Module heyvi.model.yolov3.utils.parse_config
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def parse_model_config(path):
"""Parses the yolo-v3 layer configuration file and returns module definitions"""
file = open(path, 'r')
lines = file.read().split('\n')
lines = [x for x in lines if x and not x.startswith('#')]
lines = [x.rstrip().lstrip() for x in lines] # get rid of fringe whitespaces
module_defs = []
for line in lines:
if line.startswith('['): # This marks the start of a new block
module_defs.append({})
module_defs[-1]['type'] = line[1:-1].rstrip()
if module_defs[-1]['type'] == 'convolutional':
module_defs[-1]['batch_normalize'] = 0
else:
key, value = line.split("=")
value = value.strip()
module_defs[-1][key.rstrip()] = value.strip()
return module_defs
def parse_data_config(path):
"""Parses the data configuration file"""
options = dict()
options['gpus'] = '0,1,2,3'
options['num_workers'] = '10'
with open(path, 'r') as fp:
lines = fp.readlines()
for line in lines:
line = line.strip()
if line == '' or line.startswith('#'):
continue
key, value = line.split('=')
options[key.strip()] = value.strip()
return options
Functions
def parse_data_config(path)
-
Parses the data configuration file
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def parse_data_config(path): """Parses the data configuration file""" options = dict() options['gpus'] = '0,1,2,3' options['num_workers'] = '10' with open(path, 'r') as fp: lines = fp.readlines() for line in lines: line = line.strip() if line == '' or line.startswith('#'): continue key, value = line.split('=') options[key.strip()] = value.strip() return options
def parse_model_config(path)
-
Parses the yolo-v3 layer configuration file and returns module definitions
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def parse_model_config(path): """Parses the yolo-v3 layer configuration file and returns module definitions""" file = open(path, 'r') lines = file.read().split('\n') lines = [x for x in lines if x and not x.startswith('#')] lines = [x.rstrip().lstrip() for x in lines] # get rid of fringe whitespaces module_defs = [] for line in lines: if line.startswith('['): # This marks the start of a new block module_defs.append({}) module_defs[-1]['type'] = line[1:-1].rstrip() if module_defs[-1]['type'] == 'convolutional': module_defs[-1]['batch_normalize'] = 0 else: key, value = line.split("=") value = value.strip() module_defs[-1][key.rstrip()] = value.strip() return module_defs