• 16 min read
How to Train a YOLOv6 Model on a Custom Dataset
Learn how to train a YOLOv6 object detection model on a custom dataset.
• 5 min read
Using Gaming Datasets for Game Automation with Computer Vision
SUMMARY
This tutorial walks through building a computer vision model to detect Minecraft tree trunks using screenshots collected across multiple in-game biomes, annotated and trained via Roboflow. The resulting model is deployed through a Python inference script that reads frames from an OBS Studio virtual webcam, enabling real-time
• 9 min read
Train and Deploy YOLOS Transformer On a Custom Dataset
In this post, we showcase training and deploying YOLOS end to end, from labeling your data, to training your model, to deploying your model on AWS for inference.
• 8 min read
Food Manufacturing Defect Detection with Lucky Charms
SUMMARY
This tutorial builds a computer vision system to detect and classify the eight types of Lucky Charms marshmallows (marbits) as a practical stand-in for food manufacturing quality control. Dataset labeling and preprocessing happen in Roboflow, and the post covers two training paths: Roboflow Train for a one-click
• 6 min read
Autonomous Vehicle Object Detection
SUMMARY
Ampera Racing, a student engineering team from UFSC in Brazil, built a low-cost autonomous vehicle pipeline using computer vision as the core perception layer, with RF-DETR handling cone detection for the Formula Student Driverless competition. The architecture covers five subsystems: environment perception, mapping, motion planning, lateral control,
• 2 min read
Launch: Instance Segmentation Project Training and Inference
SUMMARY
Roboflow now supports instance segmentation project training and inference natively on the platform, letting teams train directly from a pre-trained COCO checkpoint without writing training code. Instance segmentation produces per-object outlines rather than just bounding boxes, making it the right choice when downstream tasks require measuring object
• 4 min read
Launch: Roboflow OAK pip package
roboflowoak pip package lets you natively interface with your Roboflow workspace through Python scripts and deploy to an OAK device.
• 4 min read
Boxing Punch Detection Using Computer Vision
One of the best parts about joining Roboflow is doing a computer vision project in your first 2 weeks. As someone who loves to workout, I wanted to focus my project on a fitness related use case. I often mix boxing workouts into my routine, and thought it would be
• 3 min read
How to Train a YOLOv5 Oriented Bounding Box Model
Learn how to train a YOLOv5 Oriented Bounding Box (OBB) object detection model.
• 2 min read
Testing A Computer Vision Model In 10 Seconds Or Less
Learn how to test your computer vision model with Roboflow.
• 7 min read
How to Train Computer Vision Models on Aerial Imagery
SUMMARY
Aerial imagery from drones and planes presents distinct challenges for computer vision: small objects have few pixels to form features from, large image sizes slow training and inference, and orientation bias can mislead models. This post walks through the full pipeline for building a custom model on aerial data
• 7 min read
How to Train YOLOX On a Custom Dataset
The YOLO family continues to grow with the next model: YOLOX. In this post, we will walk through how you can train YOLOX to recognize object detection data for your custom use case.
• 2 min read
Fighting Wildfires with Computer Vision
SUMMARY
Abhishek Ghosh, a graduate student at Texas A&M working with AI For Mankind, trained an EfficientDet D0 computer vision model to detect early smoke from forest fires using images from weather towers. Using Roboflow Pro, he applied advanced augmentations and a static crop along the horizon line
• 8 min read
How to Train a Custom Mobile Object Detection Model (with YOLOv4 Tiny and TensorFlow Lite)
Learn how to train a custom mobile object detection model with YOLOv4 tiny and TensorFlow Lite.
• 9 min read
Retail Store Item Detection using YOLOv5
SUMMARY
This tutorial trains a YOLOv5 model on the SKU110k dataset to detect and localize products on retail store shelves, with dataset preparation handled through Roboflow and model training run in Google Colab. The resulting detector draws bounding boxes around shelf items and can support inventory tracking or automated checkout
• 9 min read
How to Train Detectron2 on Custom Object Detection Data
Learn how to train a Detectron2 model on a custom object detection dataset.
• 7 min read
Data Augmentation in YOLOv4
Learn how data augmentation is used in training YOLOv4 computer vision models.
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