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Integrate vConsole for developers to facilitate the debugging of mobile plugins.
EOS is a dual-core operating system designed specifically for embodied intelligence, suitable for robots, drones, satellites or other scenarios requiring real-time and general capabilities.
Educational framework exploring ergonomic, lightweight multi-agent orchestration. Managed by OpenAI Solution team.
A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites
Official Task Suite Implementation of ICML'23 Paper "VIMA: General Robot Manipulation with Multimodal Prompts"
Official Algorithm Implementation of ICML'23 Paper "VIMA: General Robot Manipulation with Multimodal Prompts"
Using Transformer deep learning architecture to predict stock prices.
PyTorch implementations of Generative Adversarial Networks.
Real time yolov8 Android demo by ncnn
Monocular, One-stage, Regression of Multiple 3D People and their 3D positions & trajectories in camera & global coordinates. ROMP[ICCV21], BEV[CVPR22], TRACE[CVPR2023]
We write your reusable computer vision tools. 💜
Using YOLOv5 and opencv to perform (live) object detection for several hand gestures.
The world's simplest facial recognition api for Python and the command line
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Visualizer for neural network, deep learning and machine learning models
InstantID: Zero-shot Identity-Preserving Generation in Seconds 🔥
Virtual whiteboard for sketching hand-drawn like diagrams
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
fast-stable-diffusion + DreamBooth
✨ Light and Fast AI Assistant. Support: Web | iOS | MacOS | Android | Linux | Windows
A large-scale 7B pretraining language model developed by BaiChuan-Inc.
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.