metadata

license: cc-by-nd-4.0
task_categories:
  - image-classification
language:
  - en
tags:
  - code
dataset_info:
  features:
    - name: image_id
      dtype: int32
    - name: image
      dtype: image
    - name: annotations
      dtype: string
  splits:
    - name: train
      num_bytes: 608467996
      num_examples: 100
  download_size: 607803398
  dataset_size: 608467996

Outdoor Garbage Dataset

The dataset consisting of garbage cans of various capacities and types. Best to train a neural network to monitor the timely removal of garbage and organize the logistics of vehicles for garbage collection. Dataset is useful for the recommendation systems, optimization and automization the work of coomunity services, smart city.

Get the dataset

This is just an example of the data

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Content

Dataset includes 10 000 images of trash cans:

in different times of day
in different weather conditions

Types of garbage cans capacity

is_full - at least one of the trash cans shown in the photo is completely full. This type includes filled to the top, overflown cans.
is_empty - garbage cans have free space, it could be half full or completely empty.
is_scattered - the tag is added with is_empty or is_full. The tag means that the garbage (volumetric garbage bags, or building waste, but not single elements) is scattered nearby.

Data Format

Each image from img folder is accompanied by an XML-annotation in the annotations.xml file indicating the labeled types of garbage cans capacities for each image in the dataset.

Example of XML file structure

TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets

TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets

keywords: object detection dataset, garbage detection, garbage detection, computer vision dataset, cardboard, glass, metal, paper, plastic, trash, garbage sorter, intelligent garbage, image recognition, urban management, smart city dataset, smart cities development, urban computing, image dataset, image-to-image dataset, object detection, images dataset, image classification, pictures, photo