• 4 min read
What Are Anchor Boxes in Object Detection?
Learn what anchor boxes are, and why they are used in object detection.
Blog
Erik Kokalj
Developer Experience @ Roboflow
Latest Posts by Erik Kokalj
• 5 min read
Which is the Best Coding Agent for Vision tasks?
SUMMARY
This benchmark pits four coding agents (Claude Code with Opus 4.6, Cursor with Composer 2, Gemini CLI with Gemini 3.1 Pro, and Codex with GPT 5.4) against five computer vision tasks including bird counting with SAM 3, car counting in video and RTSP streams, avocado detection,
• 7 min read
VoTT for Image Annotation and Labeling
A guide on using VoTT to label your own computer vision dataset.
• 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.
• 12 min read
Cognex vs. Keyence: Which Machine Vision System Is Right for You?
Cognex vs Keyence comparison across cost, setup, and false positives, and why a vision AI platform may actually be the best fit.
• 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.
• 10 min read
How to Train an EfficientDet Object Detection Model with a Custom Dataset
Learn how to train an EfficientDet object detection model with a custom dataset.
• 14 min read
What Is YOLOv8? Architecture, Accuracy, and How to Use It
YOLOv8 is a computer vision model architecture that you can use for object detection, segmentation, keypoint detection, and more.
• 8 min read
How to Train a VGG-16 Image Classification Model on Your Own Dataset
The VGG16 model explained: 16 layers, 3x3 filters, 92.7% ImageNet top-5, plus how to train an image classifier on your own data, no GPU.
• 5 min read
Why and How to Implement Random Rotate Data Augmentation
Learn how to apply a random rotate data augmentation to images for use in training computer vision models.
• 7 min read
EfficientDet for Object Detection
EfficientDet object detection explained: EfficientNet backbone, BiFPN feature fusion, and compound scaling, plus how to train a detector today.
• 7 min read
EfficientDet vs YOLO for Object Detection
EfficientDet vs YOLO compared on architecture, speed, accuracy, and licensing, plus why RF-DETR is the stronger detector to deploy today.
• 9 min read
How to Train an EfficientNet Model with a Custom Dataset
Learn how to train an EfficientNet model with a custom dataset.
• 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.
• 13 min read
What Is YOLOv5? Architecture, Sizes, and How It Works
In this article, we discuss what is new in YOLOv5, how the model compares to YOLOv4, and the architecture of the new v5 model.
• 2 min read
Launch: Workflows Builder 2.0
Workflows Builder 2.0 is here with a drag-to-connect interface that makes building and understanding computer vision pipelines faster and clearer.
• 5 min read
Building an AI-powered Bot to Beat the Chrome Dino Game
SUMMARY
This tutorial walks through a complete computer vision project that trains an RF-DETR model to detect the Dino, Cactus, and Bird objects in the Chrome Dino game, then uses model predictions at inference time to drive keyboard actions via pynput. Dataset images were captured by screen-recording manual
• 5 min read
Train a YOLO26 Instance Segmentation Model with Custom Data
SUMMARY
This tutorial walks through fine-tuning YOLO26 for instance segmentation on the Car Part Detection dataset from Roboflow Universe, using a Google Colab notebook with the Ultralytics library. Unlike object detection bounding boxes, instance segmentation identifies the exact pixels belonging to each object, which matters for applications like medical
• 4 min read
How to Train a YOLO26 Object Detection Model with Custom Data
SUMMARY
This tutorial covers fine-tuning a YOLO26 object detection model on the Basketball-Player-Detection dataset from Roboflow Universe, which contains 654 annotated images of NBA players, referees, and basketballs. Using a Google Colab notebook with the Ultralytics library, the guide walks through GPU environment setup, dataset download via
• 6 min read
What Is YOLO26? An Introduction
YOLO26 brings faster CPU inference, small-object accuracy, and edge optimization to the YOLO family. See how it stacks up against today’s leading computer vision models.
• 14 min read
How to Train a YOLOv5 Model On a Custom Dataset
Learn how to train a YOLOv5 model on a custom dataset.
• 5 min read
How to Try CLIP: OpenAI's Zero-Shot Image Classifier
Earlier this week, OpenAI dropped a bomb on the computer vision world.
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