Blog

Joseph Nelson

Roboflow cofounder and CEO. On a mission to transform every industry by democratizing computer vision. Previously founded and sold a machine learning company.

Latest Posts by Joseph Nelson

How To Annotate Images with Your Team Using Roboflow

25 Dec 2020 • 3 min read

How To Annotate Images with Your Team Using Roboflow

SUMMARY Splitting annotation work across a team in Roboflow involves creating one dataset per annotator, sharing each dataset with the full team so everyone can see examples from colleagues, and then merging the individually labeled datasets into a single combined dataset once all images are labeled. This workflow keeps annotation

Share Your Datasets with the Computer Vision Community

6 Dec 2020 • 2 min read

Share Your Datasets with the Computer Vision Community

SUMMARY Roboflow offers to publicly host community-contributed computer vision datasets, making them discoverable to tens of thousands of developers and automatically indexed by Google Dataset Search. Hosted datasets are available for download in every major annotation format, including Pascal VOC XML, COCO JSON, and TFRecords, with no conversion work

Scaled-YOLOv4 is Now the Best Model for Object Detection

3 Dec 2020 • 8 min read

Scaled-YOLOv4 is Now the Best Model for Object Detection

SUMMARY Scaled-YOLOv4 set a new state-of-the-art result for object detection on the Microsoft COCO benchmark at the time of its publication, surpassing Google's EfficientDet across both the speed and accuracy ends of the performance frontier. The model achieves this by scaling the depth, stages,

computer vision for street murals

15 Nov 2020 • 4 min read

Bringing Street Murals to Life with Computer Vision

SUMMARY Software engineer Yuri Fukuda built a mobile computer vision app that lets users point a phone at the 3,300-square-foot When Women Pursue Justice mural in Brooklyn and identify the 90 women depicted. She captured photos from multiple angles, labeled them, applied image augmentation in Roboflow to

Hands on with the Roboflow Infer Web Application Interface Builder

8 Nov 2020 • 3 min read

Hands on with the Roboflow Infer Web Application Interface Builder

SUMMARY After training a model with Roboflow Train, the Example Web App gives an immediate browser-based interface to test predictions: upload an image or provide a URL, adjust confidence thresholds and bounding box overlap, filter classes, and view results as an annotated image or raw JSON. Because the app

Evaluating Object Detection Models with mAP by Class

3 Nov 2020 • 3 min read

Evaluating Object Detection Models with mAP by Class

SUMMARY Overall mAP scores can mask weak spots in a multi-class object detection model: a 98% aggregate hides the fact that one class is dragging performance down. Roboflow Train addresses this by surfacing per-class mAP on both the validation and training sets after every training run, so you

How to Use the Detectron2 Model Zoo (for Object Detection)

1 Nov 2020 • 3 min read

How to Use the Detectron2 Model Zoo (for Object Detection)

SUMMARY The Detectron2 model zoo provides pre-trained checkpoints for object detection, semantic segmentation, and keypoint detection, all built on PyTorch and maintained by Facebook AI Research. Swapping from the default Faster R-CNN X101 to any other detection model in the zoo requires changing a single config file path

protect endangered species

30 Oct 2020 • 5 min read

How This Fulbright Scholar is Using Computer Vision to Protect Endangered Species

SUMMARY Kasim Rafiq, a Fulbright Scholar and National Geographic Explorer at UC Santa Cruz, is building a vehicle-mounted computer vision system that automatically detects and photographs wildlife during safari game drives, then uses those detections for species population surveys at a fraction of the cost of traditional field methods.

Train Test Split Guide and Overview

28 Oct 2020 • 2 min read

Train Test Split Guide and Overview

SUMMARY Splitting a dataset into training, validation, and test sets is a core practice for detecting overfitting and ensuring a computer vision model generalizes beyond its training examples. Roboflow defaults to a 70/20/10 split at upload time but gives you direct control: you can assign individual image batches

How to Save and Load Model Weights in Google Colab

25 Oct 2020 • 5 min read

How to Save and Load Model Weights in Google Colab

SUMMARY Google Colab disconnects sessions after 12 hours or an hour of browser inactivity, which means a training run can complete but its weights are lost if you do not export them before the session ends. This post explains how to identify the weights file path after training, download it

Using Computer Vision to Help Deaf and Hard of Hearing Communities

19 Oct 2020 • 9 min read

Using Computer Vision to Help Deaf and Hard of Hearing Communities

SUMMARY Data scientist David Lee built a computer vision model to recognize American Sign Language alphabet from images, using data warping and oversampling to handle the limited and imbalanced training data. The goal is to give deaf and hard-of-hearing communities a tool that can interpret ASL through a

tesla

11 Oct 2020 • 6 min read

How Tesla Teaches Cars to Stop

SUMMARY Tesla Senior Director of AI Andrej Karpathy's CVPR 2020 talk reveals that even a seemingly straightforward computer vision task like stop sign detection involves dozens of edge cases: occluded signs, non-standard mounting, signs that do not require stopping, and conditionally active signs. Tesla handles this by

Improving Cancer Research with Computer Vision

4 Oct 2020 • 3 min read

Improving Cancer Research with Computer Vision

SUMMARY Researcher Mateo Sokac at Aarhus University is using object detection to identify neutrophils in dry microscopy images, with the goal of accelerating cancer research in humans. Starting from 127 labeled images, augmentation via Roboflow expanded the dataset to 451 samples and lifted mean average precision to 0.70, a

Introducing Grayscale and Hue/Saturation Augmentations

27 Sep 2020 • 3 min read

Introducing Grayscale and Hue/Saturation Augmentations

SUMMARY Roboflow has added three color-based augmentation options, grayscale, hue, and saturation, to help models generalize to objects that appear under different lighting conditions or in varied color environments. Grayscale augmentation randomly converts a configurable percentage of training images to single-channel output, reducing the model's reliance

data science

12 Sep 2020 • 1 min read

Elisha Odemakinde Hosts Roboflow for a Fireside Chat

Recently, Roboflow machine learning engineer Jacob Solawetz sat down with Elisha Odemakinde, an ML researcher and Community Manager at Data Science Nigeria, for a Fireside chat. During the conversation, Jacob walks through his journey from his career in financial trading to artificial intelligence, a move from natural language processing to

Explore Images, Annotations, and Metadata Easier

2 Sep 2020 • 2 min read

Explore Images, Annotations, and Metadata Easier

SUMMARY Roboflow's updated image preview interface lets users view annotations full-screen, toggle individual annotation groups on and off by hovering, and surface image metadata including the original filename, camera used, modification date, and which split the image belongs to. For dataset versions with augmentations applied, the preview

Cocoparks with roboflow

29 Aug 2020 • 2 min read

How Cocoparks Accelerated Their Development with Roboflow

SUMMARY Cocoparks, a Paris-based startup building parking and traffic-flow intelligence for French cities, shipped a working computer vision model in 30 days by using Roboflow to handle data preparation, augmentation, and format conversion. Mixing and matching image examples, applying augmentations that lifted model accuracy by 2 percent, and

Y Combinator

25 Aug 2020 • 2 min read

Roboflow Joins Y Combinator's Summer 20 Batch

Roboflow is enabling any developer to use computer vision (without being a machine learning expert). Computer vision is the first technology that fundamentally allows us to rewrite human-computer interaction. Until now, when using computers to interact with the world, humans would assess their environment, provide commands to a computer,

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

23 Aug 2020 • 8 min read

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

SUMMARY 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. Data scientist Jamie Shaffer trained a computer vision model on fish ladder footage, reaching a meaningful mAP@0.5 on a dataset where

16 Aug 2020 • 4 min read

Using Computer Vision to Find Brands in YouTube Videos

SUMMARY Software engineer Charles Herring built a browser-based computer vision model that detects power tool brands appearing in DIY YouTube videos, giving companies a way to measure unpaid exposure and identify sponsorship opportunities. Roboflow replaced Google Cloud AutoML as his data management layer, providing dataset-level class distribution statistics

Reducing Traffic with Computer Vision

4 Aug 2020 • 3 min read

Reducing Traffic with Computer Vision

SUMMARY Transport for Cairo used computer vision to count and classify vehicles, including taxis, tuk tuks, microbuses, and motorcycles, at intersections in a Ugandan city where no prior traffic data existed, replacing a costly manual volunteer counting approach. The team used Roboflow to manage image data, apply augmentations for underrepresented

pp-yolo

3 Aug 2020 • 8 min read

PP-YOLO Surpasses YOLOv4 - State of the Art Object Detection Techniques

Baidu publishes PP-YOLO and pushes the state of the art in object detection research by building on top of YOLOv3, the PaddlePaddle deep learning framework, and cutting edge computer vision research.

Improving Infrastructure Asset Management with Computer Vision

21 Jul 2020 • 6 min read

Improving Infrastructure Asset Management with Computer Vision

SUMMARY Result! Data built a mobile app called Spobber that uses computer vision to detect hectometre signs along Dutch highways, verifying whether field assets match database records and flagging missing or damaged signs automatically. This guest post walks through their full pipeline: data collection from a moving vehicle, annotation, augmentation

Retail Store Item Detection using YOLOv5

18 Jul 2020 • 9 min read

Retail Store Item Detection using YOLOv5

SUMMARY This tutorial trains a YOLOv5 model on the SKU110k dataset to detect and localize products on retail store shelves, with dataset preparation handled through Roboflow and model training run in Google Colab. The resulting detector draws bounding boxes around shelf items and can support inventory tracking or automated checkout

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