README.md

---
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
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    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
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    num_examples: 10000
  - name: test
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    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.