Fabrice-TIERCELIN
commited on
Commit
•
478d0c1
1
Parent(s):
706e01a
Update gradio_demo.py
Browse files- gradio_demo.py +103 -2
gradio_demo.py
CHANGED
@@ -327,7 +327,6 @@ with gr.Blocks(title="SUPIR") as interface:
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input_image = gr.Image(label="Input", show_label=True, type="numpy", height=600, elem_id="image-input")
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with gr.Group():
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prompt = gr.Textbox(label="Image description for LlaVa", value="", placeholder="A person, walking, in a town, Summer, photorealistic", lines=3, visible=False)
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-
upscale = gr.Radio([["x1", 1], ["x2", 2], ["x3", 3], ["x4", 4], ["x5", 5], ["x6", 6], ["x7", 7], ["x8", 8]], label="Upscale factor", info="Resolution x1 to x8", value=2, interactive=True)
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a_prompt = gr.Textbox(label="Image description",
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info="Help the AI understand what the image represents; describe as much as possible",
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value='Cinematic, High Contrast, highly detailed, taken using a Canon EOS R '
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@@ -336,6 +335,7 @@ with gr.Blocks(title="SUPIR") as interface:
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'hyper sharpness, perfect without deformations.',
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lines=3)
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a_prompt_hint = gr.HTML("You can use a <a href='"'https://huggingface.co/spaces/MaziyarPanahi/llava-llama-3-8b'"'>LlaVa space</a> to auto-generate the description of your image.")
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output_format = gr.Radio([["*.png", "png"], ["*.webp", "webp"], ["*.jpeg", "jpeg"], ["*.gif", "gif"], ["*.bmp", "bmp"]], label="Image format for result", info="File extention", value="png", interactive=True)
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with gr.Accordion("Pre-denoising (optional)", open=False):
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@@ -409,9 +409,110 @@ with gr.Blocks(title="SUPIR") as interface:
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fb_score = gr.Slider(label="Feedback Score", minimum=1, maximum=5, value=3, step=1, interactive=True)
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fb_text = gr.Textbox(label="Feedback Text", value="", placeholder='Please enter your feedback here.')
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submit_button = gr.Button(value="Submit Feedback")
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with gr.Row():
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gr.Markdown(claim_md)
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-
event_id = gr.Textbox(label="Event ID", value="", visible=False)
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denoise_button.click(fn = check, inputs = [
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input_image
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input_image = gr.Image(label="Input", show_label=True, type="numpy", height=600, elem_id="image-input")
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with gr.Group():
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prompt = gr.Textbox(label="Image description for LlaVa", value="", placeholder="A person, walking, in a town, Summer, photorealistic", lines=3, visible=False)
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a_prompt = gr.Textbox(label="Image description",
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info="Help the AI understand what the image represents; describe as much as possible",
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value='Cinematic, High Contrast, highly detailed, taken using a Canon EOS R '
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'hyper sharpness, perfect without deformations.',
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lines=3)
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a_prompt_hint = gr.HTML("You can use a <a href='"'https://huggingface.co/spaces/MaziyarPanahi/llava-llama-3-8b'"'>LlaVa space</a> to auto-generate the description of your image.")
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+
upscale = gr.Radio([["x1", 1], ["x2", 2], ["x3", 3], ["x4", 4], ["x5", 5], ["x6", 6], ["x7", 7], ["x8", 8]], label="Upscale factor", info="Resolution x1 to x8", value=2, interactive=True)
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output_format = gr.Radio([["*.png", "png"], ["*.webp", "webp"], ["*.jpeg", "jpeg"], ["*.gif", "gif"], ["*.bmp", "bmp"]], label="Image format for result", info="File extention", value="png", interactive=True)
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with gr.Accordion("Pre-denoising (optional)", open=False):
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fb_score = gr.Slider(label="Feedback Score", minimum=1, maximum=5, value=3, step=1, interactive=True)
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fb_text = gr.Textbox(label="Feedback Text", value="", placeholder='Please enter your feedback here.')
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submit_button = gr.Button(value="Submit Feedback")
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event_id = gr.Textbox(label="Event ID", value="", visible=False)
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+
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gr.Examples(
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fn = stage2_process,
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inputs = [
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input_image,
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denoise_image,
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prompt,
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a_prompt,
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n_prompt,
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num_samples,
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min_size,
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downscale,
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upscale,
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edm_steps,
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s_stage1,
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s_stage2,
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s_cfg,
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randomize_seed,
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seed,
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s_churn,
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s_noise,
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color_fix_type,
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diff_dtype,
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ae_dtype,
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gamma_correction,
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linear_CFG,
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linear_s_stage2,
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spt_linear_CFG,
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spt_linear_s_stage2,
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model_select,
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output_format
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],
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outputs = [
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result_slider,
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result_gallery,
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restore_information,
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event_id
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],
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examples = [
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[
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"./Examples/Example1.png",
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None,
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None,
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"Group of people, walking, happy, in the street, photorealistic, 8k, extremely detailled, Cinematic, High Contrast, highly detailed, taken using a Canon EOS R camera, hyper detailed photo - realistic maximum detail, 32k, Color Grading, ultra HD, extreme meticulous detailing, skin pore detailing, hyper sharpness, perfect without deformations.",
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"painting, oil painting, illustration, drawing, art, sketch, anime, cartoon, CG Style, 3D render, unreal engine, blurring, bokeh, ugly, dirty, messy, worst quality, low quality, frames, watermark, signature, jpeg artifacts, deformed, lowres, over-smooth",
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1,
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1024,
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1,
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1,
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200,
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-1,
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1,
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7.5,
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False,
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42,
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5,
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1.003,
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"Wavelet",
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"fp16",
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"bf16",
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1.0,
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True,
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4,
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False,
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0.,
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"v0-Q",
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"png"
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],
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[
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"./Examples/Example2.jpeg",
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None,
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None,
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"The head of a tabby cat, in a house, photorealistic, 8k, extremely detailled, Cinematic, High Contrast, highly detailed, taken using a Canon EOS R camera, hyper detailed photo - realistic maximum detail, 32k, Color Grading, ultra HD, extreme meticulous detailing, skin pore detailing, hyper sharpness, perfect without deformations.",
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"painting, oil painting, illustration, drawing, art, sketch, anime, cartoon, CG Style, 3D render, unreal engine, blurring, bokeh, ugly, dirty, messy, worst quality, low quality, frames, watermark, signature, jpeg artifacts, deformed, lowres, over-smooth",
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1,
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1024,
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1,
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1,
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200,
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-1,
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1,
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7.5,
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False,
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42,
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5,
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1.003,
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"Wavelet",
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"fp16",
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"bf16",
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1.0,
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True,
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4,
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False,
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0.,
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"v0-Q",
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"png"
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],
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],
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cache_examples = False,
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)
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with gr.Row():
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gr.Markdown(claim_md)
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denoise_button.click(fn = check, inputs = [
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input_image
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