c40826179b
2.Provide more trained models with different input resoulution.
37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
def parse_model_cfg(path):
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"""Parses the yolo-v3 layer configuration file and returns module definitions"""
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file = open(path, 'r')
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lines = file.read().split('\n')
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lines = [x for x in lines if x and not x.startswith('#')]
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lines = [x.rstrip().lstrip() for x in lines] # get rid of fringe whitespaces
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module_defs = []
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for line in lines:
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if line.startswith('['): # This marks the start of a new block
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module_defs.append({})
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module_defs[-1]['type'] = line[1:-1].rstrip()
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if module_defs[-1]['type'] == 'convolutional':
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module_defs[-1]['batch_normalize'] = 0
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else:
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key, value = line.split("=")
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value = value.strip()
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if value[0] == '$':
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value = module_defs[0].get(value.strip('$'), None)
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module_defs[-1][key.rstrip()] = value
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return module_defs
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def parse_data_cfg(path):
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"""Parses the data configuration file"""
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options = dict()
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options['gpus'] = '0'
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options['num_workers'] = '10'
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with open(path, 'r') as fp:
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lines = fp.readlines()
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for line in lines:
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line = line.strip()
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if line == '' or line.startswith('#'):
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continue
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key, value = line.split('=')
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options[key.strip()] = value.strip()
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return options
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