data_path = '../dataset/'
base_dir = '../dataset/WIDER_train/'
filename = '../dataset/wider_face_train.txt'
min_face_size = 20
scale_factor = 0.79
p_thresh = 0.6
r_thresh = 0.7
# 获取人脸的box图片数据
print('开始生成bbox图像数据')
crop_48_box_image(data_path, filename, min_face_size, scale_factor,
p_thresh, r_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, 48, 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, '48'))
# 合并图像数据
print('开始合成图像文件')
convert_data(os.path.join(data_path, '48'),
os.path.join(data_path, '48', 'all_data'))
# 删除旧数据
print('开始删除就得图像文件')
delete_old_img(data_path, 48)
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)
print('%s 个图片已处理，pos：%s part: %s neg:%s' % (idx, p_idx, d_idx, n_idx))
f1.close()
f2.close()
f3.close()
if __name__ == '__main__':
data_path = '../dataset/'
# 获取人脸的box图片数据
print('开始生成bbox图像数据')
crop_12_box_image(data_path)
# 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, 12, 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, '12'))
# 合并图像数据
print('开始合成图像文件')
convert_data(os.path.join(data_path, '12'),
os.path.join(data_path, '12', 'all_data'))
# 删除旧数据
print('开始删除旧的图像文件')
delete_old_img(data_path, 12)