Model Training

1 May 2025 • 4 min read

What Is AutoML?

SUMMARY AutoML (Automated Machine Learning) removes the need to manually select algorithms, tune hyperparameters, and engineer features by automating the full model-building pipeline from preprocessing through deployment. For computer vision specifically, platforms like Roboflow Train provide one-click cloud training that handles architecture selection and optimization, making it practical

10 Apr 2025 • 6 min read

How to Monitor Red Zones with Computer Vision

Learn how to monitor red zones for safety compliance using computer vision.

28 Mar 2025 • 7 min read

Launch: Train and Deploy RF-DETR Models with Roboflow

Learn how to train RF-DETR models with Roboflow Train and deploy RF-DETR models with Roboflow Workflows and Inference.

20 Mar 2025 • 11 min read

How to Train RF-DETR on a Custom Dataset

Learn how to train an RF-DETR model on a custom dataset.

13 Mar 2025 • 7 min read

Launch: Fine-Tune and Deploy Qwen2.5-VL Models with Roboflow

Learn how to fine-tune and deploy Qwen2.5-VL models with Roboflow.

3 Jan 2025 • 8 min read

5 Strategies for Handling Unbalanced Classes in Machine Learning

SUMMARY Class imbalance causes models to underperform on minority classes because the training distribution does not reflect the real-world distribution of what matters. Five strategies address this: gathering more data from underrepresented classes, generating synthetic samples through augmentation, undersampling the majority class via random selection, oversampling the minority class

2 Jan 2025 • 8 min read

What is Few-Shot Learning?

In this blog post, we discuss what few-shot learning is, architectural approaches for implementing few-shot learning, and specific implementations of few-shot learning techniques.

17 Dec 2024 • 5 min read

Launch: Fine-Tune PaliGemma-2 for VQA with Roboflow

Learn how to fine-tune PaliGemma-2 for VQA with Roboflow.

10 Dec 2024 • 13 min read

How to Fine-tune PaliGemma 2

Learn how to fine-tune PaliGemma 2 to extract data from an image in JSON format.

10 Dec 2024 • 5 min read

Launch: Fine-Tune Florence-2 for VQA with Roboflow

Learn how to fine-tune Florence-2 for visual question answering (VQA) using Roboflow.

13 Nov 2024 • 8 min read

How to Fine-Tune SAM-2.1 on a Custom Dataset

Learn how to fine-tune the Segment Anything 2.1 (SAM-2.1) model on a custom dataset.

3 Oct 2024 • 11 min read

How to Fine-Tune GPT-4o for Object Detection

Learn how to fine-tune GPT-4o to detect the location of objects in images.

3 Oct 2024 • 6 min read

How to Train YOLOv11 Instance Segmentation on a Custom Dataset

Learn how to fine-tune a YOLOv11 instance segmetnation model with a custom dataset and deploy the model with Roboflow Inference.

3 Sep 2024 • 10 min read

How to Train and Deploy YOLOv10 with Intel Emerald Rapids

Learn how to train and deploy YOLOv10 models on Intel Emerald Rapids systems.

3 Sep 2024 • 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.

1 Sep 2024 • 11 min read

What is Active Learning? The Ultimate Guide.

In this guide, we discuss what active learning is, types of active learning, and walk through an example of active learning in practice.

8 Aug 2024 • 8 min read

Camera Calibration in Sports with Keypoints

SUMMARY Accurate player tracking in sports footage requires mapping pixel coordinates from a moving camera to real-world field positions, and this tutorial covers how to do that by training a YOLOv8 keypoint detection model to recognize characteristic landmarks on a soccer pitch, then using those detections to compute a

16 Jul 2024 • 8 min read

What is the Open Images Dataset? A Deep Dive.

SUMMARY Open Images V7, released by Google in 2022, contains over nine million annotated images spanning nearly 20,000 categories and supports six annotation types: image-level labels, bounding boxes, segmentation masks, visual relationships, localized narratives, and point-level labels. That breadth makes it one of the few public datasets

11 Jul 2024 • 11 min read

How to Train RT-DETR on a Custom Dataset with Transformers

SUMMARY RT-DETR (Real-Time DEtection TRansformer), developed by Peking University and Baidu, is a transformer-based object detection model that targets competitive speed and accuracy compared to YOLO-family models. This tutorial covers fine-tuning RT-DETR on a custom dataset sourced from Roboflow Universe, using the HuggingFace Transformers

5 Jul 2024 • 5 min read

How to Use GPT-4 To Extract Handwritten Text from Images

SUMMARY This tutorial builds a pipeline that combines a custom object detection model trained in Roboflow with GPT-4 Vision inside a Roboflow Workflow to extract and structure handwritten information from homework booklets. The object detection model localizes handwritten marks, and GPT-4 Vision reads time and name fields, with

25 Jun 2024 • 12 min read

How to Fine-tune Florence-2 for Object Detection Tasks

This tutorial will show you how to fine-tune Florence-2 on object detection datasets to improve model performance for your specific use case.

14 Jun 2024 • 7 min read

What is YOLOv10? An Architecture Deep Dive

Learn about the main architectural components of YOLOv10 that contribute to the model's state-of-the-art speed and accuracy.

24 May 2024 • 6 min read

How to Train a YOLOv10 Model on a Custom Dataset

Learn how to train a YOLOv10 model using a custom dataset.

20 May 2024 • 7 min read

What is New in YOLOv9? An Architecture Deep Dive.

Learn what YOLOv9 is and what architectural features allow YOLOv9 to achieve strong performance on object detection and segmentation tasks.