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Learn to set up, train, and deploy YOLOv9 for custom object detection, including model evaluation, inference, and practical applications like self-service checkout systems.
Master image segmentation techniques using SAM-2.1, Meta's advanced model, through hands-on fine-tuning and practical implementation for enhanced computer vision capabilities.
Explore Meta's Perception Encoder with researcher Daniel Bolya to enhance visual understanding and improve text-to-image search relevancy through cutting-edge AI models.
Train a DETR object-detection transformer on a custom dataset with PyTorch, from COCO annotations and data loaders to inference and evaluation.
Master real-time video analytics using RTSP streams and computer vision to build monitoring systems for object counting, duration tracking, and traffic analysis.
Explore YOLO11's performance benchmarks, compare it to previous models, and learn to build real-world applications using this cutting-edge object detection technology.
Master YOLO11 object detection from dataset selection to model deployment. Learn image labeling, local and Colab training, hyperparameter tuning, performance evaluation, and real-world implementation in this comprehensive guide.
Explore OCR models, benchmark performance, and follow a step-by-step guide to implement Optical Character Recognition in your projects.
Discover how to speed up dataset annotation using AI-assisted labeling tools, then train an RF-DETR model for pill counting with live webcam testing in this hands-on tutorial.
Master PTZ camera automation with AI-powered object tracking using ONVIF integration, computer vision workflows, and real-time demonstrations.
Discover how to implement AI depth estimation in computer vision projects using Depth Anything V2 to accurately measure distances between objects in images and videos.
Discover how to build a smart parking system using computer vision to analyze drone footage, detect trailers, and determine stall occupancy with Roboflow's AI tools and OCR integration.
Master building production-ready computer vision apps in minutes with Roboflow Rapid. Create object detection models, implement tracking workflows, and deploy counting solutions.
Master RF-DETR, the state-of-the-art object detection model that surpasses YOLO methods. Train custom models using Google Colab or Roboflow Platform with step-by-step guidance.
Discover RF-DETR, a state-of-the-art object detection model that outperforms YOLO. Learn how to train, test, compare, and deploy this model in your computer vision projects with insights from Roboflow's machine learning team.
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