metadata

license: cc-by-nc-4.0
task_categories:
  - object-detection
tags:
  - shagai
size_categories:
  - n<1K
dataset_info:
  features:
    - name: image
      dtype: image
    - name: objects
      struct:
        - name: bbox
          sequence:
            sequence: int64
        - name: categories
          sequence: int64
  splits:
    - name: train
      num_bytes: 4647508
      num_examples: 644
    - name: validation
      num_bytes: 2000239
      num_examples: 277
  download_size: 6398185
  dataset_size: 6647747
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*

Shagai

Object detection dataset for identifying the shape of shagai (ankle of a sheep).

Checkout our original Github Repo.

Dataset info

Dataset contains total of 921 images with 3680 objects. Each image has exactly 4 objects.

Categories:

horse
camel
sheep
goat

Splits:

Training: 644 images, 2573 objects, {0: 644, 1: 642, 2: 668, 3: 619} (obj. class)
Validation: 277 images, 1107 objects, {0: 302, 1: 245, 2: 281, 3: 279} (obj. class)

Credits

This dataset was created with contributions from Amarsaikhan Batjargal, Bandikhuu Baasanjav, and Bilguun Ochirbat, students of the National University of Mongolia.

Citation

@misc{shagai2018,
  author = {Ochirbat, Bilguun and Batjargal, Amarsaikhan and Baasanjav, Bandikhuu},
  title = {{Detect the shape of shagai using RetinaNet}},
  howpublished = {\url{https://github.com/bilguun0203/ankle-bone-recognition}},
  year = {2018},
  month = {July}
}