Video · Image / AI & Machine Learning
Annotated Imagery Data | {Africa}
Advertised by providerLicensing rights not independently verifiedPaid licence
Overview
Annotated Imagery Data | {Africa} is a video and image dataset. Typical applications include segmentation, autonomous driving and robotics & embodied AI. Relevant sectors: AI & Machine Learning, Automotive & Mobility and Education. The listing mentions bounding boxes, polygons / segmentation and keypoints. It is offered as a paid dataset; pricing details are provided on request.
Primary applications
What the listing offers
- Listing mentions bounding boxes, polygons / segmentation, keypoints.
This dataset provides high-quality, ethically sourced Annotated Imagery Data and video streams across Africa and global regions, specifically designed to train, benchmark, and deploy advanced Computer Vision (CV), Machine Learning (ML), and Multi-Modal AI models. Sourced from our proprietary, ethically consented 500+ hour African video bank as well as targeted on-the-ground field capture, this dataset delivers rich, diverse visual training data that helps eliminate AI model bias across non-Western environments. Key Features & Capabilities Multi-Modal & Egocentric Datasets: Includes static imagery, continuous video streams, audio-synced sequences, and first-person (egocentric) perspective recordings. Geographic Diversity: Comprehensive coverage spanning diverse urban, rural, and aerial environments in Africa and worldwide under varied lighting and atmospheric conditions. Precision Human-in-the-Loop Annotations: High-accuracy bounding boxes, polygon masks, semantic segmentation, and keypoint tracking optimized for object detection and scene understanding. AI & ML Pipeline Ready: Cleaned, structured, and formatted for seamless integration into PyTorch, TensorFlow, OpenCV, and major cloud ML workflows. Key Use Cases Computer Vision & Object Detection: Train models to accurately recognize, classify, and track objects in complex, real-world scenes. Autonomous Systems & Mobility: Improve spatial perception, road feature recognition, and navigation for drones, autonomous vehicles, an
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