Latest Posts

5 Jul 2020 • 1 min read

Roboflow vs Scale

SUMMARY Roboflow and Scale serve different stages of the computer vision pipeline: Scale and similar services (LabelBox, SuperAnnotate, SageMaker Ground Truth) handle outsourced annotation, while Roboflow takes over after labeling to manage preprocessing, augmentation, dataset versioning, and training integrations. Roboflow imports annotations directly from most of these services, and its

1 Jul 2020 • 3 min read

How AI Acts as a Human Rights Watchdog for the Maasai People

SUMMARY A team of students built a computer vision system that processes satellite imagery from Google Earth Engine to monitor Maasai villages in Kenya and Tanzania, tracking settlement size, health, and evidence of burning to document land displacement by government and conservation interests. The model was trained using Roboflow'

1 Jul 2020 • 6 min read

Train a YOLOv4-tiny Model on a Custom Dataset

Learn how to train a YOLOv4-tiny model on a custom dataset.

28 Jun 2020 • 6 min read

Improving Uno with Computer Vision (Plus the Dataset so You Can Too)

SUMMARY Software engineer Adam Crawshaw built an Android app that uses object detection to automatically score Uno hands, handling the multi-round point system most players overlook. Starting from 41 source card images, he used OpenCV to synthetically composite cards into stacked groups, producing a dataset of 8,992 images

25 Jun 2020 • 7 min read

Creating BoardBoss: A Mobile Application that Improves Boggle

SUMMARY BoardBoss is a free iOS app, built by the Roboflow team, that scans a Boggle board with a smartphone camera, identifies letters in any orientation across more than 30 classes, and overlays all valid word solutions in augmented reality. The post walks through the full pipeline: collecting 355 images

24 Jun 2020 • 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.

19 Jun 2020 • 5 min read

How to Convert Annotations from PASCAL VOC to YOLO Darknet

SUMMARY PASCAL VOC stores bounding box annotations as XML files with absolute pixel coordinates, while YOLO Darknet uses plain text files with class index and normalized center coordinates. Converting between them means restructuring both the file format and the coordinate representation. This post walks through both formats with concrete examples

18 Jun 2020 • 4 min read

How to Build a Custom Open Images Dataset for Object Detection

SUMMARY Google's Open Images dataset contains millions of labeled images across hundreds of object classes, all under a CC BY 4.0 license, but downloading the full dataset requires over 500 GB of storage. This post shows how to use the OIDv4_ToolKit to query specific classes and

12 Jun 2020 • 16 min read

Responding to the Controversy about YOLOv5

SUMMARY When Roboflow published an early YOLOv5 benchmark in June 2020, the machine learning community raised two substantive objections: whether naming Glenn Jocher's repository YOLOv5 was appropriate given no paper was published, and whether the benchmark methodology was reproducible and fair. This post documents the full history of

10 Jun 2020 • 4 min read

YOLOv5 is Here: State-of-the-Art Object Detection at 140 FPS

SUMMARY Released in June 2020, YOLOv5 is a PyTorch-based object detection model from Ultralytics that differs from YOLOv4 in several practical ways: it uses a lighter Ultralytics PyTorch framework instead of Darknet, its smallest variant (YOLOv5s) weighs 27 MB compared to 244 MB for YOLOv4, and it offers faster

3 Jun 2020 • 3 min read

Teaching a Drone to Fly on Auto Pilot with Roboflow

SUMMARY Victor Antony, a data scientist at the University of Rochester, built a computer vision autopilot system to detect gates that a drone must fly through, starting from only 300 images captured in a warehouse. Using Roboflow, he applied augmentations for rotation, lighting, and blur to expand the dataset to

2 Jun 2020 • 7 min read

Getting Started with Data Augmentation in Computer Vision

SUMMARY Data augmentation artificially expands training sets by applying flips, crops, rotations, noise, and occlusion techniques, and it has a measurable impact on object detection accuracy even when collecting more labeled images is not practical. RF-DETR relies heavily on augmentation to achieve its COCO benchmark results, and the same

31 May 2020 • 1 min read

A New Video Tutorial: YOLOv4 in PyTorch

SUMMARY This post introduces a 20-minute video tutorial covering how to use Roboflow to prepare a custom dataset and train a YOLOv4 model in PyTorch. It accompanies the team's earlier written guides on the YOLOv4 architecture and Darknet-based training, extending them to the PyTorch framework for

27 May 2020 • 3 min read

Introducing An Even Better Way to Preview Image Preprocessing and Augmentation

SUMMARY Roboflow's revamped preprocessing and augmentation previews let you see exactly what each step does to your images before committing to a pipeline, replacing guesswork and boilerplate transformation code with a visual interface. The update covers choices like aspect-ratio-preserving resize strategies (padding, crop, reflect) and the

24 May 2020 • 3 min read

Thermal Infrared Dataset for Object Detection

SUMMARY Thermal infrared cameras detect surface temperature rather than reflected light, which makes them useful for detecting people and objects in darkness, smoke, or other low-visibility conditions where RGB cameras fail. Roboflow released a free 203-image thermal dataset of people and dogs, captured with a Seek Compact XR

13 May 2020 • 7 min read

Data Augmentation in YOLOv4

Learn how data augmentation is used in training YOLOv4 computer vision models.

5 May 2020 • 7 min read

Using Computer Vision to Count Fish Populations (and Monitor Environmental Health)

Counting salmon passing through a fish ladder viewing window is currently done by trained human observers, but object detection models can automate and scale that work. See how data scientist Jamie Shaffer trained a computer vision model.

4 May 2020 • 6 min read

Breaking Down the Technology Behind Self-Driving Cars

SUMMARY Self-driving systems fail at edge cases like a white truck against a bright sky because object detection models learn only from the labeled examples they are trained on, making data collection and annotation the most critical and expensive part of building autonomous perception. This post walks through how

29 Apr 2020 • 4 min read

Breaking Down Roboflow's Health Check Dimension Insights

SUMMARY Resizing images for computer vision is not a simple stretch-to-fill operation: aspect ratio distortion, small image outliers, and extreme width-to-height ratios all affect what a model can learn. Roboflow's Dimension Insights tool, part of the Dataset Health Check, visualizes every image in a

28 Apr 2020 • 1 min read

Introducing the Roboflow Model Library

SUMMARY The Roboflow Model Library brings together 7 open source object detection models and 3 classification models in one place, each accessible via GitHub, a downloadable Jupyter notebook, or Google Colab with free GPU access. All notebooks integrate directly with Roboflow, so datasets uploaded and annotated on the platform can

16 Apr 2020 • 2 min read

Roboflow Presents at Open Data Science Conference (ODSC) East 2020

SUMMARY At ODSC East 2020, Roboflow delivered a three-hour online tutorial walking through the full object detection workflow: framing a good problem, collecting and labeling images, preprocessing, selecting augmentations, training a model, and running inference. Slides, a Colab notebook, and additional resources from the session are publicly available for

10 Apr 2020 • 3 min read

Introducing an Improved Hard Hat Dataset for Computer Vision in Workplace Safety

SUMMARY Detecting hard hat compliance with computer vision requires a well-annotated dataset that reflects the variety of real construction environments. This post introduces a cleaned version of the Northeastern University hard hat dataset, now available on Roboflow Universe with 7,035 images and 27,039 bounding box annotations across

8 Apr 2020 • 1 min read

Our First Video Tutorial: YOLOv3 in PyTorch on a Custom Dataset

SUMMARY This post announces the launch of Roboflow's YouTube channel with a debut video tutorial on training YOLOv3 in PyTorch on a custom dataset, using an Ultralytics implementation and Roboflow for data preparation. The video format was introduced to provide more guided support as the volume and variety

3 Apr 2020 • 2 min read

Using Computer Vision to Fight Coronavirus (COVID-19)

SUMMARY Chest X-rays and CT scans show patterns associated with COVID-19 that computer vision models can learn to flag, offering a supplementary diagnostic path in settings where PCR testing infrastructure is limited. Early open datasets combined COVID-19 scans with existing pneumonia radiology data to give models enough