Datasets:
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---
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")
``` |