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cfg.py
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cfg.py
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def parse_cfg(cfgfile):
blocks = []
fp = open(cfgfile, 'r')
block = None
line = fp.readline()
while line != '':
line = line.rstrip()
if line == '' or line[0] == '#':
line = fp.readline()
continue
elif line[0] == '[':
if block:
blocks.append(block)
block = dict()
block['type'] = line.lstrip('[').rstrip(']')
# set default value
if block['type'] in ['convolutional', 'deconvolutional']:
block['batch_normalize'] = 0
else:
key,value = line.split('=')
key = key.strip()
if key == 'type':
key = '_type'
value = value.strip()
block[key] = value
line = fp.readline()
if block:
blocks.append(block)
fp.close()
return blocks
def print_cfg(blocks, width, height, channels):
print('layer filters size input output');
prev_width = width
prev_height = height
prev_filters = channels
out_filters =[]
out_widths =[]
out_heights =[]
ind = -1
for block in blocks:
ind = ind + 1
if block['type'] in ['convolutional', 'deconvolutional']:
filters = int(block['filters'])
kernel_size = int(block['size'])
stride = int(block['stride'])
is_pad = int(block['pad'])
pad = int((kernel_size-1)/2) if is_pad else 0
if block['type'] == 'convolutional':
width = int((prev_width + 2 * pad - kernel_size) / stride + 1)
height = int((prev_height + 2 * pad - kernel_size) / stride + 1)
print('%5d %-6s %4d %d x %d / %d %3d x %3d x%4d -> %3d x %3d x%4d' % (ind, 'conv', filters, kernel_size, kernel_size, stride, prev_width, prev_height, prev_filters, width, height, filters))
elif block['type'] == 'deconvolutional':
width = int((prev_width - 1) * stride - 2 * pad + kernel_size)
height = int((prev_height - 1) * stride - 2 * pad + kernel_size)
print('%5d %-6s %4d %d x %d / %d %3d x %3d x%4d -> %3d x %3d x%4d' % (ind, 'deconv', filters, kernel_size, kernel_size, stride, prev_width, prev_height, prev_filters, width, height, filters))
prev_width = width
prev_height = height
prev_filters = filters
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'maxpool':
pool_size = int(block['size'])
stride = int(block['stride'])
width = int(prev_width/stride)
height = int(prev_height/stride)
print('%5d %-6s %-2dx%2d / %d %3d x %3d x%4d -> %3d x %3d x%4d' % (ind, 'max', pool_size, pool_size, stride, prev_width, prev_height, prev_filters, width, height, filters))
prev_width = width
prev_height = height
prev_filters = filters
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'avgpool':
width = 1
height = 1
print('%5d %-6s %3d x %3d x%4d -> %3d' % (ind, 'avg', prev_width, prev_height, prev_filters, prev_filters))
prev_width = width
prev_height = height
prev_filters = filters
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'softmax':
print('%5d %-6s -> %3d' % (ind, 'softmax', prev_filters))
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'cost':
print('%5d %-6s -> %3d' % (ind, 'cost', prev_filters))
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'reorg':
stride = int(block['stride'])
filters = stride * stride * prev_filters
width = int(prev_width/stride)
height = int(prev_height/stride)
print('%5d %-6s / %d %3d x %3d x%4d -> %3d x %3d x%4d' % (ind, 'reorg', stride, prev_width, prev_height, prev_filters, width, height, filters))
prev_width = width
prev_height = height
prev_filters = filters
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'upsample':
stride = int(block['stride'])
filters = prev_filters
width = prev_width*stride
height = prev_height*stride
print('%5d %-6s * %d %3d x %3d x%4d -> %3d x %3d x%4d' % (ind, 'upsample', stride, prev_width, prev_height, prev_filters, width, height, filters))
prev_width = width
prev_height = height
prev_filters = filters
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'route':
layers = block['layers'].split(',')
layers = [int(i) if int(i) > 0 else int(i)+ind for i in layers]
layerlen = len(layers)
assert(layerlen >= 1)
prev_width = out_widths[layers[0]]
prev_height = out_heights[layers[0]]
prev_filters = out_filters[layers[0]]
prtstr = ('%5d %-6s %d' % (ind, 'route', layers[0]))
if layerlen > 1:
for i in range(1, layerlen):
prtstr += (' %d' % layers[i])
assert (prev_width == out_widths[layers[i]])
assert (prev_height == out_heights[layers[i]])
prev_filters += out_filters[layers[i]]
print(prtstr)
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'outlayer':
print('%5d %-6s' % (ind, block['type']))
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'shortcut':
from_id = int(block['from'])
from_id = from_id if from_id > 0 else from_id+ind
print('%5d %-6s %d' % (ind, 'shortcut', from_id))
prev_width = out_widths[from_id]
prev_height = out_heights[from_id]
prev_filters = out_filters[from_id]
out_widths.append(prev_width)
out_heights.append(prev_height)
out_filters.append(prev_filters)
elif block['type'] == 'connected':
filters = int(block['output'])
print('%5d %-6s %d -> %3d' % (ind, 'connected', prev_filters, filters))
prev_filters = filters
out_widths.append(1)
out_heights.append(1)
out_filters.append(prev_filters)
else:
print('unknown type %s' % (block['type']))
if __name__ == '__main__':
import sys
blocks = parse_cfg('cfg/yolov3.cfg')
if len(sys.argv) == 2:
blocks = parse_cfg(sys.argv[1])
print_cfg(blocks)