README.md

---
license: mit
size_categories:
- 10K<n<100K
task_categories:
- image-segmentation
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    path: data/train-*
  - split: test
    path: data/test-*
- config_name: default-tiny
  data_files:
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    path: default-tiny/train-*
  - split: test
    path: default-tiny/test-*
- config_name: human-plant
  data_files:
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    path: human-plant/train-*
  - split: test
    path: human-plant/test-*
- config_name: human-plant-tiny
  data_files:
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    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.

# Example loader

## Install Hugging Face datasets package

```sh
pip install datasets
```


## Download the dataset

```python
from datasets import load_dataset

dataset = load_dataset("Menchen/AgroSegNet","default") # Change "default" to "default-tiny" to preview and test

```

## Load the data

Images and masks are stored as PIL, for example:

```python

dataset["train"][1]["image"] # PIL image to rendered image

dataset["train"][1]["label"] # PIL image to mask

```