Does the uvo_process.py file lack preprocess for val dataset?

[mao-code]

I noticed that both the train and val set in UVO dataset have "reorg" in the config file.
However, I only found the train path in the uvo_preprocess.py.

I have modified the code. If it is the case, please notify me. I will send a pull request.

import cv2 
import json 
import os
from pycocotools import mask as mask_utils
import numpy as np
from tqdm import tqdm

# train
# json_path = '/home/default/ephemeral_drive/Tryon/AnyDoor/training_data/UVO/UVO_sparse_train_video_with_interpolation.json'
# output_path = "/home/default/ephemeral_drive/Tryon/AnyDoor/training_data/UVO/UVO_sparse_train_video_with_interpolation_reorg.json"

# val
json_path = '/home/default/ephemeral_drive/Tryon/AnyDoor/training_data/UVO/UVO_sparse_val_video_with_interpolation.json'
output_path = "/home/default/ephemeral_drive/Tryon/AnyDoor/training_data/UVO/UVO_sparse_val_video_interpolation_reorg.json"

with open(json_path, 'r') as fcc_file:
    data = json.load(fcc_file)

info = data['info']
videos = data['videos']
print(len(videos))


uvo_dict = {}
for video in tqdm(videos):
    vid = video['id']
    file_names = video['file_names']
    uvo_dict[vid] = file_names


with open(output_path,"w") as f:
    json.dump(uvo_dict,f)
    print('finish')