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46,695 Images – Annotated Household Waste Dataset for Object Detection
household waste dataset
waste classification dataset
garbage detection dataset
object detection waste images
recycling AI dataset
multi-type waste image dataset
waste recognition dataset
smart waste sorting dataset
trash detection dataset
annotated garbage images
This dataset covering multiple waste types and diverse scenes. Annotated for object detection, classification, and recognition tasks.This dataset is ideal for AI research in waste sorting, recycling automation, and computer vision applications in smart environmental management.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Date size
46,695 images, 46,695 bounding boxes
Collecting environment
including indoor and outdoor scenes
Data diversity
multiple types of waste, multiple scenes
Device
cellphone
Data format
the image data formats are .jpg, png and jpeg , the annotation file format is .json
Annotation content
rectangular bounding boxes of waste
准确率
the accuracy of rectangular bounding boxes is not less than 97%
What types of computer vision applications can Nexdata’s datasets support?
Nexdata’s computer vision datasets support a wide range of AI applications, including image classification, object detection, image segmentation, facial and human-related recognition, scene understanding, autonomous driving, and other visual perception tasks. Depending on the dataset, data may include images, videos, bounding boxes, polygons, keypoints, segmentation masks, text annotations, and other structured labels.
Can Nexdata customize Computer Vision datasets based on our specific requirements?
Yes. If our off-the-shelf Computer Vision datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, annotation, and curation services. We can customize data based on your target objects, environments, scenarios, camera specifications, geographic locations, data volume, annotation formats, and quality standards to support specific model training and evaluation needs.
How does Nexdata ensure the quality and scalability of its Computer Vision datasets?
Nexdata applies multi-stage quality control throughout data collection, annotation, validation, and delivery. Depending on project requirements, we can implement customized annotation guidelines, multi-level reviews, consistency checks, and quality sampling to ensure dataset accuracy and consistency. Our data collection and processing capabilities can also be scaled to support large-volume Computer Vision projects.
Specifications
Sample
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