• 12 min read
Luxonis OAK-D: Deploy a Custom Object Detection Model with Depth
Train a custom object detection model and deploy it to the Luxonis OAK-D: RF-DETR on the host, depth per detection, and on-device options.
• 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.
• 15 min read
Best Pose Estimation Models
Pose estimation is transforming how we understand human movement, powering everything from fitness tracking and sports analytics to healthcare rehabilitation. This guide explores the best pose estimation models, and shows how to deploy them efficiently across mobile, edge, and cloud environments.
• 6 min read
Using Videos as Training Data
Turn video files into training data. Learn how to extract frames, set sampling rates, and use Roboflow to speed up computer vision labeling.
• 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.
• 25 min read
Gemini 3 Guide: Master Google’s Deep Think Model in Roboflow
Explore Gemini 3’s native multimodality and Deep Think reasoning. Learn how to deploy Gemini 3.1 Pro for object detection, OCR, and VQA using Roboflow Workflows and Playground.
• 7 min read
What Is ResNet-50? Architecture Explained
Learn what ResNet-50 is, how it works, and how ResNet models of various levels perform on image classification.
• 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.
• 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.
• 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.
• 15 min read
Roboflow Training Graphs Guide
Learn how to read Roboflow training graphs. Understand what each curve means, how the underlying metrics are computed, and how to diagnose common training problems.
• 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.
• 5 min read
Liquid Neural Networks in Computer Vision
Excitement is building in the artificial intelligence community around MIT's recent release of liquid neural networks. The breakthroughs that Hasani and team have made are incredible. In this post, we will discuss the new liquid neural networks and what they might mean for the vision field.
• 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.
• 10 min read
Training a TensorFlow MobileNet Object Detection Model with a Custom Dataset
Train a TensorFlow object detection model on a custom dataset the modern way: label, train RF-DETR, and deploy in Roboflow, no TFRecords.
• 7 min read
Best Multimodal Models in 2026
From SAM 3’s record-breaking segmentation speed to Gemini 3’s massive 2-million-token context window, explore the top models that can "see," reason, and deploy in production today.
• 7 min read
Segment Anything
This guide breaks down the SAM lineage - from SAM 1’s 50ms CPU inference to SAM 3’s open-vocabulary "GPT moment" - showing you how to deploy these foundation models into your production workflows 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.
• 12 min read
What Is OpenPose? A Guide to Pose Estimation
In this guide, we discuss what OpenPose is, what you can do with the model, and how to use OpenPose.
• 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.
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