Real Time Inference
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A cutting-edge framework for training and deploying state-of-the-art YOLO models for object detection, segmentation, classification, and pose estimation.
A state-of-the-art PyTorch-based computer vision model for object detection, segmentation, and classification.
Cross-platform framework for building customizable on-device machine learning pipelines for live and streaming media.
A platform for deploying, managing, and scaling machine learning models in production on AWS infrastructure.
A library for building high-performance custom human pose estimation applications with real-time inference and flexible model development.
A lightweight encoder-decoder neural network for real-time semantic segmentation on resource-constrained devices.
A single-stage 3D object detector for point clouds that improves localization precision by explicitly leveraging structure information.
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