AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models
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Updated
Jun 15, 2024 - Python
AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models
This Python script uses YOLOv8 from Ultralytics for real-time object detection using OpenCV. The script initializes a camera, loads the YOLOv8 model, and processes frames from the camera, annotating detected objects with bounding boxes.
YOLO model integration with the Streamlit
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
Проект для обучения модели по определению рамки автомобильного номера
Проект для обучения модели по определению автомобилей на изображениях
Robot capable of performing object detection using a Raspberry Pi Zero 2W and a camera module. The goal is to detect and track the user's presence in the camera feed.
Base Image Processing repo focuses on YOLO (You Only Look Once) used in Jetson Nano (+ Orin Nano) & Raspberry Pi 4
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.
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