• 7 min read
Data Augmentation in YOLOv4
Learn how data augmentation is used in training YOLOv4 computer vision models.
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 2 min read
Releasing a New YOLOv3 Implementation in PyTorch
SUMMARY
Roboflow released a PyTorch implementation of YOLOv3 built on the Ultralytics codebase, complementing the existing Keras version that users had requested an alternative to. In testing on a 12-class chess piece detection task, 300 epochs on Google Colab produced 0.93 recall and 0.978 mAP@50 in
• 1 min read
Introducing Image Preprocessing and Augmentation Previews
SUMMARY
Choosing augmentation settings without previewing the result means iterating blind, generating dataset versions only to discover the brightness shift was too aggressive or the rotation too extreme. Roboflow added preprocessing and augmentation previews so you can hover over an image in the dataset builder and see exactly how each
• 3 min read
Introducing Bounding Box Level Augmentations
SUMMARY
Standard image augmentation applies transforms to the entire frame, but bounding box level augmentation applies transforms only to the pixels inside each labeled bounding box, letting you vary brightness, blur, or other properties of a target object independently from its background. This technique, drawn from a 2019 Google research
• 4 min read
How to Select the Right Computer Vision Model Architecture
SUMMARY
Choosing a computer vision model architecture for object detection involves trading off speed, accuracy, and deployment constraints. This post compares three architectures: YOLOv3, a single-shot detector optimized for speed at 60+ FPS with lower accuracy; MobileNet SSD, a single-shot detector slightly slower than YOLOv3 but stronger on
• 3 min read
How to Win Pioneer
SUMMARY
Roboflow held the number one spot on the Pioneer.app global leaderboard for 18 consecutive weeks by following a consistent discipline: set concrete, completable goals each Sunday (not open-ended ones like "continue X"), then exceed them by focusing on controllable inputs rather than unpredictable outputs like
• 2 min read
Releasing an Improved Blood Count and Cell Detection (BCCD) Dataset
SUMMARY
The Blood Count and Cell Detection (BCCD) dataset, a widely used object detection benchmark with 364 microscope images across three classes (WBC, RBC, and Platelets), had significant annotation gaps in its original release. The Roboflow team reviewed each image and added 187 missing labels, 183 of them red blood
• 4 min read
Eliminating Boilerplate Code with Roboflow to Monitor Security Camera Footage
SUMMARY
Data scientist Alaa Senjab built a real-time gun detection model for security camera footage using a 2,973-image handgun dataset from the University of Grenada, and reported that Roboflow cut roughly half of his project code by handling annotation validation, preprocessing, augmentation, and format conversion automatically. Roboflow
• 2 min read
A popular self-driving car dataset is missing labels for hundreds of pedestrians
SUMMARY
A hand-check of the 15,000 images in the widely used Udacity Dataset 2 found problems in 4,986 of them (33%), including thousands of unlabeled vehicles, hundreds of unlabeled pedestrians, dozens of unlabeled cyclists, and 217 completely unannotated images that contained real objects. Phantom annotations, duplicated bounding
• 2 min read
Introducing Public Datasets
SUMMARY
Getting access to clean, labeled data is one of the hardest parts of starting a computer vision project. Roboflow Public Datasets (public.roboflow.com) addresses this by hosting free, downloadable datasets covering domains from board games to aerial drone imagery, each available in formats including VOC XML, COCO JSON,
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