• 7 min read
School Bus Detection Using YOLOv5 (Tutorial – Part 2)
Learn how to detect school buses using YOLOv5.
• 4 min read
Blurring Faces to Preserve Privacy with Computer Vision
SUMMARY
Automatically blurring faces and license plates before data enters a storage pipeline is a practical way to handle personally identifiable information in computer vision deployments, following the same approach used by Google Maps Street View. This tutorial covers collecting face and license plate datasets from Roboflow Universe, training a
• 4 min read
Launch: Semantic Segmentation for Labeling, Training, Deployment
SUMMARY
Semantic segmentation assigns a class label to every pixel in an image, making it useful for tasks where per-pixel precision matters: road and sidewalk mapping from aerial imagery, crack detection in infrastructure, defect identification in manufacturing, and medical image analysis. Roboflow now supports semantic segmentation end-to-end,
• 8 min read
What is an Autoencoder?
SUMMARY
An autoencoder is a neural network that compresses an input into a compact latent vector and then reconstructs it, with the latent representation, not the output, being the useful artifact. Six main variants exist for computer vision: undercomplete, denoising, sparse, contrastive, Variational (VAE), and Vector Quantised-Variational (VQ-VAE)
• 6 min read
What is Object Tracking in Computer Vision?
Learn about object tracking and how it is used in computer vision.
• 5 min read
Top 6 Manufacturing Datasets for Computer Vision
Explore six manufacturing datasets you can use for computer vision projects.
• 7 min read
Accelerate PyTorch Models via OpenVINO™ Integration with Torch-ORT
SUMMARY
OpenVINO integration with Torch-ORT lets PyTorch developers run accelerated inference on Intel CPUs, integrated GPUs, and VPUs without changing their existing code structure, requiring only two additional lines of Python. This post benchmarks a custom-trained YOLOv7 model on a dataset from Roboflow Universe and shows roughly a
• 8 min read
How to Use Computer Vision to Control OBS Studio
Learn how to use computer vision to control OBS Studio.
• 4 min read
Launch: Cloning Images from Open Source Datasets
SUMMARY
Roboflow Universe now lets you clone any of its 100+ million open source images directly into your own Roboflow project, with or without their existing annotations. This removes one of the biggest time sinks in computer vision development: sourcing labeled training data from scratch. You can filter by object
• 2 min read
Roboflow Joins AWS Global Startup Program and Becomes AWS ISV Accelerate Partner
SUMMARY
Roboflow has joined the AWS Global Startup Program and become an AWS ISV Accelerate Partner, deepening its integration with the cloud infrastructure that already powers Roboflow's model pipeline. The ISV Accelerate designation puts Roboflow alongside companies like Databricks and Auth0 in a co-sell program for enterprise
• 4 min read
Sharing Your Computer Vision Project on Roboflow Universe
In this guide, learn how to launch your computer vision project on Roboflow Universe.
• 3 min read
Launch: Use YouTube Videos for Training Data and Inference Testing
SUMMARY
Roboflow now accepts YouTube video URLs directly as an upload source, letting you sample frames from any of YouTube's 800+ million videos to build or expand a computer vision training dataset without downloading files manually. The same feature works in reverse: you can paste a YouTube URL
• 4 min read
Roboflow Changelog: September 2022
Each month, we share a recap of product and company updates. In this post, we detail Roboflow's updates from September 2022.
• 4 min read
Launch: Smart Polygon Labeling
SUMMARY
Roboflow Annotate's Smart Polygon tool uses a machine learning model behind the scenes to generate a polygon label with a single click on an object, reducing what previously required many manual point placements to a near-instant operation. Precise polygon annotations are required for training instance segmentation
• 6 min read
Object Detection vs. Image Classification vs. Keypoint Detection
Learn what object detection, classification, and keypoint detection are, and when tech technique is useful.
• 9 min read
Supervised Learning vs. Unsupervised Learning: Explained
Learn what supervised and unsupervised learning are and how they compare.
• 12 min read
How to Measure Distance in Photos and Videos Using Computer Vision
Learn how to measure distance in photos and videos using computer vision.
• 10 min read
How to Train YOLOv5 Instance Segmentation on a Custom Dataset
Learn how to train a YOLOv5 instance segmentation model on a custom dataset.
• 2 min read
Launch: Test Computer Vision Models Locally
SUMMARY
Roboflow Inference can now run locally on a development machine via a single npx command, with no CUDA installation or Docker setup required. Any 64-bit Intel, AMD, or Arm CPU (including M1 Macs and Raspberry Pi 4) can host the inference server on port 9001, and any pre-
• 9 min read
Using Computer Vision with Drones for Georeferencing
SUMMARY
A computer vision model can detect objects in drone footage but only tells you where something appears in a frame, not where it is on Earth. This tutorial shows how to combine detection output with the flight log from a DJI Mavic Air 2, converting pixel coordinates to latitude
• 4 min read
Roboflow Changelog: July & August 2022
Each month, we share a recap of product and company updates. In this post, we detail Roboflow's updates from July and August 2022.
• 2 min read
Roboflow now available in the AWS Marketplace
SUMMARY
Roboflow is now available through the AWS Marketplace, letting AWS customers purchase the platform under consolidated billing and apply spend toward AWS Enterprise Development Program commitments. Available tiers include Roboflow Growth (25k source images, 100k generated images, 1,000 monthly API calls) and custom enterprise orders with added usage
• 7 min read
How I use Computer Vision and Twilio to Guarantee Availability at Busy Public Tennis Courts
SUMMARY
A non-ML practitioner built a working computer vision application that monitors a local tennis court via webcam, detects whether players are on the court using a model trained in Roboflow, and sends an SMS notification through Twilio when a court opens up. The post covers the full pipeline:
• 5 min read
Train Activity Recognition Models Using Spectrograms and Computer Vision
As Ph.D. students in the Active Robotics Sensing Lab (ARoS) at NC State under the supervision of Dr. Edgar Lobaton, we developed in conjunction with The Engineering Place at NC State a set of activities to walk high school students through the entire computer vision pipeline.
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