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Learn to track vehicles and estimate their speed using computer vision techniques. Covers object detection, multi-object tracking, perspective transformation, and speed estimation with practical code implementation.
Step-by-step guide to fine-tune PaliGemma for custom object detection, covering setup, dataset preparation, training, evaluation, and deployment. Includes practical tips and important considerations.
Comprehensive guide to fine-tuning Florence-2 for custom object detection, covering environment setup, dataset preparation, and model optimization using LoRA, with practical examples and performance comparisons.
Explore OCR models, benchmark performance, and follow a step-by-step guide to implement Optical Character Recognition in your projects.
Discover the latest Roboflow innovations through six mini-presentations covering RF-DETR object detection, instant training, polygon zones, SQL integration, batch processing, and serverless inference for computer vision applications.
Master real-time video analytics using RTSP streams and computer vision to build monitoring systems for object counting, duration tracking, and traffic analysis.
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.
Learn how to enhance workplace safety with vision AI by tracking people and objects in danger zones, building red zone trackers, and integrating data systems for trend analysis.
Discover how to train custom AI models to measure physical objects, avoid common mistakes, and improve accuracy through proper calibration and image processing techniques.
Learn to create advanced computer vision applications by combining Workflows editor tools with custom Python blocks for gesture detection, data enrichment, and visualization customization.
Master real-time vision model deployment across multiple video streams while centralizing management, reducing hardware needs, and streamlining monitoring for efficient AI implementation.
Master YOLOv12 object detection by learning model fine-tuning, custom training, and building applications to identify shipping containers with OCR text extraction and CSV export capabilities.
Explore how different vision-language models (VLMs) perform on real-world visual tasks, with comparisons, observations about their future, and techniques for combining models to solve complex problems.
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.
Master vision language modeling with Florence-2, from fine-tuning techniques to practical implementation in computer vision projects using Roboflow's Workflows for object detection and OCR tasks.
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