AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models
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Updated
Jun 13, 2024 - Python
AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
Person detection and movment tracking using YOLOv8
A Python-based project utilizing YOLO and UltraAnalytics for advanced football analysis.
Object Detection System using Raspberry Pi and python
NVIDIA DeepStream SDK 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models
Ultralytics Docs at https://docs.ultralytics.com/
Real-Time Person Detection with Landmark Detection and Depth Estimation
Use YOLOv8 in real-time, for object detection, instance segmentation, pose estimation and image classification, via ONNX Runtime.
Ultralytics GitHub Actions
Converting COCO annotation (CVAT) to annotation for YOLOv8-seg (instance segmentation) and YOLOv8-obb (oriented bounding box detection)
MkDocs plugin for Ultralytics Docs at https://docs.ultralytics.com
Profile PyTorch models for FLOPs and parameters, helping to evaluate computational efficiency and memory usage.
Python script for people detection on webcam.
xView 2018 Object Detection Challenge: YOLOv3 Training and Inference.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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