if __name__ == '__main__':
data_path = '../dataset/'
base_dir = '../dataset/WIDER_train/'
filename = '../dataset/wider_face_train.txt'
min_face_size = 20
scale_factor = 0.79
thresh = 0.6
# 获取人脸的box图片数据
print('开始生成bbox图像数据')
crop_24_box_image(data_path, filename, min_face_size, scale_factor, thresh)
# 获取人脸关键点的数据
print('开始生成landmark图像数据')
# 获取lfw negbox，关键点
lfw_neg_path = os.path.join(data_path, 'trainImageList.txt')
data_list = get_landmark_from_lfw_neg(lfw_neg_path, data_path)
# 获取celeba，关键点
# celeba_data_list = get_landmark_from_celeba(data_path)
# data_list.extend(celeba_data_list)
crop_landmark_image(data_path, data_list, 24, argument=True)
# 合并数据列表
print('开始合成数据列表')
combine_data_list(os.path.join(data_path, '24'))
# 合并图像数据
print('开始合成图像文件')
convert_data(os.path.join(data_path, '24'), os.path.join(data_path, '24', 'all_data'))
# 删除旧数据
print('开始删除就得图像文件')
delete_old_img(data_path, 24)
chars = image.split('.')[0].split('_')[1]
for c in chars:
keys = label_dict.keys()
if c not in keys:
label_dict[c] = len(label_dict) + 1
labels = [label_dict.get(c) for c in chars]
label = ''
for l in labels:
label += '%s,' % l
label = label[:-1]
if i % 20 == 0:
f_test.write("%s %s\n" % (image_path.replace('\\', '/'), label))
else:
f_train.write("%s %s\n" % (image_path.replace('\\', '/'), label))
f_label.write("%s\n" % str(label_dict).replace("'", '"'))
f_train.close()
f_test.close()
f_label.close()
shuffle_data(train_list_path)
print('create data list done!')
if __name__ == '__main__':
create('dataset/images', config.train_list, config.test_list,
config.dict_path)
convert_data(config.train_list, config.train_prefix)
convert_data(config.test_list, config.test_prefix)