ford442 commited on
Commit
e6ea6a6
1 Parent(s): 7f76633

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +3 -3
app.py CHANGED
@@ -158,7 +158,7 @@ preset_options = [
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  {"label": "896x608, 73 frames", "width": 896, "height": 608, "num_frames": 73},
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  {"label": "896x544, 81 frames", "width": 896, "height": 544, "num_frames": 81},
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  {"label": "832x544, 89 frames", "width": 832, "height": 544, "num_frames": 89},
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- {"label": "768x768, 200 frames", "width": 768, "height": 768, "num_frames": 160},
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  {"label": "768x512, 97 frames", "width": 768, "height": 512, "num_frames": 97},
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  {"label": "800x480, 105 frames", "width": 800, "height": 480, "num_frames": 105},
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  {"label": "736x480, 113 frames", "width": 736, "height": 480, "num_frames": 113},
@@ -250,7 +250,7 @@ def generate_video_from_text(
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  "media_items": None,
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  }
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- generator = torch.Generator(device="cpu").manual_seed(seed)
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  def gradio_progress_callback(self, step, timestep, kwargs):
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  progress((step + 1) / num_inference_steps)
@@ -346,7 +346,7 @@ def generate_video_from_image(
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  "media_items": media_items,
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  }
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- generator = torch.Generator(device="cpu").manual_seed(seed)
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  def gradio_progress_callback(self, step, timestep, kwargs):
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  progress((step + 1) / num_inference_steps)
 
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  {"label": "896x608, 73 frames", "width": 896, "height": 608, "num_frames": 73},
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  {"label": "896x544, 81 frames", "width": 896, "height": 544, "num_frames": 81},
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  {"label": "832x544, 89 frames", "width": 832, "height": 544, "num_frames": 89},
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+ {"label": "768x768, 200 frames", "width": 768, "height": 768, "num_frames": 140},
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  {"label": "768x512, 97 frames", "width": 768, "height": 512, "num_frames": 97},
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  {"label": "800x480, 105 frames", "width": 800, "height": 480, "num_frames": 105},
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  {"label": "736x480, 113 frames", "width": 736, "height": 480, "num_frames": 113},
 
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  "media_items": None,
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  }
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+ generator = torch.Generator(device="cuda").manual_seed(seed)
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  def gradio_progress_callback(self, step, timestep, kwargs):
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  progress((step + 1) / num_inference_steps)
 
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  "media_items": media_items,
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  }
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+ generator = torch.Generator(device="cuda").manual_seed(seed)
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  def gradio_progress_callback(self, step, timestep, kwargs):
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  progress((step + 1) / num_inference_steps)