Player detection for Apex Legends video-game
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Updated
Jun 3, 2024 - Jupyter Notebook
Player detection for Apex Legends video-game
带你从零实现一个高性能的深度学习推理库,支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step
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🚀🚀🚀 YOLO series of PaddlePaddle implementation, PP-YOLOE+, RT-DETR, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOX, YOLOv5u, YOLOv7u, YOLOv6Lite, RTMDet and so on. 🚀🚀🚀
Profile PyTorch models for FLOPs and parameters, helping to evaluate computational efficiency and memory usage.
YOLO V5 OBJECT DETECTION APPLICATION
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
Rental app with in-depth data analysis, interactive data visualization, predictive analytics, and chatbot using Dash. Selected as Plotly’s Top ChatGPT & Generative AI Project
Custom YOLOv5 fork for the Insect Detect DIY camera trap.
A small AI project that Seamlessly integrates object detection, text-to-speech synthesis, and speech recognition into a powerful interactive model.
Detection models and Python scripts for automated insect monitoring with the Insect Detect DIY camera trap.
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Ultralytics HUB tutorials and support
Seeed SenseCraft Model Assistant is an open-source project focused on embedded AI. 🔥🔥🔥
Smart Traffic Flow Management System
MkDocs plugin for Ultralytics Docs at https://docs.ultralytics.com
Identifying cooling towers from satellite and aerial imagery
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