ford442 commited on
Commit
633ba49
·
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1 Parent(s): c3167cb

Update app.py

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Files changed (1) hide show
  1. app.py +148 -5
app.py CHANGED
@@ -257,6 +257,14 @@ def generate_30(
257
  num_inference_steps: int = 125,
258
  latent_file = gr.File(), # Add latents file input
259
  latent_file_2 = gr.File(), # Add latents file input
 
 
 
 
 
 
 
 
260
  samples=1,
261
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
262
  ):
@@ -268,6 +276,18 @@ def generate_30(
268
  sd_image_b = Image.open(latent_file_2.name)
269
  else:
270
  sd_image_b = None
 
 
 
 
 
 
 
 
 
 
 
 
271
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
272
  filename= f'rv_IP_{timestamp}.png'
273
  print("-- using image file --")
@@ -276,9 +296,16 @@ def generate_30(
276
  sd_image = ip_model.generate(
277
  pil_image=sd_image_a,
278
  pil_image_2=sd_image_b,
 
 
 
279
  prompt=prompt,
280
  negative_prompt=negative_prompt,
281
- scale=1.0,
 
 
 
 
282
  num_samples=samples,
283
  seed=seed,
284
  num_inference_steps=num_inference_steps,
@@ -299,7 +326,7 @@ def generate_30(
299
  print('-- IMAGE REQUIRED --')
300
  return image_paths
301
 
302
- @spaces.GPU(duration=60)
303
  def generate_60(
304
  prompt: str = "",
305
  negative_prompt: str = "",
@@ -311,6 +338,14 @@ def generate_60(
311
  num_inference_steps: int = 125,
312
  latent_file = gr.File(), # Add latents file input
313
  latent_file_2 = gr.File(), # Add latents file input
 
 
 
 
 
 
 
 
314
  samples=1,
315
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
316
  ):
@@ -322,6 +357,18 @@ def generate_60(
322
  sd_image_b = Image.open(latent_file_2.name)
323
  else:
324
  sd_image_b = None
 
 
 
 
 
 
 
 
 
 
 
 
325
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
326
  filename= f'rv_IP_{timestamp}.png'
327
  print("-- using image file --")
@@ -330,9 +377,16 @@ def generate_60(
330
  sd_image = ip_model.generate(
331
  pil_image=sd_image_a,
332
  pil_image_2=sd_image_b,
 
 
 
333
  prompt=prompt,
334
  negative_prompt=negative_prompt,
335
- scale=1.0,
 
 
 
 
336
  num_samples=samples,
337
  seed=seed,
338
  num_inference_steps=num_inference_steps,
@@ -353,7 +407,7 @@ def generate_60(
353
  print('-- IMAGE REQUIRED --')
354
  return image_paths
355
 
356
- @spaces.GPU(duration=90)
357
  def generate_90(
358
  prompt: str = "",
359
  negative_prompt: str = "",
@@ -365,6 +419,14 @@ def generate_90(
365
  num_inference_steps: int = 125,
366
  latent_file = gr.File(), # Add latents file input
367
  latent_file_2 = gr.File(), # Add latents file input
 
 
 
 
 
 
 
 
368
  samples=1,
369
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
370
  ):
@@ -376,6 +438,18 @@ def generate_90(
376
  sd_image_b = Image.open(latent_file_2.name)
377
  else:
378
  sd_image_b = None
 
 
 
 
 
 
 
 
 
 
 
 
379
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
380
  filename= f'rv_IP_{timestamp}.png'
381
  print("-- using image file --")
@@ -384,9 +458,16 @@ def generate_90(
384
  sd_image = ip_model.generate(
385
  pil_image=sd_image_a,
386
  pil_image_2=sd_image_b,
 
 
 
387
  prompt=prompt,
388
  negative_prompt=negative_prompt,
389
- scale=1.0,
 
 
 
 
390
  num_samples=samples,
391
  seed=seed,
392
  num_inference_steps=num_inference_steps,
@@ -452,7 +533,45 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
452
 
453
  with gr.Row():
454
  latent_file = gr.File(label="Image Prompt (Required)")
 
 
 
 
 
 
 
455
  latent_file_2 = gr.File(label="Image Prompt 2 (Optional)")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
456
  style_selection = gr.Radio(
457
  show_label=True,
458
  container=True,
@@ -541,6 +660,14 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
541
  num_inference_steps,
542
  latent_file,
543
  latent_file_2,
 
 
 
 
 
 
 
 
544
  samples,
545
  ],
546
  outputs=[result],
@@ -563,6 +690,14 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
563
  num_inference_steps,
564
  latent_file,
565
  latent_file_2,
 
 
 
 
 
 
 
 
566
  samples,
567
  ],
568
  outputs=[result],
@@ -585,6 +720,14 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
585
  num_inference_steps,
586
  latent_file,
587
  latent_file_2,
 
 
 
 
 
 
 
 
588
  samples,
589
  ],
590
  outputs=[result],
 
257
  num_inference_steps: int = 125,
258
  latent_file = gr.File(), # Add latents file input
259
  latent_file_2 = gr.File(), # Add latents file input
260
+ latent_file_3 = gr.File(), # Add latents file input
261
+ latent_file_4 = gr.File(), # Add latents file input
262
+ latent_file_5 = gr.File(), # Add latents file input
263
+ latent_file_1_scale: float = 3.8,
264
+ latent_file_2_scale: float = 3.8,
265
+ latent_file_3_scale: float = 3.8,
266
+ latent_file_4_scale: float = 3.8,
267
+ latent_file_5_scale: float = 3.8,
268
  samples=1,
269
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
270
  ):
 
276
  sd_image_b = Image.open(latent_file_2.name)
277
  else:
278
  sd_image_b = None
279
+ if latent_file_3 is not None: # Check if a latent file is provided
280
+ sd_image_c = Image.open(latent_file_3.name)
281
+ else:
282
+ sd_image_c = None
283
+ if latent_file_4 is not None: # Check if a latent file is provided
284
+ sd_image_d = Image.open(latent_file_4.name)
285
+ else:
286
+ sd_image_d = None
287
+ if latent_file_5 is not None: # Check if a latent file is provided
288
+ sd_image_e = Image.open(latent_file_5.name)
289
+ else:
290
+ sd_image_e = None
291
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
292
  filename= f'rv_IP_{timestamp}.png'
293
  print("-- using image file --")
 
296
  sd_image = ip_model.generate(
297
  pil_image=sd_image_a,
298
  pil_image_2=sd_image_b,
299
+ pil_image_3=sd_image_c,
300
+ pil_image_4=sd_image_d,
301
+ pil_image_5=sd_image_e,
302
  prompt=prompt,
303
  negative_prompt=negative_prompt,
304
+ scale_1=latent_file_1_scale,
305
+ scale_2=latent_file_2_scale,
306
+ scale_3=latent_file_3_scale,
307
+ scale_4=latent_file_4_scale,
308
+ scale_5=latent_file_5_scale,
309
  num_samples=samples,
310
  seed=seed,
311
  num_inference_steps=num_inference_steps,
 
326
  print('-- IMAGE REQUIRED --')
327
  return image_paths
328
 
329
+ @spaces.GPU(duration=70)
330
  def generate_60(
331
  prompt: str = "",
332
  negative_prompt: str = "",
 
338
  num_inference_steps: int = 125,
339
  latent_file = gr.File(), # Add latents file input
340
  latent_file_2 = gr.File(), # Add latents file input
341
+ latent_file_3 = gr.File(), # Add latents file input
342
+ latent_file_4 = gr.File(), # Add latents file input
343
+ latent_file_5 = gr.File(), # Add latents file input
344
+ latent_file_1_scale: float = 3.8,
345
+ latent_file_2_scale: float = 3.8,
346
+ latent_file_3_scale: float = 3.8,
347
+ latent_file_4_scale: float = 3.8,
348
+ latent_file_5_scale: float = 3.8,
349
  samples=1,
350
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
351
  ):
 
357
  sd_image_b = Image.open(latent_file_2.name)
358
  else:
359
  sd_image_b = None
360
+ if latent_file_3 is not None: # Check if a latent file is provided
361
+ sd_image_c = Image.open(latent_file_3.name)
362
+ else:
363
+ sd_image_c = None
364
+ if latent_file_4 is not None: # Check if a latent file is provided
365
+ sd_image_d = Image.open(latent_file_4.name)
366
+ else:
367
+ sd_image_d = None
368
+ if latent_file_5 is not None: # Check if a latent file is provided
369
+ sd_image_e = Image.open(latent_file_5.name)
370
+ else:
371
+ sd_image_e = None
372
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
373
  filename= f'rv_IP_{timestamp}.png'
374
  print("-- using image file --")
 
377
  sd_image = ip_model.generate(
378
  pil_image=sd_image_a,
379
  pil_image_2=sd_image_b,
380
+ pil_image_3=sd_image_c,
381
+ pil_image_4=sd_image_d,
382
+ pil_image_5=sd_image_e,
383
  prompt=prompt,
384
  negative_prompt=negative_prompt,
385
+ scale_1=latent_file_1_scale,
386
+ scale_2=latent_file_2_scale,
387
+ scale_3=latent_file_3_scale,
388
+ scale_4=latent_file_4_scale,
389
+ scale_5=latent_file_5_scale,
390
  num_samples=samples,
391
  seed=seed,
392
  num_inference_steps=num_inference_steps,
 
407
  print('-- IMAGE REQUIRED --')
408
  return image_paths
409
 
410
+ @spaces.GPU(duration=100)
411
  def generate_90(
412
  prompt: str = "",
413
  negative_prompt: str = "",
 
419
  num_inference_steps: int = 125,
420
  latent_file = gr.File(), # Add latents file input
421
  latent_file_2 = gr.File(), # Add latents file input
422
+ latent_file_3 = gr.File(), # Add latents file input
423
+ latent_file_4 = gr.File(), # Add latents file input
424
+ latent_file_5 = gr.File(), # Add latents file input
425
+ latent_file_1_scale: float = 3.8,
426
+ latent_file_2_scale: float = 3.8,
427
+ latent_file_3_scale: float = 3.8,
428
+ latent_file_4_scale: float = 3.8,
429
+ latent_file_5_scale: float = 3.8,
430
  samples=1,
431
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
432
  ):
 
438
  sd_image_b = Image.open(latent_file_2.name)
439
  else:
440
  sd_image_b = None
441
+ if latent_file_3 is not None: # Check if a latent file is provided
442
+ sd_image_c = Image.open(latent_file_3.name)
443
+ else:
444
+ sd_image_c = None
445
+ if latent_file_4 is not None: # Check if a latent file is provided
446
+ sd_image_d = Image.open(latent_file_4.name)
447
+ else:
448
+ sd_image_d = None
449
+ if latent_file_5 is not None: # Check if a latent file is provided
450
+ sd_image_e = Image.open(latent_file_5.name)
451
+ else:
452
+ sd_image_e = None
453
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
454
  filename= f'rv_IP_{timestamp}.png'
455
  print("-- using image file --")
 
458
  sd_image = ip_model.generate(
459
  pil_image=sd_image_a,
460
  pil_image_2=sd_image_b,
461
+ pil_image_3=sd_image_c,
462
+ pil_image_4=sd_image_d,
463
+ pil_image_5=sd_image_e,
464
  prompt=prompt,
465
  negative_prompt=negative_prompt,
466
+ scale_1=latent_file_1_scale,
467
+ scale_2=latent_file_2_scale,
468
+ scale_3=latent_file_3_scale,
469
+ scale_4=latent_file_4_scale,
470
+ scale_5=latent_file_5_scale,
471
  num_samples=samples,
472
  seed=seed,
473
  num_inference_steps=num_inference_steps,
 
533
 
534
  with gr.Row():
535
  latent_file = gr.File(label="Image Prompt (Required)")
536
+ file_1_strength = gr.Slider(
537
+ label="Img 1 Str",
538
+ minimum=0.0,
539
+ maximum=16.0,
540
+ step=0.01,
541
+ value=3.8,
542
+ )
543
  latent_file_2 = gr.File(label="Image Prompt 2 (Optional)")
544
+ file_2_strength = gr.Slider(
545
+ label="Img 2 Str",
546
+ minimum=0.0,
547
+ maximum=16.0,
548
+ step=0.01,
549
+ value=3.8,
550
+ )
551
+ latent_file_3 = gr.File(label="Image Prompt 3 (Optional)")
552
+ file_3_strength = gr.Slider(
553
+ label="Img 3 Str",
554
+ minimum=0.0,
555
+ maximum=16.0,
556
+ step=0.01,
557
+ value=3.8,
558
+ )
559
+ latent_file_4 = gr.File(label="Image Prompt 4 (Optional)")
560
+ file_4_strength = gr.Slider(
561
+ label="Img 4 Str",
562
+ minimum=0.0,
563
+ maximum=16.0,
564
+ step=0.01,
565
+ value=3.8,
566
+ )
567
+ latent_file_5 = gr.File(label="Image Prompt 5 (Optional)")
568
+ file_5_strength = gr.Slider(
569
+ label="Img 5 Str",
570
+ minimum=0.0,
571
+ maximum=16.0,
572
+ step=0.01,
573
+ value=3.8,
574
+ )
575
  style_selection = gr.Radio(
576
  show_label=True,
577
  container=True,
 
660
  num_inference_steps,
661
  latent_file,
662
  latent_file_2,
663
+ latent_file_3,
664
+ latent_file_4,
665
+ latent_file_5,
666
+ file_1_strength,
667
+ file_2_strength,
668
+ file_3_strength,
669
+ file_4_strength,
670
+ file_5_strength,
671
  samples,
672
  ],
673
  outputs=[result],
 
690
  num_inference_steps,
691
  latent_file,
692
  latent_file_2,
693
+ latent_file_3,
694
+ latent_file_4,
695
+ latent_file_5,
696
+ file_1_strength,
697
+ file_2_strength,
698
+ file_3_strength,
699
+ file_4_strength,
700
+ file_5_strength,
701
  samples,
702
  ],
703
  outputs=[result],
 
720
  num_inference_steps,
721
  latent_file,
722
  latent_file_2,
723
+ latent_file_3,
724
+ latent_file_4,
725
+ latent_file_5,
726
+ file_1_strength,
727
+ file_2_strength,
728
+ file_3_strength,
729
+ file_4_strength,
730
+ file_5_strength,
731
  samples,
732
  ],
733
  outputs=[result],