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add dynamic
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app.py
CHANGED
@@ -1,4 +1,5 @@
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import os
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import cv2
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import gradio as gr
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@@ -9,21 +10,33 @@ from imgutils.data import load_image
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from imgutils.restore import restore_with_nafnet, restore_with_scunet
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def
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input_image: Image.Image,
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img = np.array(input_image).astype(np.float32)
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y = img.copy()
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for _ in range(
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y = cv2.bilateralFilter(y, diameter, sigma_color, sigma_space)
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for _ in range(
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y = guidedFilter(img, y, radius, eps)
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output_image = Image.fromarray(y.clip(0, 255).astype(np.uint8))
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@@ -33,18 +46,33 @@ def clean_adverse(
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def clean(
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image: Image.Image,
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use_scunet_clean: bool = False,
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use_nafnet_clean: bool = False
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) -> Image.Image:
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image = load_image(image)
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image =
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if use_scunet_clean:
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image = restore_with_scunet(image)
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if use_nafnet_clean:
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@@ -59,51 +87,70 @@ if __name__ == '__main__':
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gr_input_image = gr.Image(label='Input Image', type="pil")
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gr_submit = gr.Button(value='MIST = MIST is Stupid Trash')
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with gr.Accordion("Advanced Config", open=False):
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)
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with gr.Accordion("Extra Restoration", open=False):
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with gr.Column():
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gr_output_image = gr.Image(label='Output Image', type="pil")
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@@ -113,11 +160,18 @@ if __name__ == '__main__':
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inputs=[
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gr_input_image,
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gr_scunet,
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gr_nafnet,
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import os
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import random
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import cv2
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import gradio as gr
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from imgutils.restore import restore_with_nafnet, restore_with_scunet
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def dynamic_clean_adverse(
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input_image: Image.Image,
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diameter_min: int = 4,
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diameter_max: int = 6,
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sigma_color_min: float = 6.0,
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sigma_color_max: float = 10.0,
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sigma_space_min: float = 6.0,
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sigma_space_max: float = 10.0,
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radius_min: int = 3,
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radius_max: int = 6,
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eps_min: float = 16.0,
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eps_max: float = 24.0,
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b_iters: int = 64,
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g_iters: int = 4,
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):
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img = np.array(input_image).astype(np.float32)
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y = img.copy()
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for _ in range(b_iters):
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diameter = random.randint(diameter_min, diameter_max)
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sigma_color = random.random() * (sigma_color_max - sigma_color_min) + sigma_color_min
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sigma_space = random.random() * (sigma_space_max - sigma_space_min) + sigma_space_min
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y = cv2.bilateralFilter(y, diameter, sigma_color, sigma_space)
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for _ in range(g_iters):
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radius = random.randint(radius_min, radius_max)
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eps = random.random() * (eps_max - eps_min) + eps_min
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y = guidedFilter(img, y, radius, eps)
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output_image = Image.fromarray(y.clip(0, 255).astype(np.uint8))
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def clean(
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image: Image.Image,
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diameter_min: int = 4,
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diameter_max: int = 6,
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sigma_color_min: float = 6.0,
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sigma_color_max: float = 10.0,
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sigma_space_min: float = 6.0,
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sigma_space_max: float = 10.0,
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radius_min: int = 3,
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radius_max: int = 6,
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eps_min: float = 16.0,
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eps_max: float = 24.0,
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b_iters: int = 64,
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g_iters: int = 4,
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use_scunet_clean: bool = False,
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use_nafnet_clean: bool = False
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) -> Image.Image:
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image = load_image(image)
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image = dynamic_clean_adverse(
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image,
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diameter_min, diameter_max,
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sigma_color_min, sigma_color_max,
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sigma_space_min, sigma_space_max,
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radius_min, radius_max,
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eps_min, eps_max,
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b_iters, g_iters
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)
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if use_scunet_clean:
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image = restore_with_scunet(image)
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if use_nafnet_clean:
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gr_input_image = gr.Image(label='Input Image', type="pil")
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gr_submit = gr.Button(value='MIST = MIST is Stupid Trash')
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with gr.Accordion("Advanced Config", open=False):
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with gr.Row():
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gr_diameter_min = gr.Slider(
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minimum=1, maximum=30, step=1, value=4,
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label="Diameter Min (default = 4)", interactive=True,
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)
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gr_diameter_max = gr.Slider(
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minimum=1, maximum=30, step=1, value=6,
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label="Diameter Max (default = 6)", interactive=True,
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)
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with gr.Row():
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gr_sigma_color_min = gr.Slider(
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minimum=1, maximum=30, step=1, value=6,
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label="SigmaColor Min (default = 6)", interactive=True,
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)
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gr_sigma_color_max = gr.Slider(
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minimum=1, maximum=30, step=1, value=10,
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label="SigmaColor Max (default = 10)", interactive=True,
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)
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with gr.Row():
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gr_sigma_space_min = gr.Slider(
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minimum=1, maximum=30, step=1, value=6,
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label="SigmaSpace Min (default = 6)", interactive=True,
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)
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gr_sigma_space_max = gr.Slider(
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minimum=1, maximum=30, step=1, value=10,
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label="SigmaSpace Max (default = 10)", interactive=True,
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)
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with gr.Row():
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gr_radius_min = gr.Slider(
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minimum=1, maximum=30, step=1, value=3,
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label="Radius Min (default = 3)", interactive=True,
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)
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gr_radius_max = gr.Slider(
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minimum=1, maximum=30, step=1, value=6,
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label="Radius Max (default = 6)", interactive=True,
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)
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with gr.Row():
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gr_eps_min = gr.Slider(
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minimum=1, maximum=30, step=1, value=16,
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label="Accuracy Min (default = 16)", interactive=True,
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)
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gr_eps_max = gr.Slider(
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minimum=1, maximum=30, step=1, value=24,
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label="Accuracy Max (default = 24)", interactive=True,
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)
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with gr.Row():
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gr_b_iters = gr.Slider(
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minimum=1, maximum=256, step=1, value=64,
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label="Bilateral Filter Iters (default = 64)", interactive=True,
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)
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gr_g_iters = gr.Slider(
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minimum=1, maximum=32, step=1, value=4,
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label="Guided Filter Iters (default = 4)", interactive=True,
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)
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with gr.Accordion("Extra Restoration", open=False):
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with gr.Row():
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gr_scunet = gr.Checkbox(label='Use SCUNET', value=False)
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gr_nafnet = gr.Checkbox(label='Use NAFNET', value=False)
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with gr.Column():
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gr_output_image = gr.Image(label='Output Image', type="pil")
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inputs=[
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gr_input_image,
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gr_diameter_min,
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gr_diameter_max,
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gr_sigma_color_min,
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gr_sigma_color_max,
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gr_sigma_space_min,
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gr_sigma_space_max,
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gr_radius_min,
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gr_radius_max,
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gr_eps_min,
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gr_eps_max,
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gr_b_iters,
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gr_g_iters,
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gr_scunet,
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gr_nafnet,
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