Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -211,6 +211,9 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
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return seed
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def uploadNote():
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with open(filename, "w") as f:
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f.write(f"Realvis 5.0 (Tester B): {seed} png\n")
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f.write(f"Date/time: {timestamp} \n")
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@@ -265,10 +268,7 @@ def generate_30(
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options["use_resolution_binning"] = True
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images = []
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pipe.scheduler.set_timesteps(num_inference_steps,device)
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-
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filename= f'tst_{seed}.txt'
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timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
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for i in range(0, num_images, BATCH_SIZE):
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batch_options = options.copy()
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batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
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@@ -323,9 +323,6 @@ def generate_60(
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options["use_resolution_binning"] = True
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images = []
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pipe.scheduler.set_timesteps(num_inference_steps,device)
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# write note txt
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filename= f'tst_{seed}.txt'
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timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
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uploadNote()
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for i in range(0, num_images, BATCH_SIZE):
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batch_options = options.copy()
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@@ -381,9 +378,6 @@ def generate_90(
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options["use_resolution_binning"] = True
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images = []
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pipe.scheduler.set_timesteps(num_inference_steps,device)
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# write note txt
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filename= f'tst_{seed}.txt'
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timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
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uploadNote()
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for i in range(0, num_images, BATCH_SIZE):
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batch_options = options.copy()
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return seed
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def uploadNote():
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# write note txt
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filename= f'tst_B_{seed}.txt'
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timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
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with open(filename, "w") as f:
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f.write(f"Realvis 5.0 (Tester B): {seed} png\n")
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f.write(f"Date/time: {timestamp} \n")
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options["use_resolution_binning"] = True
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images = []
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pipe.scheduler.set_timesteps(num_inference_steps,device)
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uploadNote()
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for i in range(0, num_images, BATCH_SIZE):
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batch_options = options.copy()
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batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
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options["use_resolution_binning"] = True
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images = []
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pipe.scheduler.set_timesteps(num_inference_steps,device)
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uploadNote()
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for i in range(0, num_images, BATCH_SIZE):
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batch_options = options.copy()
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options["use_resolution_binning"] = True
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images = []
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pipe.scheduler.set_timesteps(num_inference_steps,device)
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uploadNote()
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for i in range(0, num_images, BATCH_SIZE):
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batch_options = options.copy()
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