Use YOLOv5 tensorflow.js models to speed up annotation

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/computervision

Our great sponsors
  • Zigi - Delete the most useless function ever: context switching.
  • Scout APM - Truly a developer’s best friend
  • InfluxDB - Build time-series-based applications quickly and at scale.
  • Sonar - Write Clean Python Code. Always.
  • yolov5

    YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

    Hi everyone! I'm Piotr and for several years I have been developing a small open-source project for labeling photos - makesense.ai. I added a new feature this weekend. You can use [YOLOv5](https://github.com/ultralytics/yolov5) models to automatically annotate photos. You can choose one of the models pre-trained on the COCO dataset, but most importantly you can load your own custom models. Just drag and drop the tensorflow.js model to the editor and you are good to go. Everything runs in brawser - no backend, so it is completely free. Let me know what you think! I'm super excited about that project.

  • yolov5js

    Effortless YOLOv5 javascript deployment

    By the way, I have created an NPM package, which can also make it easier for you to deploy YOLOv5 in the browser. https://github.com/SkalskiP/yolov5js

  • Zigi

    Delete the most useless function ever: context switching.. Zigi monitors Jira and GitHub updates, pings you when PRs need approval and lets you take fast actions - all directly from Slack! Plus it reduces cycle time by up to 75%.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts