43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import numpy as np
|
|
|
|
|
|
def parse_model_cfg(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
|
|
mdefs = [] # module definitions
|
|
for line in lines:
|
|
if line.startswith('['): # This marks the start of a new block
|
|
mdefs.append({})
|
|
mdefs[-1]['type'] = line[1:-1].rstrip()
|
|
if mdefs[-1]['type'] == 'convolutional':
|
|
mdefs[-1]['batch_normalize'] = 0 # pre-populate with zeros (may be overwritten later)
|
|
else:
|
|
key, val = line.split("=")
|
|
key = key.rstrip()
|
|
|
|
if 'anchors' in key:
|
|
mdefs[-1][key] = np.array([float(x) for x in val.split(',')]).reshape((-1, 2)) # np anchors
|
|
else:
|
|
mdefs[-1][key] = val.strip()
|
|
|
|
return mdefs
|
|
|
|
|
|
def parse_data_cfg(path):
|
|
# Parses the data configuration file
|
|
options = dict()
|
|
with open(path, 'r') as fp:
|
|
lines = fp.readlines()
|
|
|
|
for line in lines:
|
|
line = line.strip()
|
|
if line == '' or line.startswith('#'):
|
|
continue
|
|
key, val = line.split('=')
|
|
options[key.strip()] = val.strip()
|
|
|
|
return options
|