Fabrice-TIERCELIN commited on
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243e220
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1 Parent(s): 4efac9e

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Files changed (1) hide show
  1. app.py +4 -5
app.py CHANGED
@@ -14,7 +14,6 @@ import numpy as np
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  import argparse
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  import random
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  import math
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- import time
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  # 20250506 pftq: Added for video input loading
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  import decord
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  # 20250506 pftq: Added for progress bars in video_encode
@@ -665,7 +664,6 @@ def worker_video(input_video, prompt, n_prompt, seed, batch, resolution, total_s
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  #save_bcthw_as_mp4(vae_decode(video_latents, vae).cpu(), os.path.join(outputs_folder, f'{job_id}_input_video.mp4'), fps=fps, crf=mp4_crf) # 20250507 pftq: test fast movement corrupted by vae encoding if vae batch size too low
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  for section_index in range(total_latent_sections):
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- start = time.time()
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  if stream.input_queue.top() == 'end':
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  stream.output_queue.push(('end', None))
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  return
@@ -745,9 +743,6 @@ def worker_video(input_video, prompt, n_prompt, seed, batch, resolution, total_s
745
 
746
  # 20250507 pftq: Fix for <=1 sec videos.
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  max_frames = min(latent_window_size * 4 - 3, history_latents.shape[2] * 4)
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- end = time.time()
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- secondes = int(end - start)
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- print("££££££££££££££££££££££££££££££££££££££££ " + str(secondes))
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  generated_latents = sample_hunyuan(
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  transformer=transformer,
@@ -778,6 +773,7 @@ def worker_video(input_video, prompt, n_prompt, seed, batch, resolution, total_s
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  clean_latent_4x_indices=clean_latent_4x_indices,
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  callback=callback,
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  )
 
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  total_generated_latent_frames += int(generated_latents.shape[2])
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  history_latents = torch.cat([history_latents, generated_latents.to(history_latents)], dim=2)
@@ -826,6 +822,9 @@ def worker_video(input_video, prompt, n_prompt, seed, batch, resolution, total_s
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  print(f'Decoded. Current latent shape {real_history_latents.shape}; pixel shape {history_pixels.shape}')
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  stream.output_queue.push(('file', output_filename))
 
 
 
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  seed = (seed + 1) % np.iinfo(np.int32).max
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  import argparse
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  import random
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  import math
 
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  # 20250506 pftq: Added for video input loading
18
  import decord
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  # 20250506 pftq: Added for progress bars in video_encode
 
664
  #save_bcthw_as_mp4(vae_decode(video_latents, vae).cpu(), os.path.join(outputs_folder, f'{job_id}_input_video.mp4'), fps=fps, crf=mp4_crf) # 20250507 pftq: test fast movement corrupted by vae encoding if vae batch size too low
665
 
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  for section_index in range(total_latent_sections):
 
667
  if stream.input_queue.top() == 'end':
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  stream.output_queue.push(('end', None))
669
  return
 
743
 
744
  # 20250507 pftq: Fix for <=1 sec videos.
745
  max_frames = min(latent_window_size * 4 - 3, history_latents.shape[2] * 4)
 
 
 
746
 
747
  generated_latents = sample_hunyuan(
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  transformer=transformer,
 
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  clean_latent_4x_indices=clean_latent_4x_indices,
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  callback=callback,
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  )
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+ start = time.time()
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  total_generated_latent_frames += int(generated_latents.shape[2])
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  history_latents = torch.cat([history_latents, generated_latents.to(history_latents)], dim=2)
 
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  print(f'Decoded. Current latent shape {real_history_latents.shape}; pixel shape {history_pixels.shape}')
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  stream.output_queue.push(('file', output_filename))
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+ end = time.time()
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+ secondes = int(end - start)
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+ print("££££££££££££££££££££££££££££££££££££££££ " + str(secondes))
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829
  seed = (seed + 1) % np.iinfo(np.int32).max
830