr_scunet = gr.Checkbox(label='Use SCUNET', value=True)
+                gr_nafnet = gr.Checkbox(label='Use NafNET', value=False)
+
+            with gr.Column():
+                gr_output_image = gr.Image(label='Output Image', type="pil")
+
+            gr_submit.click(
+                fn=clean,
+                inputs=[gr_input_image, gr_adverse, gr_scunet, gr_nafnet],
+                outputs=[gr_output_image],
+            )
+
+    demo.queue(os.cpu_count()).launch()

requirements.txt

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+gradio==4.10.0
+pillow
+dghs-imgutils
+numpy
+opencv-python
+opencv-contrib-python