Anonymous commited on
Commit
bfa1f1d
1 Parent(s): a2ce0ab

remove 512

Browse files
Files changed (1) hide show
  1. app.py +24 -23
app.py CHANGED
@@ -64,27 +64,27 @@ def infer(prompt, output_size, seed, num_frames, ddim_steps, unconditional_guida
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  model = model_1024
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  fps = 28
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  num_frames = min(num_frames, 36)
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- elif output_size == "256x256":
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- width = 256
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- height = 256
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- ckpt_dir_256 = "checkpoints/base_256_v1"
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- ckpt_path_256 = "checkpoints/base_256_v1/model_256.pth"
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- config_256 = "configs/inference_t2v_tconv256_v1.0_freenoise.yaml"
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- config_256 = OmegaConf.load(config_256)
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- model_config_256 = config_256.pop("model", OmegaConf.create())
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- model_256 = instantiate_from_config(model_config_256)
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- model_256 = model_256.cuda()
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- if not os.path.exists(ckpt_path_256):
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- os.makedirs(ckpt_dir_256, exist_ok=True)
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- hf_hub_download(repo_id="MoonQiu/LongerCrafter", filename="model_256.pth", local_dir=ckpt_dir_256)
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- try:
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- model_256 = load_model_checkpoint(model_256, ckpt_path_256)
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- except:
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- hf_hub_download(repo_id="MoonQiu/LongerCrafter", filename="model_256.pth", local_dir=ckpt_dir_256, force_download=True)
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- model_256 = load_model_checkpoint(model_256, ckpt_path_256)
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- model_256.eval()
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- model = model_256
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- fps = 8
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  if seed is None:
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  seed = int.from_bytes(os.urandom(2), "big")
@@ -287,11 +287,12 @@ with gr.Blocks(css=css) as demo:
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  with gr.Accordion('FreeNoise Parameters (feel free to adjust these parameters based on your prompt): ', open=False):
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  with gr.Row():
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  # output_size = gr.Dropdown(["320x512", "576x1024"], value="320x512", label="Output Size", info="250s for 512 model, 900s for 1024 model (32 frames). Recovering from sleeping will take more time to download ckpt")
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- output_size = gr.Dropdown(["256x256", "576x1024"], value="576x1024", label="Output Size", info="900s for 1024 model (32 frames). Recovering from sleeping will take more time to download ckpt")
 
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  with gr.Row():
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  num_frames = gr.Slider(label='Frames (a multiple of 4), max 36 for 1024 model',
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  minimum=16,
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- maximum=64,
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  step=4,
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  value=32)
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  ddim_steps = gr.Slider(label='DDIM Steps',
 
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  model = model_1024
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  fps = 28
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  num_frames = min(num_frames, 36)
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+ # elif output_size == "256x256":
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+ # width = 256
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+ # height = 256
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+ # ckpt_dir_256 = "checkpoints/base_256_v1"
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+ # ckpt_path_256 = "checkpoints/base_256_v1/model_256.pth"
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+ # config_256 = "configs/inference_t2v_tconv256_v1.0_freenoise.yaml"
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+ # config_256 = OmegaConf.load(config_256)
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+ # model_config_256 = config_256.pop("model", OmegaConf.create())
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+ # model_256 = instantiate_from_config(model_config_256)
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+ # model_256 = model_256.cuda()
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+ # if not os.path.exists(ckpt_path_256):
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+ # os.makedirs(ckpt_dir_256, exist_ok=True)
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+ # hf_hub_download(repo_id="MoonQiu/LongerCrafter", filename="model_256.pth", local_dir=ckpt_dir_256)
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+ # try:
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+ # model_256 = load_model_checkpoint(model_256, ckpt_path_256)
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+ # except:
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+ # hf_hub_download(repo_id="MoonQiu/LongerCrafter", filename="model_256.pth", local_dir=ckpt_dir_256, force_download=True)
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+ # model_256 = load_model_checkpoint(model_256, ckpt_path_256)
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+ # model_256.eval()
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+ # model = model_256
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+ # fps = 8
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  if seed is None:
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  seed = int.from_bytes(os.urandom(2), "big")
 
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  with gr.Accordion('FreeNoise Parameters (feel free to adjust these parameters based on your prompt): ', open=False):
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  with gr.Row():
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  # output_size = gr.Dropdown(["320x512", "576x1024"], value="320x512", label="Output Size", info="250s for 512 model, 900s for 1024 model (32 frames). Recovering from sleeping will take more time to download ckpt")
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+ # output_size = gr.Dropdown(["256x256", "576x1024"], value="576x1024", label="Output Size", info="900s for 1024 model (32 frames). Recovering from sleeping will take more time to download ckpt")
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+ output_size = gr.Dropdown(["576x1024"], value="576x1024", label="Output Size", info="900s for 1024 model (32 frames). Recovering from sleeping will take more time to download ckpt")
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  with gr.Row():
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  num_frames = gr.Slider(label='Frames (a multiple of 4), max 36 for 1024 model',
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  minimum=16,
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+ maximum=36,
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  step=4,
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  value=32)
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  ddim_steps = gr.Slider(label='DDIM Steps',