README.md

metadata

license: mit
size_categories:
  - 10K<n<100K
task_categories:
  - image-segmentation
dataset_info:
  - config_name: default
    features:
      - name: image
        dtype: image
      - name: label
        dtype: image
    splits:
      - name: train
        num_bytes: 20529210440
        num_examples: 40000
      - name: test
        num_bytes: 5090296000
        num_examples: 10000
    download_size: 25684569380
    dataset_size: 25619506440
  - config_name: human-plant
    features:
      - name: image
        dtype: image
      - name: label
        dtype: image
    splits:
      - name: train
        num_bytes: 20529582920
        num_examples: 40000
      - name: test
        num_bytes: 5084631770
        num_examples: 10000
    download_size: 25675082023
    dataset_size: 25614214690
  - config_name: human-plant-tiny
    features:
      - name: image
        dtype: image
      - name: label
        dtype: image
    splits:
      - name: train
        num_bytes: 5117076360
        num_examples: 10000
      - name: test
        num_bytes: 1280707488.5
        num_examples: 2500
    download_size: 6400701649
    dataset_size: 6397783848.5
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
  - config_name: human-plant
    data_files:
      - split: train
        path: human-plant/train-*
      - split: test
        path: human-plant/test-*
  - config_name: human-plant-tiny
    data_files:
      - split: train
        path: human-plant-tiny/train-*
      - split: test
        path: human-plant-tiny/test-*

AgroSegNet

This dataset comprises synthetic images captured from a top-down perspective, featuring two distinct annotations: one for direct sunlight and another for human and plant segmentation.