Fabrice-TIERCELIN commited on
Commit
4fe413f
1 Parent(s): 320e40a

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Browse files
Files changed (1) hide show
  1. gradio_demo.py +34 -20
gradio_demo.py CHANGED
@@ -129,6 +129,7 @@ def stage2_process(
129
  s_stage1,
130
  s_stage2,
131
  s_cfg,
 
132
  seed,
133
  s_churn,
134
  s_noise,
@@ -142,6 +143,7 @@ def stage2_process(
142
  spt_linear_s_stage2,
143
  model_select
144
  ):
 
145
  print('Start stage2_process')
146
  if torch.cuda.device_count() == 0:
147
  gr.Warning('Set this space to GPU config to make it work.')
@@ -200,8 +202,17 @@ def stage2_process(
200
  Image.fromarray(input_image).save(f'./history/{event_id[:5]}/{event_id[5:]}/LQ.png')
201
  for i, result in enumerate(results):
202
  Image.fromarray(result).save(f'./history/{event_id[:5]}/{event_id[5:]}/HQ_{i}.png')
 
203
  print('End stage2_process')
204
- return [input_image] + results, [input_image] + results, gr.update(visible = True), event_id
 
 
 
 
 
 
 
 
205
 
206
  def load_and_reset(param_setting):
207
  print('Start load_and_reset')
@@ -285,17 +296,18 @@ with gr.Blocks(title="SUPIR") as interface:
285
  """)
286
  gr.HTML(title_html)
287
 
288
- input_image = gr.Image(label="Input", show_label=True, type="numpy", height=600, elem_id="image-input")
289
- prompt = gr.Textbox(label="Image description for LlaVa", value="", placeholder="A person, walking, in a town, Summer, photorealistic", lines=3, visible=False)
290
- upscale = gr.Radio([1, 2, 3, 4, 5, 6, 7, 8], label="Upscale factor", info="Resolution x1 to x8", value=2, interactive=True)
291
- a_prompt = gr.Textbox(label="Image description",
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- info="The prompt that describes what the image represents",
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- value='Cinematic, High Contrast, highly detailed, taken using a Canon EOS R '
294
- 'camera, hyper detailed photo - realistic maximum detail, 32k, Color '
295
- 'Grading, ultra HD, extreme meticulous detailing, skin pore detailing, '
296
- 'hyper sharpness, perfect without deformations.',
297
- lines=3)
298
- 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.")
 
299
 
300
  with gr.Accordion("Pre-denoising (optional)", open=False):
301
  gamma_correction = gr.Slider(label="Gamma Correction", minimum=0.1, maximum=2.0, value=1.0, step=0.1)
@@ -352,17 +364,18 @@ with gr.Blocks(title="SUPIR") as interface:
352
  with gr.Group():
353
  param_setting = gr.Radio(["Quality", "Fidelity"], interactive=True, label="Presetting", value="Quality")
354
  restart_button = gr.Button(value="Apply presetting")
355
-
356
 
357
- llave_button = gr.Button(value="Generate description by LlaVa (disabled)", visible=False)
358
- diffusion_button = gr.Button(value="🚀 Upscale/Restore", variant = "primary", elem_id="process_button")
359
- restore_information = gr.HTML(value="Restart the process to get another result.", visible=False)
360
- result_slider = ImageSlider(label='Output', show_label=True, elem_id="slider1")
361
- result_gallery = gr.Gallery(label='Output', show_label=True, elem_id="gallery1")
 
 
 
362
 
363
  with gr.Accordion("Feedback", open=True, visible=False):
364
- fb_score = gr.Slider(label="Feedback Score", minimum=1, maximum=5, value=3, step=1,
365
- interactive=True)
366
  fb_text = gr.Textbox(label="Feedback Text", value="", placeholder='Please enter your feedback here.')
367
  submit_button = gr.Button(value="Submit Feedback")
368
  with gr.Row():
@@ -412,6 +425,7 @@ with gr.Blocks(title="SUPIR") as interface:
412
  s_stage1,
413
  s_stage2,
414
  s_cfg,
 
415
  seed,
416
  s_churn,
417
  s_noise,
 
129
  s_stage1,
130
  s_stage2,
131
  s_cfg,
132
+ randomize_seed,
133
  seed,
134
  s_churn,
135
  s_noise,
 
143
  spt_linear_s_stage2,
144
  model_select
145
  ):
146
+ start = time.time()
147
  print('Start stage2_process')
148
  if torch.cuda.device_count() == 0:
149
  gr.Warning('Set this space to GPU config to make it work.')
 
202
  Image.fromarray(input_image).save(f'./history/{event_id[:5]}/{event_id[5:]}/LQ.png')
203
  for i, result in enumerate(results):
204
  Image.fromarray(result).save(f'./history/{event_id[:5]}/{event_id[5:]}/HQ_{i}.png')
205
+
206
  print('End stage2_process')
207
+ end = time.time()
208
+ secondes = int(end - start)
209
+ minutes = secondes // 60
210
+ secondes = secondes - (minutes * 60)
211
+ hours = minutes // 60
212
+ minutes = minutes - (hours * 60)
213
+ information = ("Restart the process to get another result. " if randomize_seed else "") + "The image(s) has(ve) been generated in " + ((str(hours) + " h, ") if hours != 0 else "") + ((str(minutes) + " min, ") if hours != 0 or minutes != 0 else "") + str(secondes) + " sec."
214
+
215
+ return [input_image] + results, [input_image] + results, gr.update(value = information, visible = True), event_id
216
 
217
  def load_and_reset(param_setting):
218
  print('Start load_and_reset')
 
296
  """)
297
  gr.HTML(title_html)
298
 
299
+ with gr.Group():
300
+ input_image = gr.Image(label="Input", show_label=True, type="numpy", height=600, elem_id="image-input")
301
+ prompt = gr.Textbox(label="Image description for LlaVa", value="", placeholder="A person, walking, in a town, Summer, photorealistic", lines=3, visible=False)
302
+ upscale = gr.Radio([1, 2, 3, 4, 5, 6, 7, 8], label="Upscale factor", info="Resolution x1 to x8", value=2, interactive=True)
303
+ a_prompt = gr.Textbox(label="Image description",
304
+ info="Help the AI to understand what the image represents",
305
+ value='Cinematic, High Contrast, highly detailed, taken using a Canon EOS R '
306
+ 'camera, hyper detailed photo - realistic maximum detail, 32k, Color '
307
+ 'Grading, ultra HD, extreme meticulous detailing, skin pore detailing, '
308
+ 'hyper sharpness, perfect without deformations.',
309
+ lines=3)
310
+ 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.")
311
 
312
  with gr.Accordion("Pre-denoising (optional)", open=False):
313
  gamma_correction = gr.Slider(label="Gamma Correction", minimum=0.1, maximum=2.0, value=1.0, step=0.1)
 
364
  with gr.Group():
365
  param_setting = gr.Radio(["Quality", "Fidelity"], interactive=True, label="Presetting", value="Quality")
366
  restart_button = gr.Button(value="Apply presetting")
 
367
 
368
+ with gr.Group():
369
+ llave_button = gr.Button(value="Generate description by LlaVa (disabled)", visible=False)
370
+
371
+ diffusion_button = gr.Button(value="🚀 Upscale/Restore", variant = "primary", elem_id="process_button")
372
+
373
+ restore_information = gr.HTML(value="Restart the process to get another result.", visible=False)
374
+ result_slider = ImageSlider(label='Output', show_label=True, elem_id="slider1")
375
+ result_gallery = gr.Gallery(label='Output', show_label=True, elem_id="gallery1")
376
 
377
  with gr.Accordion("Feedback", open=True, visible=False):
378
+ fb_score = gr.Slider(label="Feedback Score", minimum=1, maximum=5, value=3, step=1, interactive=True)
 
379
  fb_text = gr.Textbox(label="Feedback Text", value="", placeholder='Please enter your feedback here.')
380
  submit_button = gr.Button(value="Submit Feedback")
381
  with gr.Row():
 
425
  s_stage1,
426
  s_stage2,
427
  s_cfg,
428
+ randomize_seed,
429
  seed,
430
  s_churn,
431
  s_noise,