ZhengPeng7 commited on
Commit
fd82537
·
1 Parent(s): 1792b56

Remove redundant codes in fixing the HF space permission error.

Browse files
Files changed (1) hide show
  1. app.py +4 -6
app.py CHANGED
@@ -18,11 +18,9 @@ import zipfile
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  hf_cache_path = '/tmp/hf_cache'
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- os.environ["HUGGINGFACE_HUB_CACHE"] = hf_cache_path
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  os.environ["HF_HOME"] = hf_cache_path
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- os.environ["TRANSFORMERS_CACHE"] = hf_cache_path
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- os.environ["HF_MODULES_CACHE"] = os.path.join("/tmp/hf_cache", "modules")
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- os.makedirs(os.path.join("/tmp/hf_cache", "modules"), exist_ok=True)
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  import transformers
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  transformers.utils.move_cache()
@@ -99,7 +97,7 @@ usage_to_weights_file = {
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  'General-dynamic': 'BiRefNet_dynamic',
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  }
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- birefnet = transformers.AutoModelForImageSegmentation.from_pretrained('/'.join(('zhengpeng7', usage_to_weights_file['General'])), trust_remote_code=True, cache_dir=hf_cache_path)
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  birefnet.to(device)
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  birefnet.eval(); birefnet.half()
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@@ -112,7 +110,7 @@ def predict(images, resolution, weights_file):
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  # Load BiRefNet with chosen weights
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  _weights_file = '/'.join(('zhengpeng7', usage_to_weights_file[weights_file] if weights_file is not None else usage_to_weights_file['General']))
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  print('Using weights: {}.'.format(_weights_file))
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- birefnet = transformers.AutoModelForImageSegmentation.from_pretrained(_weights_file, trust_remote_code=True, cache_dir=hf_cache_path)
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  birefnet.to(device)
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  birefnet.eval(); birefnet.half()
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  hf_cache_path = '/tmp/hf_cache'
 
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  os.environ["HF_HOME"] = hf_cache_path
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+ # os.environ["HF_MODULES_CACHE"] = os.path.join("/tmp/hf_cache", "modules")
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+ os.makedirs(os.path.join(hf_cache_path, "modules"), exist_ok=True)
 
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  import transformers
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  transformers.utils.move_cache()
 
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  'General-dynamic': 'BiRefNet_dynamic',
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  }
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+ birefnet = transformers.AutoModelForImageSegmentation.from_pretrained('/'.join(('zhengpeng7', usage_to_weights_file['General'])), trust_remote_code=True)
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  birefnet.to(device)
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  birefnet.eval(); birefnet.half()
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  # Load BiRefNet with chosen weights
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  _weights_file = '/'.join(('zhengpeng7', usage_to_weights_file[weights_file] if weights_file is not None else usage_to_weights_file['General']))
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  print('Using weights: {}.'.format(_weights_file))
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+ birefnet = transformers.AutoModelForImageSegmentation.from_pretrained(_weights_file, trust_remote_code=True)
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  birefnet.to(device)
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  birefnet.eval(); birefnet.half()
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