Open yaolinli opened 2 years ago
Noted. Will prepare the suggested one as well.
Noted. Will prepare the suggested one as well.
I have found the related preprocessing codes in the ./prepro and can get the correct data files by modifying them. Thanks!
Noted. Will prepare the suggested one as well.
I have found the related preprocessing codes in the ./prepro and can get the correct data files by modifying them. Thanks!
Hi, would you please provide some insights on how you get the correct data files?
Take training set as an example, the following files should be prepared:
I refer to the ./prepro/create_image_frame_tsv.py
to create the train_32frames.img.tsv and the caption-related files can be prepared imitating the file format in MSRVTT dataset.
Besides, we also should generate the corresponding *.lineidx for the above tsv files, it can be generated by:
def generate_lineidx_file(filein, idxout):
idxout_tmp = idxout + '.tmp'
with open(filein, 'r') as tsvin, open(idxout_tmp,'w') as tsvout:
fsize = os.fstat(tsvin.fileno()).st_size
fpos = 0
while fpos!=fsize:
tsvout.write(str(fpos)+"\n")
tsvin.readline()
fpos = tsvin.tell()
os.rename(idxout_tmp, idxout)
I follow “/prepro/extract youcook2 frms.sh" executes "./prepro/extract_ frames.py", but it doesn't seem to work, and the following results are obtained:
python ./prepro/extract_frames.py \ --video_root_dir ./datasets/MSRVTT-v2/videos \ --save_dir ./datasets/MSRVTT-v2/ \ --video_info_tsv ./datasets/MSRVTT-v2/val.img.tsv \ --num_frames 32 \ 0it [00:00, ?it/s]`
Is my operation incorrect? Thank you very much ~
I follow “/prepro/extract youcook2 frms.sh" executes "./prepro/extract_ frames.py", but it doesn't seem to work, and the following results are obtained:
python ./prepro/extract_frames.py --video_root_dir ./datasets/MSRVTT-v2/videos --save_dir ./datasets/MSRVTT-v2/ --video_info_tsv ./datasets/MSRVTT-v2/val.img.tsv --num_frames 32 0it [00:00, ?it/s]`
Is my operation incorrect? Thank you very much ~
Hi, I see there are several dockers of different tags in [https://hub.docker.com/r/linjieli222/videocap_torch1.7/tags](), could you please tell me which one should I choose? Thanks a lot!
I follow “/prepro/extract youcook2 frms.sh" executes "./prepro/extract_ frames.py", but it doesn't seem to work, and the following results are obtained:
python ./prepro/extract_frames.py --video_root_dir ./datasets/MSRVTT-v2/videos --save_dir ./datasets/MSRVTT-v2/ --video_info_tsv ./datasets/MSRVTT-v2/val.img.tsv --num_frames 32 0it [00:00, ?it/s]`
Is my operation incorrect? Thank you very much ~
Hi, I see there are several dockers of different tags in https://hub.docker.com/r/linjieli222/videocap_torch1.7/tags, could you please tell me which one should I choose? Thanks a lot!
The image "fairscale" is my choice.
Hi! Excuse me, could you please tell me how you get the _train32frames.img.tsv? I prepared the annotations with
bash scripts/download_annotations.sh
But when I run the code, it says that:
No such file or directory: 'datasets/MSRVTT-v2/frame_tsv/train_32frames.img.tsv'
I don't know why the _train32frames.img.tsv is not included in the annotations zip file of MSRVTT. Thank you!
I follow “/prepro/extract youcook2 frms.sh" executes "./prepro/extract_ frames.py", but it doesn't seem to work, and the following results are obtained:
python ./prepro/extract_frames.py --video_root_dir ./datasets/MSRVTT-v2/videos --save_dir ./datasets/MSRVTT-v2/ --video_info_tsv ./datasets/MSRVTT-v2/val.img.tsv --num_frames 32 0it [00:00, ?it/s]`
Is my operation incorrect? Thank you very much ~
Hi, I see there are several dockers of different tags in https://hub.docker.com/r/linjieli222/videocap_torch1.7/tags, could you please tell me which one should I choose? Thanks a lot!
The image "fairscale" is my choice.
Hi! Did you run the code successfully? Excuse me, could you please tell me how you get the _train32frames.img.tsv? I prepared the annotations with:
bash scripts/download_annotations.sh
But when I run the code, it says that:
No such file or directory: 'datasets/MSRVTT-v2/frame_tsv/train_32frames.img.tsv'
I don't know why the _train32frames.img.tsv is not included in the annotations zip file of MSRVTT. Thank you!
I follow “/prepro/extract youcook2 frms.sh" executes "./prepro/extract_ frames.py", but it doesn't seem to work, and the following results are obtained:
python ./prepro/extract_frames.py --video_root_dir ./datasets/MSRVTT-v2/videos --save_dir ./datasets/MSRVTT-v2/ --video_info_tsv ./datasets/MSRVTT-v2/val.img.tsv --num_frames 32 0it [00:00, ?it/s]`
Is my operation incorrect? Thank you very much ~
Hi, I see there are several dockers of different tags in hub.docker.com/r/linjieli222/videocap_torch1.7/tags, could you please tell me which one should I choose? Thanks a lot!
The image "fairscale" is my choice.
Hi! Did you run the code successfully? Excuse me, could you please tell me how you get the _train32frames.img.tsv? I prepared the annotations with:
bash scripts/download_annotations.sh
But when I run the code, it says that:No such file or directory: 'datasets/MSRVTT-v2/frame_tsv/train_32frames.img.tsv'
I don't know why the _train32frames.img.tsv is not included in the annotations zip file of MSRVTT. Thank you!
Hi! Have you solved this problem? I have encountered the same. Now I think maybe should download the dataset and run create_image_frame_tsv.py
? Could you give me some advice? Thanks a lot.
Hi, I am getting this file not found error "datasets/MSRVTT-v2/frame_tsv/val_128frames_img_size256.img.tsv" while running evaluation can anyone help me out regarding how to generate required tsv file it would be really helpful, I went through repo instruction but this file are not generated it seems.
Some advice would be really helpful.
Thanks a lot
I follow “/prepro/extract youcook2 frms.sh" executes "./prepro/extract_ frames.py", but it doesn't seem to work, and the following results are obtained:
python ./prepro/extract_frames.py --video_root_dir ./datasets/MSRVTT-v2/videos --save_dir ./datasets/MSRVTT-v2/ --video_info_tsv ./datasets/MSRVTT-v2/val.img.tsv --num_frames 32 0it [00:00, ?it/s]`
Is my operation incorrect? Thank you very much ~
Hi,I meet the same problem.I have solved it by annotating the code in line 124
raw_video_info = load_tsv_to_mem(video_info_tsv)
videoFiles = []
for _, line_item in enumerate(raw_video_info):
input_file = line_item[0]
#####input_file = input_file.replace('datasets','_datasets')
if os.path.isfile(input_file):
videoFiles.append(input_file)
Besides, how can we prepare the data files like .label.tsv / .caption.tsv / *.caption.linelist.tsv to train SwinBert on our own dataset? Thank you very much ~