Metadata-Version: 2.1
Name: vdataset
Version: 0.0.2
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
        * torchvision
        * 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") |
        | frames_resize | tuple/None | False |        Resize the frames (Also this can be done on using transform too) |
        
        ## Usage
        
        ```python
        from torch.utils.data import DataLoader
        from torchvision import transforms
        
        transforms = transforms.Compose([transforms.Resize((100, 100)),
                                               transforms.ToTensor()])
        
        vdataset = VDataset(csv_file='path-to-csv-file.csv', root_dir='path-to-video-dir', transform=transforms)
        dataloader = DataLoader(vdataset, batch_size=64) # use in 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
