vdataset 0.0.3

Load video datasets to PyTorch DataLoader

VDataset

Description

Load video datasets to PyTorch DataLoader. (Custom Video Data set for PyTorch DataLoader)
VDataset can be use to load 20BN-Jester dataset to the PyTorch DataLoader

Required Libraries

• torch
• Pillow
• pandas

Arguments for constructor

Argument	Type	Required	Description
csv_file	str	True	Path to .csv file
root_dir	str	True	Root Directory of the video dataset
file_format	str	False	File type of the frame images (ex: .jpg, .jpeg, .png)
id_col_name	str	False	Column name, where id/name of the video on the .csv file
label_col_name	str	False	Column name, where label is on the .csv file
frames_limit_mode	str/None	False	Mode of the frame count detection ("manual", "csv" or else it auto detects all the frames available)
frames_limit	int	False	Number of frames in a video (required if frames_count_mode set to "manual")
frames_limit_col_name	str	False	Column name, where label is on the .csv file (required if frames_count_mode set to "csv")
video_transforms	tuple/None	False	Video Transforms (Refere: https://github.com/hassony2/torch_videovision)

Usage

from vdataset import VDataset 

from torch.utils.data import DataLoader

from torchvideotransforms.volume_transforms import ClipToTensor # https://github.com/hassony2/torch_videovision
from torchvideotransforms import video_transforms, volume_transforms # https://github.com/hassony2/torch_videovision

video_transform_list = [video_transforms.RandomRotation(30),
            video_transforms.Resize((100, 100)),
            volume_transforms.ClipToTensor()]
video_transforms = video_transforms.Compose(video_transform_list)

dataset = VDataset(csv_file='/path-to-csv/csv_file.csv', root_dir='/path-to-root/', video_transforms=video_transforms)

dataloader = DataLoader(dataset, batch_size=64, shuffle=True, num_workers=2, pin_memory=True)
print(dataloader)

for image, label in dataloader: # Do what do you want in dataset
    print(image, label)
    break