• 10 min read
Flanges Quality Inspection with Computer Vision
Train RF-DETR to catch flange face defects, then sort results into pass, review, and fail.
• 9 min read
How to Fine-Tune RF-DETR Keypoints on Custom Data
A step-by-step guide to fine-tuning RF-DETR Keypoint on a custom basketball court dataset, from COCO pretrained inference to training, evaluation, and broadcast-video inference.
• 16 min read
YOLO Training Guide: How to Train a YOLO Model
In this guide you will learn how to train a YOLO model with Roboflow using a labeled dataset, pretrained checkpoints, hosted GPUs, and well managed infrastructure, and as well as how to use the YOLO CLI.
• 12 min read
Train a Computer Vision Model with Roboflow Train
Discover how Roboflow Train automates computer vision model training. Eliminate infrastructure setup, leverage NAS, and deploy to production.
• 11 min read
What is Mean Average Precision (mAP) in Object Detection?
What is mean average precision? How do we calculate mAP?
• 13 min read
How to Train a YOLO26 Oriented Bounding Box (OBB) Model
Learn how to train a YOLO26 Oriented Bounding Boxes model with a dataset labeled on Roboflow.
• 5 min read
Neural Architecture Search: Train the best vision model for your data
Balancing inference speed and accuracy just got easier. Learn how Neural Architecture Search evaluates thousands of configurations simultaneously to deliver the highest-performing model for your target hardware.
• 4 min read
How to Create a TFRecord File for Computer Vision and Object Detection
How to create a TFRecord file for object detection: what it is, when you need it, and how to export one from a labeled dataset in Roboflow.
• 18 min read
Training a TensorFlow Faster R-CNN Object Detection Model on a Custom Dataset
Train a Faster R-CNN style detector on a custom dataset in your browser: no GPU, no code. Label, train RF-DETR, and deploy from cloud to edge.
• 4 min read
The Importance of Blur as an Image Augmentation Technique
Learn about the efficacy of blur as an image augmentation step in computer vision model training.
• 7 min read
How to Train a Custom TensorFlow Lite (Now LiteRT) Object Detection Model
Learn how to train a custom TensorFlow Lite object detection model with a custom dataset.
• 7 min read
How to Train YOLOv4 on a Custom Dataset
Want to train YOLOv4? Train a custom object detector without Darknet, a config file, or a GPU: Learn how with Roboflow.
• 5 min read
Why and How to Implement Random Crop Data Augmentation
Learn how to apply a random crop data augmentation to images for use in training computer vision models.
• 9 min read
How to Save and Load Model Weights in Google Colab
Save and load model weights in Google Colab: mount Google Drive, checkpoint during training, reload or resume in a new session, and deploy.
• 4 min read
Launch: Train and Deploy YOLO26 with Roboflow
SUMMARY
Roboflow platform support for YOLO26 covers the full workflow from labeling and training to deployment. The model's edge-optimized architecture, which removes Non-Maximum Suppression for end-to-end predictions and introduces the MuSGD optimizer, can be deployed via Roboflow Inference on CPU or GPU hardware. Dataset
• 9 min read
How to Train YOLOv8 Object Detection on a Custom Dataset
In this article, we walk through how to train a YOLOv8 object detection model using a custom dataset.
• 14 min read
How to Train a YOLOv5 Model On a Custom Dataset
Learn how to train a YOLOv5 model on a custom dataset.
• 6 min read
Launch: Use Segment Anything 3 (SAM 3) with Roboflow
SUMMARY
Roboflow has integrated SAM 3, Meta's foundation model for Promptable Concept Segmentation, across every major part of its platform, covering the Playground for interactive testing, the inference API, edge and private-cloud deployment, Roboflow Workflows for building production pipelines, and the Label Assist annotation tool for accelerating
• 3 min read
Roboflow Named Leader in Image Recognition Software
We’re proud to announce that as of November 2025, Roboflow has been ranked the #1 Image Recognition product on G2.
• 4 min read
Launch: Verified Model Metrics
SUMMARY
Model evaluation scores are not always comparable across providers because teams use different test sets, confidence thresholds, and calculation methods, which makes selecting models for production unreliable. Roboflow Verified Model Metrics addresses this by calculating mAP using open-source COCO Evaluation methodology from the Supervision library on independent test
• 4 min read
How I Taught My Dad Computer Vision with Roboflow in Under 30 Minutes!
Discover how I helped my dad build a custom computer vision model in under 30 minutes using Roboflow’s no-code AI tools.
• 3 min read
Automate Game Scorekeeping with Vision AI
SUMMARY
This tutorial builds a real-time automated scorekeeping system for cornhole using a custom computer vision model and a Roboflow Workflow. The model detects bags, the board, and the hole from an overhead camera; the Workflow then applies game logic to map detections to zones, calculate the score, and
• 5 min read
Count Objects on a Conveyor Belt Using Computer Vision
SUMMARY
This tutorial builds an end-to-end system for counting bolts and nuts on a moving conveyor belt, covering every stage from data collection to local deployment. Video frames are annotated using Roboflow's auto-labeling with Grounding DINO, a custom detection model is trained in the cloud,
• 4 min read
How to Draw a Bounding Box with Python
In this post, we discuss how to use the Roboflow supervision library to draw and fill a bounding box in Python.
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