File size: 7,406 Bytes
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import os
import cv2
from PIL import Image
# parse revos format
# # mask_dict = '/mnt/bn/xiangtai-training-data-video/dataset/video_vlm/video_res/revos/mask_dict.json'
# exp_dict = '/mnt/bn/xiangtai-training-data-video/dataset/video_vlm/video_res/revos/meta_expressions_valid_.json'
# #
# # with open(mask_dict, 'r') as f:
# # mask_dict = json.load(f)
# #
# # print(mask_dict.keys())
# # keys = list(mask_dict.keys())
# # print(mask_dict[keys[0]])
#
# with open(exp_dict, 'r') as f:
# exp_dict = json.load(f)
#
# print(exp_dict['videos']['UVO/all/-fbscFfkh4M']['expressions'])
# print(exp_dict['videos']['UVO/all/-fbscFfkh4M']['vid_id'])
# print(exp_dict['videos']['UVO/all/-fbscFfkh4M']['height'])
# print(exp_dict['videos']['UVO/all/-fbscFfkh4M']['width'])
# print(exp_dict['videos']['UVO/all/-fbscFfkh4M']['frames'])
# #{'exp': 'the person who is wearing a white shirt and blue jeans.', 'obj_id': [0], 'anno_id': [3003019], 'type_id': 0}
#--------------------------------------------------------------------------------------
mini = False
checked_folder = './manual_check_visualization_1028/checked/'
short_anno_folder = './manual_check_visualization_1028/short_annotation/'
save_dir = './ref_SAV/'
auto_annotation_folders = [
'./whole_pesudo_cap_v3/sav_054_step6/',
'./whole_pesudo_cap_v3/sav_053_step6/'
]
json_files = []
for auto_annotation_folder in auto_annotation_folders:
file_names = os.listdir(auto_annotation_folder)
file_names = [os.path.join(auto_annotation_folder, name) for name in file_names]
json_files.extend(file_names)
auto_json_datas = []
for file_path in json_files:
with open(file_path, 'r') as f:
_data = json.load(f)
auto_json_datas.extend(_data)
auto_json_dict = {}
for _item in auto_json_datas:
video_id = _item['video_id']
obj_id = _item['obj_id']
if video_id not in auto_json_dict.keys():
auto_json_dict[video_id] = {}
auto_json_dict[video_id][obj_id] = _item
def parse_file_name(name):
print(name)
name = name[:-4]
name = name.split('_')
folder_id = name[1]
split_id = name[-1]
return folder_id, split_id
def parse_txt(path):
with open(path, 'r') as f:
data = f.read()
data = data.split('\n')
data_ = []
for line in data:
line = line.strip()
if line == '':
pass
else:
data_.append(line)
return data_
def parse_txt_short_anno(path):
with open(path, 'r') as f:
data = f.read()
data = data.split('\n')
short_cap = ''
num = 0
for _item in data:
if 'The' in _item or 'Object' in _item or 'object' in _item or 'a' in _item:
short_cap = _item
num += 1
assert num == 1, data
short_cap = short_cap.strip()
if short_cap[-1] != '.':
short_cap = short_cap + '.'
return short_cap
def get_video_frames(video_path):
cap = cv2.VideoCapture(video_path)
if not cap.isOpened():
print("Error: Cannot open video file.")
return
frames = []
frame_id = 0
while True:
ret, frame = cap.read()
if not ret:
break
frames.append(frame)
frame_id += 1
cap.release()
return frames
file_names = os.listdir(checked_folder)
checked_number = 0
meta_infos = []
for file_name in file_names:
checked_path = os.path.join(checked_folder, file_name)
folder_id, split_id = parse_file_name(file_name)
checked_object_ids = parse_txt(checked_path)
for _object_id in checked_object_ids:
_info = {'id': _object_id, 'folder_id': folder_id, 'split_id': split_id}
meta_infos.append(_info)
if mini:
meta_infos = meta_infos[:50]
short_file_names = os.listdir(short_anno_folder)
short_meta_infos = []
for file_name in short_file_names:
short_cap = parse_txt_short_anno(os.path.join(short_anno_folder, file_name))
_object_id = file_name.replace('.txt', '')
_info = {'id': _object_id, 'folder_id': '054', 'short_cap': short_cap}
meta_infos.append(_info)
if mini:
meta_infos = meta_infos[:100]
ret_mask_dict = {}
ret_exp_dict = {}
if not os.path.exists(save_dir):
os.mkdir(save_dir)
if not os.path.exists(os.path.join(save_dir, 'videos')):
os.mkdir(os.path.join(save_dir, 'videos'))
for anno_id, _info in enumerate(meta_infos):
print(anno_id)
_object_id = _info['id']
folder_id = _info['folder_id']
# split_id = _info['split_id']
video_id, object_id = _object_id.split('_obj')
object_id = int(object_id.strip())
# prepare exp
if 'short_cap' in _info.keys():
# print("Short manual anno.")
# print(_info['short_cap'])
object_exp = _info['short_cap']
_exp_dict = {
'exp': object_exp,
'obj_id': [object_id],
'anno_id': [10000 + anno_id],
'type_id': 1,
}
else:
object_exp = auto_json_dict[video_id][object_id]['final_caption']
_exp_dict = {
'exp': object_exp,
'obj_id': [object_id],
'anno_id': [10000 + anno_id],
'type_id': 0,
}
# prepare mask
mask_anno_path = \
f"/mnt/bn/xiangtai-training-data-video/dataset/segmentation_datasets/sam_v_full/sav_{folder_id}/sav_train/sav_{folder_id}/{video_id}_manual.json"
with open(mask_anno_path, 'r') as f:
mask_anno_data = json.load(f)
masklents = mask_anno_data['masklet']
object_masklent = [_all_objects[object_id] for _all_objects in masklents]
# save and append
ret_mask_dict[str(10000+anno_id)] = object_masklent
if video_id not in ret_exp_dict.keys():
if not os.path.exists(os.path.join(save_dir, f"videos/{video_id}")):
os.mkdir(os.path.join(save_dir, f"videos/{video_id}"))
# prepare images
video_path = \
f"/mnt/bn/xiangtai-training-data-video/dataset/segmentation_datasets/sam_v_full/sav_{folder_id}/sav_train/sav_{folder_id}/{video_id}.mp4"
video_frames = get_video_frames(video_path)
video_valid = False
if os.path.exists(os.path.join(save_dir, f"videos/{video_id}/")):
video_valid = True
video_frames = video_frames[::4]
video_frames_ = []
video_frames_names = []
frames_ids = []
for i_frame, frame in enumerate(video_frames):
frame = frame[:, :, ::-1]
frame_image = Image.fromarray(frame).convert('RGB')
frames_ids.append(str(100000 + i_frame * 4))
video_frames_names.append(f"videos/{video_id}/{100000 + i_frame * 4}.jpg")
video_frames_.append(frame_image)
width, height = video_frames_[0].size
ret_exp_dict[video_id] = {
'expressions': {},
'vid_id': video_id,
'height': height,
'width': width,
'frames': frames_ids,
}
for _video_frame_name, _frame_image in zip(video_frames_names, video_frames_):
_save_pth = os.path.join(save_dir, _video_frame_name)
_frame_image.save(_save_pth)
ret_exp_dict[video_id]['expressions'][str(object_id)] = _exp_dict
with open(os.path.join(save_dir, 'meta_expressions_valid.json'), 'w') as f:
json.dump({'videos': ret_exp_dict}, f)
with open(os.path.join(save_dir, 'mask_dict.json'), 'w') as f:
json.dump(ret_mask_dict, f)
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