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get68pointsfor300W.py
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get68pointsfor300W.py
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import os
import math
import numpy as np
num_kpts = 68
def get_kpts(file_path):
kpts = []
with open(file_path, 'r') as fr:
ln = fr.readline()
while not ln.startswith('n_points'):
ln = fr.readline()
num_pts = ln.split(':')[1].strip()
# checking for the number of keypoints
if float(num_pts) != num_kpts:
print("encountered file with less than %f keypoints in %s" %(num_kpts, file_pts))
return None
# skipping the line with '{'
ln = fr.readline()
ln = fr.readline()
while not ln.startswith('}'):
vals = ln.strip().split(' ')[:2]
vals = list(map(np.float32, vals))
kpts.append(vals)
ln = fr.readline()
return kpts
def get_Infomation_list(root_dir, info_dir, lines):
info_path = os.path.join(root_dir, info_dir)
files = os.listdir(info_path)
points_files = [i for i in files if i.endswith('.pts')]
for index, pf in enumerate(points_files):
file_path = os.path.join(info_path, pf)
kpts = get_kpts(file_path)
if kpts is None:
continue
# ibug dir exist a image that has a space in name
image_file = pf.split('.')[0] + '.jpg'
image_path = os.path.join(info_path, image_file)
if not os.path.isfile(image_path):
image_file = pf.split('.')[0] + '.png'
image_path = os.path.join(info_path, image_file)
GT_points = np.asarray(kpts)
# crop face box
x_min, y_min = GT_points.min(0)
x_max, y_max = GT_points.max(0)
w, h = x_max-x_min, y_max-y_min
w = h = min(w, h)
ratio = 0.1
x_new = x_min - w*ratio
y_new = y_min - h*ratio
w_new = w*(1 + 2*ratio)
h_new = h*(1 + 2*ratio)
x1 = x_new
x2 = x_new+w_new
y1 = y_new
y2 = y_new+h_new
line = []
for i in range(num_kpts):
line.append(str(kpts[i][0]))
line.append(str(kpts[i][1]))
line.append(str(int(x1)))
line.append(str(int(y1)))
line.append(str(int(x2)))
line.append(str(int(y2)))
for i in range(6):
line.append(str(0))
line.append(os.path.join(info_dir, image_file))
assert(len(line) == 147)
lines.append(line)
def main(root_dir, fw_path_train, fw_path_test):
train_lines = []
train_dirs = ['lfpw/trainset', 'ibug', 'afw', 'helen/trainset']
for train_dir in train_dirs:
get_Infomation_list(root_dir+'/raw', train_dir, train_lines)
test_lines = []
test_dirs = ['lfpw/testset', 'helen/testset']
for test_dir in test_dirs:
get_Infomation_list(root_dir+'/raw', test_dir, test_lines)
with open(fw_path_train, 'w') as fw:
for i, line in enumerate(train_lines):
#print(line)
for j in range(len(line)):
fw.write(line[j]+' ')
fw.write('\n')
with open(fw_path_test, 'w') as fw:
for i, line in enumerate(test_lines):
for j in range(len(line)):
fw.write(line[j]+' ')
fw.write('\n')
if __name__ == '__main__':
root_dir = os.path.dirname(os.path.realpath(__file__))
print(root_dir)
fw_path_train = os.path.join(root_dir, 'annotations/list_68pt_rect_attr_train_test/list_68pt_rect_attr_train.txt')
fw_path_test = os.path.join(root_dir, 'annotations/list_68pt_rect_attr_train_test/list_68pt_rect_attr_test.txt')
main(root_dir, fw_path_train, fw_path_test)