ford442 commited on
Commit
73b4de6
·
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1 Parent(s): fe5ad45

Update app.py

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Files changed (1) hide show
  1. app.py +18 -0
app.py CHANGED
@@ -267,6 +267,7 @@ def generate_30(
267
  num_inference_steps: int = 125,
268
  latent_file = gr.File(), # Add latents file input
269
  latent_file_2 = gr.File(), # Add latents file input
 
270
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
271
  ):
272
  ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
@@ -274,6 +275,10 @@ def generate_30(
274
  generator = torch.Generator(device='cuda').manual_seed(seed)
275
  if latent_file is not None: # Check if a latent file is provided
276
  sd_image_a = Image.open(latent_file.name)
 
 
 
 
277
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
278
  filename= f'rv_IP_{timestamp}.png'
279
  print("-- using image file --")
@@ -315,6 +320,7 @@ def generate_60(
315
  num_inference_steps: int = 125,
316
  latent_file = gr.File(), # Add latents file input
317
  latent_file_2 = gr.File(), # Add latents file input
 
318
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
319
  ):
320
  ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
@@ -322,6 +328,10 @@ def generate_60(
322
  generator = torch.Generator(device='cuda').manual_seed(seed)
323
  if latent_file is not None: # Check if a latent file is provided
324
  sd_image_a = Image.open(latent_file.name)
 
 
 
 
325
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
326
  filename= f'rv_IP_{timestamp}.png'
327
  print("-- using image file --")
@@ -363,6 +373,7 @@ def generate_90(
363
  num_inference_steps: int = 125,
364
  latent_file = gr.File(), # Add latents file input
365
  latent_file_2 = gr.File(), # Add latents file input
 
366
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
367
  ):
368
  ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
@@ -370,6 +381,10 @@ def generate_90(
370
  generator = torch.Generator(device='cuda').manual_seed(seed)
371
  if latent_file is not None: # Check if a latent file is provided
372
  sd_image_a = Image.open(latent_file.name)
 
 
 
 
373
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
374
  filename= f'rv_IP_{timestamp}.png'
375
  print("-- using image file --")
@@ -533,6 +548,7 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
533
  num_inference_steps,
534
  latent_file,
535
  latent_file_2,
 
536
  ],
537
  outputs=[result],
538
  )
@@ -554,6 +570,7 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
554
  num_inference_steps,
555
  latent_file,
556
  latent_file_2,
 
557
  ],
558
  outputs=[result],
559
  )
@@ -575,6 +592,7 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
575
  num_inference_steps,
576
  latent_file,
577
  latent_file_2,
 
578
  ],
579
  outputs=[result],
580
  )
 
267
  num_inference_steps: int = 125,
268
  latent_file = gr.File(), # Add latents file input
269
  latent_file_2 = gr.File(), # Add latents file input
270
+ samples=1,
271
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
272
  ):
273
  ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
 
275
  generator = torch.Generator(device='cuda').manual_seed(seed)
276
  if latent_file is not None: # Check if a latent file is provided
277
  sd_image_a = Image.open(latent_file.name)
278
+ if latent_file_2 is not None: # Check if a latent file is provided
279
+ sd_image_b = Image.open(latent_file_2.name)
280
+ else:
281
+ sd_image_b = None
282
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
283
  filename= f'rv_IP_{timestamp}.png'
284
  print("-- using image file --")
 
320
  num_inference_steps: int = 125,
321
  latent_file = gr.File(), # Add latents file input
322
  latent_file_2 = gr.File(), # Add latents file input
323
+ samples=1,
324
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
325
  ):
326
  ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
 
328
  generator = torch.Generator(device='cuda').manual_seed(seed)
329
  if latent_file is not None: # Check if a latent file is provided
330
  sd_image_a = Image.open(latent_file.name)
331
+ if latent_file_2 is not None: # Check if a latent file is provided
332
+ sd_image_b = Image.open(latent_file_2.name)
333
+ else:
334
+ sd_image_b = None
335
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
336
  filename= f'rv_IP_{timestamp}.png'
337
  print("-- using image file --")
 
373
  num_inference_steps: int = 125,
374
  latent_file = gr.File(), # Add latents file input
375
  latent_file_2 = gr.File(), # Add latents file input
376
+ samples=1,
377
  progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
378
  ):
379
  ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
 
381
  generator = torch.Generator(device='cuda').manual_seed(seed)
382
  if latent_file is not None: # Check if a latent file is provided
383
  sd_image_a = Image.open(latent_file.name)
384
+ if latent_file_2 is not None: # Check if a latent file is provided
385
+ sd_image_b = Image.open(latent_file_2.name)
386
+ else:
387
+ sd_image_b = None
388
  timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
389
  filename= f'rv_IP_{timestamp}.png'
390
  print("-- using image file --")
 
548
  num_inference_steps,
549
  latent_file,
550
  latent_file_2,
551
+ samples,
552
  ],
553
  outputs=[result],
554
  )
 
570
  num_inference_steps,
571
  latent_file,
572
  latent_file_2,
573
+ samples,
574
  ],
575
  outputs=[result],
576
  )
 
592
  num_inference_steps,
593
  latent_file,
594
  latent_file_2,
595
+ samples,
596
  ],
597
  outputs=[result],
598
  )