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Clothing1M

This project preprocess the Clothing 1M Dataset and gives a classwise directory structure. The raw dataset can be obtained by following steps on official repository

Dataset details

Check using find test/ -maxdepth 2 -type f | wc -l in terminal

  • Number of nosiy train images - 1000000
  • Number of clean train images - 47570
  • Number of val images - 10526
  • Number of test images - 14313

Below is the final directory structure:

The images in the directroy for each partition of the dataset are arranged in the directory with q00xx where xx is the class number from 0-13.

└── Clothing1M
    ├── clean_train
    |   ├── q0000
    |   ├── q0001
    |   └── ...
    |   └── q0013
    |
    ├── noisy_train
    |   ├── q0000
    |   ├── q0001
    |   └── ...
    |   └── q0013
    |
    ├── val
    |   ├── q0000
    |   ├── q0001
    |   └── ...
    |   └── q0013
    |
    ├── test
    |   ├── q0000
    |   ├── q0001
    |   └── ...
    |   └── q0013
    |
    ├── xxxx
    ├── xxxx
    ├── xxxx
    ├── xxxx
    ├── xxxx
    └── creat_dataset.sh
    └── helper.py
    └── Readme.md
    └── Citation.cff
    └── LICENSE

Instructions

  1. Get access to dataset following steps on official repository

  2. Clone this repository.

    git clone https://github.com/sangamesh-kodge/Clothing1M.git
  3. Download the dataset from the download link obtained in step 1 in the cloned repository from step 2. (Or move data after download. )

  4. Unzip files in images/ directory using tar -xf <file_name.tar>. Additionally unzip file in the root directory using unzip <file_name.zip>. (See the commented lines 20-29 in create_dataset.sh). At this stage the cloned repository should have images/ directory containing raw images and files with the label information for each image.

  5. Run the following command in your terminal/command contraining the cloned repository

    sh create_dataset.sh

Conclusion

The project preprocess Clothing1M Dataset and gives a classwise directory structure.

Citation

Kindly cite the repository if you use the code. Thanks!

APA

Kodge, S. (2024). Clothing1M [Computer software]. https://github.com/sangamesh-kodge/Clothing1M

Bibtex

@software{Kodge_Clothing1M_2024,
author = {Kodge, Sangamesh},
month = feb,
title = {{Clothing1M}},
url = {https://github.com/sangamesh-kodge/Clothing1M},
year = {2024}
}

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