---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: class_id
    dtype:
      class_label:
        names:
          '0': verde_plastico
          '1': azul
          '2': negro_plastico
          '3': negro_carton
          '4': roja_plastico
          '5': carton
          '6': verde_carton
          '7': roja_eldulze
          '8': verde_plastico_oscuro
          '9': verde_cogollo
          '10': ilfres
  - name: bbox
    sequence: float64
  splits:
  - name: loads
    num_bytes: 285494082.0
    num_examples: 949
  download_size: 285535164
  dataset_size: 285494082.0
configs:
- config_name: default
  data_files:
  - split: loads
    path: data/loads-*
license: mit
task_categories:
- object-detection
size_categories:
- n<1K
tags:
- industry
---

The **IndustrialLateralLoads** dataset is divided into a single split: `loads`. This split contains the following:

- A folder with all the images: `imgs`
- A folder that includes for each image a `.txt` file that holds a single line with the bounding box annotation of the main load in the image: `annotations`

---

**Remark:** Each row in a `.txt` file follows this format:

`<class_name> <instance_id> <x_min> <y_min> <weight> <height>`,

where the field `<instance_id>` is not relevant in the currently published dataset.

---

### Install Hugging Face datasets package:
```sh
pip install datasets
```

### Download the dataset:
```python
from datasets import load_dataset
dataset = load_dataset("jjldo21/IndustrialLateralLoads")
```