0e3dc773bfe1cc74e3c72192c5dc6fbf63864d08,train.py,,,#,132

Before Change

    your_objs_info_list = your_data.get_joint_list()
    your_mask_list = your_data.get_mask()
    if len(your_imgs_file_list) != len(your_objs_info_list):
        raise Exception("number of customized images and annotations do not match")
    else:
        print("number of customized images {}".format(len(your_imgs_file_list)))

    // choice dataset for training

After Change

    folder_list = tl.files.load_folder_list(path="your_data")
    your_imgs_file_list, your_objs_info_list, your_mask_list = [], [], []
    for folder in folder_list:
        _imgs_file_list, _objs_info_list, _mask_list, _targets = \
            get_pose_data_list(os.path.join(folder, "images"), os.path.join(folder, "coco.json"))
        print(len(_imgs_file_list))
        your_imgs_file_list.extend(_imgs_file_list)
        your_objs_info_list.extend(your_objs_info_list)
        your_mask_list.extend(your_mask_list)

Instances