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Update app.py
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app.py
CHANGED
@@ -126,10 +126,10 @@ def run_inference(prompt, video_path, condition, video_length, seed, steps):
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total_frames = get_video_dimension(video_path)[3]
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# Resize the video
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resized = resize_video(video_path, 'resized.mp4', 512, 512, target_fps)
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# normalize pixels
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normalized = normalize_and_save_video(resized, 'normalized.mp4')
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output_path = 'output/'
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os.makedirs(output_path, exist_ok=True)
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@@ -141,27 +141,27 @@ def run_inference(prompt, video_path, condition, video_length, seed, steps):
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print(f"RUNNING INFERENCE ...")
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if video_length > 12:
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command = f"python inference.py --prompt '{prompt}' --inference_steps {steps} --condition '{condition}' --video_path '{
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else:
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command = f"python inference.py --prompt '{prompt}' --inference_steps {steps} --condition '{condition}' --video_path '{
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try:
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subprocess.run(command, shell=True)
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# Construct the video path
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video_path_output = os.path.join(output_path, f"result.mp4")
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# Resize to original video input size
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o_width = get_video_dimension(video_path)[0]
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o_height = get_video_dimension(video_path)[1]
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resize_video(video_path_output, 'resized_final.mp4', o_width, o_height, target_fps)
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print(f"FINISHED !")
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return "done", 'resized_final.mp4'
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except cuda.Error as e:
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return f"CUDA Error: {e}", None
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except RuntimeError as e:
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return f"Runtime Error: {e}", None
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css="""
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total_frames = get_video_dimension(video_path)[3]
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# Resize the video
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#resized = resize_video(video_path, 'resized.mp4', 512, 512, target_fps)
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# normalize pixels
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#normalized = normalize_and_save_video(resized, 'normalized.mp4')
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output_path = 'output/'
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os.makedirs(output_path, exist_ok=True)
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print(f"RUNNING INFERENCE ...")
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if video_length > 12:
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command = f"python inference.py --prompt '{prompt}' --inference_steps {steps} --condition '{condition}' --video_path '{video_path}' --output_path '{output_path}' --temp_chunk_path 'result' --width 512 --height 512 --fps {target_fps} --seed {seed} --video_length {video_length} --smoother_steps 19 20 --is_long_video"
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else:
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command = f"python inference.py --prompt '{prompt}' --inference_steps {steps} --condition '{condition}' --video_path '{video_path}' --output_path '{output_path}' --temp_chunk_path 'result' --width 512 --height 512 --fps {target_fps} --seed {seed} --video_length {video_length} --smoother_steps 19 20"
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try:
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subprocess.run(command, shell=True)
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except cuda.Error as e:
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return f"CUDA Error: {e}", None
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except RuntimeError as e:
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return f"Runtime Error: {e}", None
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# Construct the video path
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video_path_output = os.path.join(output_path, f"result.mp4")
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# Resize to original video input size
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o_width = get_video_dimension(video_path)[0]
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o_height = get_video_dimension(video_path)[1]
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resize_video(video_path_output, 'resized_final.mp4', o_width, o_height, target_fps)
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print(f"FINISHED !")
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return "done", 'resized_final.mp4'
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css="""
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