shikunl commited on
Commit
359b3f0
β€’
1 Parent(s): 33747ca

Update with md5sum and half precision inference

Browse files
app.py CHANGED
@@ -20,6 +20,7 @@ description = """
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  # Prismer
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  The official demo for **Prismer: A Vision-Language Model with An Ensemble of Experts**.
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  Please refer to our [project page](https://shikun.io/projects/prismer) or [github](https://github.com/NVlabs/prismer) for more details.
 
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  """
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  if (SPACE_ID := os.getenv('SPACE_ID')) is not None:
 
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  # Prismer
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  The official demo for **Prismer: A Vision-Language Model with An Ensemble of Experts**.
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  Please refer to our [project page](https://shikun.io/projects/prismer) or [github](https://github.com/NVlabs/prismer) for more details.
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+ Expert labels will be only computed once for the same image checked with md5sum.
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  """
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  if (SPACE_ID := os.getenv('SPACE_ID')) is not None:
label_prettify.py CHANGED
@@ -8,6 +8,7 @@ import numpy as np
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  import shutil
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  from prismer.utils import create_ade20k_label_colormap
 
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  obj_label_map = torch.load('prismer/dataset/detection_features.pt')['labels']
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  coco_label_map = torch.load('prismer/dataset/coco_features.pt')['labels']
 
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  import shutil
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  from prismer.utils import create_ade20k_label_colormap
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+ matplotlib.use('agg')
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  obj_label_map = torch.load('prismer/dataset/detection_features.pt')['labels']
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  coco_label_map = torch.load('prismer/dataset/coco_features.pt')['labels']
prismer/configs/experts.yaml CHANGED
@@ -1,3 +1,3 @@
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  data_path: helpers
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- im_name: 4265e527d8897c032baabea78e590c18
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  save_path: helpers/labels
 
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  data_path: helpers
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+ im_name: ca2a8e1305af24483124b85c53bd24b3
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  save_path: helpers/labels
prismer_model.py CHANGED
@@ -34,10 +34,10 @@ def download_models() -> None:
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  subprocess.run(shlex.split('python download_checkpoints.py --download_experts=True'), cwd='prismer')
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  model_names = [
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- 'vqa_prismer_base',
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- 'vqa_prismer_large',
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  'pretrain_prismer_base',
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- 'pretrain_prismer_large',
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  ]
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  for model_name in model_names:
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  if pathlib.Path(f'prismer/logging/{model_name}').exists():
@@ -78,6 +78,7 @@ def run_experts(image_path: str) -> Tuple[str, Tuple[str, ...]]:
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  config = yaml.load(open('prismer/configs/experts.yaml', 'r'), Loader=yaml.Loader)
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  config['im_name'] = im_name
 
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  with open('prismer/configs/experts.yaml', 'w') as yaml_file:
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  yaml.dump(config, yaml_file, default_flow_style=False)
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@@ -89,7 +90,7 @@ def run_experts(image_path: str) -> Tuple[str, Tuple[str, ...]]:
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  run_expert('depth')
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  with concurrent.futures.ProcessPoolExecutor() as executor:
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  executor.map(run_expert, expert_names)
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- executor.shutdown(wait=True)
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  # no parallelization just to be safe
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  # expert_names = ['depth', 'edge', 'normal', 'objdet', 'ocrdet', 'segmentation']
 
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  subprocess.run(shlex.split('python download_checkpoints.py --download_experts=True'), cwd='prismer')
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  model_names = [
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+ # 'vqa_prismer_base',
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+ # 'vqa_prismer_large',
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  'pretrain_prismer_base',
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+ # 'pretrain_prismer_large',
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  ]
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  for model_name in model_names:
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  if pathlib.Path(f'prismer/logging/{model_name}').exists():
 
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  config = yaml.load(open('prismer/configs/experts.yaml', 'r'), Loader=yaml.Loader)
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  config['im_name'] = im_name
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+ print(im_name)
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  with open('prismer/configs/experts.yaml', 'w') as yaml_file:
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  yaml.dump(config, yaml_file, default_flow_style=False)
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  run_expert('depth')
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  with concurrent.futures.ProcessPoolExecutor() as executor:
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  executor.map(run_expert, expert_names)
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+ executor.shutdown(wait=True)
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  # no parallelization just to be safe
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  # expert_names = ['depth', 'edge', 'normal', 'objdet', 'ocrdet', 'segmentation']