Fabrice-TIERCELIN commited on
Commit
ba43c72
1 Parent(s): 3dd58cf

10 min (may fail)

Browse files
Files changed (1) hide show
  1. gradio_demo.py +27 -55
gradio_demo.py CHANGED
@@ -179,82 +179,54 @@ def stage2_process(
179
  return restore_in_9min(
180
  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, allocation
181
  )
 
 
 
 
182
  else:
183
  return restore_in_6min(
184
  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, allocation
185
  )
186
 
187
  @spaces.GPU(duration=60)
188
- def restore_in_1min(
189
- 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, allocation
190
- ):
191
- return restore(
192
- 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, allocation
193
- )
194
 
195
  @spaces.GPU(duration=120)
196
- def restore_in_2min(
197
- 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, allocation
198
- ):
199
- return restore(
200
- 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, allocation
201
- )
202
 
203
  @spaces.GPU(duration=180)
204
- def restore_in_3min(
205
- 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, allocation
206
- ):
207
- return restore(
208
- 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, allocation
209
- )
210
 
211
  @spaces.GPU(duration=240)
212
- def restore_in_4min(
213
- 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, allocation
214
- ):
215
- return restore(
216
- 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, allocation
217
- )
218
 
219
  @spaces.GPU(duration=300)
220
- def restore_in_5min(
221
- 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, allocation
222
- ):
223
- return restore(
224
- 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, allocation
225
- )
226
 
227
  @spaces.GPU(duration=360)
228
- def restore_in_6min(
229
- 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, allocation
230
- ):
231
- return restore(
232
- 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, allocation
233
- )
234
 
235
  @spaces.GPU(duration=420)
236
- def restore_in_7min(
237
- 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, allocation
238
- ):
239
- return restore(
240
- 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, allocation
241
- )
242
 
243
  @spaces.GPU(duration=480)
244
- def restore_in_8min(
245
- *args, **kwargs
246
- ):
247
- return restore(
248
- *args, **kwargs
249
- )
250
 
251
  @spaces.GPU(duration=540)
252
- def restore_in_9min(
253
- 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, allocation
254
- ):
255
- return restore(
256
- 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, allocation
257
- )
258
 
259
  def restore(
260
  noisy_image,
@@ -527,7 +499,7 @@ with gr.Blocks(title="SUPIR") as interface:
527
  prompt = gr.Textbox(label="Image description", info="Help the AI understand what the image represents; describe as much as possible; I advise you to write in English as other languages may not be handled", value="", placeholder="A person, walking, in a town, Summer, photorealistic", lines=3)
528
  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.")
529
  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)
530
- allocation = gr.Radio([["1 min", 1], ["2 min", 2], ["3 min", 3], ["4 min", 4], ["5 min", 5], ["6 min", 6], ["7 min", 7], ["8 min", 8], ["9 min", 9]], label="GPU allocation time", info="lower=May abort run, higher=Time penalty for next runs", value=6, interactive=True)
531
  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)
532
 
533
  with gr.Accordion("Pre-denoising (optional)", open=False):
 
179
  return restore_in_9min(
180
  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, allocation
181
  )
182
+ if allocation == 10:
183
+ return restore_in_10min(
184
+ 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, allocation
185
+ )
186
  else:
187
  return restore_in_6min(
188
  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, allocation
189
  )
190
 
191
  @spaces.GPU(duration=60)
192
+ def restore_in_1min(*args, **kwargs):
193
+ return restore(*args, **kwargs)
 
 
 
 
194
 
195
  @spaces.GPU(duration=120)
196
+ def restore_in_2min(*args, **kwargs):
197
+ return restore(*args, **kwargs)
 
 
 
 
198
 
199
  @spaces.GPU(duration=180)
200
+ def restore_in_3min(*args, **kwargs):
201
+ return restore(*args, **kwargs)
 
 
 
 
202
 
203
  @spaces.GPU(duration=240)
204
+ def restore_in_4min(*args, **kwargs):
205
+ return restore(*args, **kwargs)
 
 
 
 
206
 
207
  @spaces.GPU(duration=300)
208
+ def restore_in_5min(*args, **kwargs):
209
+ return restore(*args, **kwargs)
 
 
 
 
210
 
211
  @spaces.GPU(duration=360)
212
+ def restore_in_6min(*args, **kwargs):
213
+ return restore(*args, **kwargs)
 
 
 
 
214
 
215
  @spaces.GPU(duration=420)
216
+ def restore_in_7min(*args, **kwargs):
217
+ return restore(*args, **kwargs)
 
 
 
 
218
 
219
  @spaces.GPU(duration=480)
220
+ def restore_in_8min(*args, **kwargs):
221
+ return restore(*args, **kwargs)
 
 
 
 
222
 
223
  @spaces.GPU(duration=540)
224
+ def restore_in_9min(*args, **kwargs):
225
+ return restore(*args, **kwargs)
226
+
227
+ @spaces.GPU(duration=599)
228
+ def restore_in_10min(*args, **kwargs):
229
+ return restore(*args, **kwargs)
230
 
231
  def restore(
232
  noisy_image,
 
499
  prompt = gr.Textbox(label="Image description", info="Help the AI understand what the image represents; describe as much as possible; I advise you to write in English as other languages may not be handled", value="", placeholder="A person, walking, in a town, Summer, photorealistic", lines=3)
500
  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.")
501
  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)
502
+ allocation = gr.Radio([["1 min", 1], ["2 min", 2], ["3 min", 3], ["4 min", 4], ["5 min", 5], ["6 min", 6], ["7 min", 7], ["8 min", 8], ["9 min", 9], ["10 min (may fail)", 10]], label="GPU allocation time", info="lower=May abort run, higher=Time penalty for next runs", value=6, interactive=True)
503
  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)
504
 
505
  with gr.Accordion("Pre-denoising (optional)", open=False):