---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: image_id
    dtype: int64
  - name: image
    dtype: image
  - name: width
    dtype: int32
  - name: height
    dtype: int32
  - name: objects
    sequence:
    - name: id
      dtype: int64
    - name: area
      dtype: int64
    - name: bbox
      sequence: float32
      length: 4
    - name: category
      dtype:
        class_label:
          names:
            '0': metals_and_plastic
            '1': other
            '2': non_recyclable
            '3': glass
            '4': paper
            '5': bio
            '6': unknown
  splits:
  - name: train
    num_bytes: 14799255261.307
    num_examples: 3647
  - name: test
    num_bytes: 3009820376.0
    num_examples: 915
  download_size: 3002391644
  dataset_size: 17809075637.307
language:
- en
tags:
- climate
pretty_name: detect-waste
size_categories:
- 1K<n<10K
---

# Dataset Card for detect-waste

## Dataset Description

- **Homepage: https://github.com/wimlds-trojmiasto/detect-waste** 

### Dataset Summary

AI4Good project for detecting waste in environment. www.detectwaste.ml.

Our latest results were published in Waste Management journal in article titled Deep learning-based waste detection in natural and urban environments.

You can find more technical details in our technical report Waste detection in Pomerania: non-profit project for detecting waste in environment.

Did you know that we produce 300 million tons of plastic every year? And only the part of it is properly recycled.

The idea of detect waste project is to use Artificial Intelligence to detect plastic waste in the environment. Our solution is applicable for video and photography. Our goal is to use AI for Good.


### Supported Tasks and Leaderboards

Object Detection

### Languages

English

### Data Fields

https://github.com/wimlds-trojmiasto/detect-waste/tree/main/annotations

## Dataset Creation

The images are post processed to remove exif and reorient as required. Some images are labelled without the exif rotation in mind thus they're not rotated at all but have their exif metadata removed

### Personal and Sensitive Information

**BEWARE** This repository had been created by a third-party and is not affiliated in any way with the original detect-waste creators/

## Considerations for Using the Data

### Licensing Information

https://raw.githubusercontent.com/wimlds-trojmiasto/detect-waste/main/LICENSE