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Update app.py
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app.py
CHANGED
@@ -1,12 +1,12 @@
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import torch
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torch.jit.script = lambda f: f
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# General
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import os
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from os.path import join as opj
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import argparse
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import datetime
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from pathlib import Path
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import spaces
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import gradio as gr
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import tempfile
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import yaml
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@@ -56,7 +56,7 @@ msxl_model = init_v2v_model(cfg_v2v, device)
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# -------------------------
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# ----- Functionality -----
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# -------------------------
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@spaces.GPU(duration=120)
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def generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, seed, t, image_guidance, where_to_log=result_fol):
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now = datetime.datetime.now()
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name = prompt[:100].replace(" ", "_") + "_" + str(now.time()).replace(":", "_").replace(".", "_")
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@@ -86,7 +86,7 @@ def generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, se
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video_path = opj(where_to_log, name+".mp4")
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return video_path
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@spaces.GPU(duration=400)
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def enhance(prompt, input_to_enhance, num_frames=None, image=None, model_name_stage1=None, model_name_stage2=None, seed=33, t=50, image_guidance=9.5, result_fol=result_fol):
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if input_to_enhance is None:
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input_to_enhance = generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, seed, t, image_guidance)
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import torch
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# torch.jit.script = lambda f: f
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# General
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import os
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from os.path import join as opj
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import argparse
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import datetime
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from pathlib import Path
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# import spaces
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import gradio as gr
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import tempfile
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import yaml
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# -------------------------
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# ----- Functionality -----
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# -------------------------
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# @spaces.GPU(duration=120)
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def generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, seed, t, image_guidance, where_to_log=result_fol):
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now = datetime.datetime.now()
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name = prompt[:100].replace(" ", "_") + "_" + str(now.time()).replace(":", "_").replace(".", "_")
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video_path = opj(where_to_log, name+".mp4")
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return video_path
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# @spaces.GPU(duration=400)
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def enhance(prompt, input_to_enhance, num_frames=None, image=None, model_name_stage1=None, model_name_stage2=None, seed=33, t=50, image_guidance=9.5, result_fol=result_fol):
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if input_to_enhance is None:
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input_to_enhance = generate(prompt, num_frames, image, model_name_stage1, model_name_stage2, seed, t, image_guidance)
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