Metadata-Version: 2.1
Name: vdataset
Version: 0.0.3
Summary: Load video datasets to PyTorch DataLoader
Home-page: https://github.com/nzx9/VDataset
Author: Navindu Dananga
Author-email: navindum@protonmail.com
License: MIT
Description: # VDataset
        
        ## Description
        
        Load video datasets to PyTorch DataLoader. (Custom Video Data set for PyTorch DataLoader)
        </br>
        **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
        
        ```python
        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
        
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
