Fabrice-TIERCELIN
commited on
Commit
•
bb54994
1
Parent(s):
11fe5b3
restore_in_9min
Browse files- gradio_demo.py +14 -32
gradio_demo.py
CHANGED
@@ -146,37 +146,18 @@ def stage2_process(
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model_select,
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output_format
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):
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return
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noisy_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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@spaces.GPU(duration=540)
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def restore(
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noisy_image,
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denoise_image,
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@@ -285,13 +266,14 @@ def restore(
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hours = math.floor(minutes / 60)
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minutes = minutes - (hours * 60)
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information = ("Start the process again if you want a different result. " if randomize_seed else "") + \
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"
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" pixels large and " + str(result_height) + \
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" pixels high, so a resolution of " + f'{result_width * result_height:,}' + " pixels. " + \
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"The image(s) has(ve) been generated in " + \
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((str(hours) + " h, ") if hours != 0 else "") + \
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((str(minutes) + " min, ") if hours != 0 or minutes != 0 else "") + \
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str(secondes) + " sec."
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print(information)
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# Only one image can be shown in the slider
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model_select,
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output_format
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):
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return restore_in_9min(
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noisy_image, denoise_image, prompt, a_prompt, n_prompt, num_samples, min_size, downscale, upscale, edm_steps, s_stage1, s_stage2, s_cfg, randomize_seed, seed, s_churn, s_noise, color_fix_type, diff_dtype, ae_dtype, gamma_correction, linear_CFG, linear_s_stage2, spt_linear_CFG, spt_linear_s_stage2, model_select, output_format
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)
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@spaces.GPU(duration=540)
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def restore_in_9min(
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noisy_image, denoise_image, prompt, a_prompt, n_prompt, num_samples, min_size, downscale, upscale, edm_steps, s_stage1, s_stage2, s_cfg, randomize_seed, seed, s_churn, s_noise, color_fix_type, diff_dtype, ae_dtype, gamma_correction, linear_CFG, linear_s_stage2, spt_linear_CFG, spt_linear_s_stage2, model_select, output_format
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):
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return restore(
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noisy_image, denoise_image, prompt, a_prompt, n_prompt, num_samples, min_size, downscale, upscale, edm_steps, s_stage1, s_stage2, s_cfg, randomize_seed, seed, s_churn, s_noise, color_fix_type, diff_dtype, ae_dtype, gamma_correction, linear_CFG, linear_s_stage2, spt_linear_CFG, spt_linear_s_stage2, model_select, output_format
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)
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def restore(
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noisy_image,
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denoise_image,
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hours = math.floor(minutes / 60)
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minutes = minutes - (hours * 60)
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information = ("Start the process again if you want a different result. " if randomize_seed else "") + \
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"Wait 9 min before a new run to avoid time penalty. " + \
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"The image(s) has(ve) been generated in " + \
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((str(hours) + " h, ") if hours != 0 else "") + \
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((str(minutes) + " min, ") if hours != 0 or minutes != 0 else "") + \
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str(secondes) + " sec. " + \
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"The new image resolution is " + str(result_width) + \
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" pixels large and " + str(result_height) + \
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" pixels high, so a resolution of " + f'{result_width * result_height:,}' + " pixels."
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print(information)
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# Only one image can be shown in the slider
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