An offline image annotation tool for object detection and segmentation.

Tokyo
Joined March 2017
Replying to @rectlabel
nice to meet you, and thank you for your reply. I watched the video from the link, and it looks good. It seems worth trying once. Thank you 🙏
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RectLabel retweeted
Developing novel or general category discovery for ocean research will help scientists to rapidly find unlabeled objects in historic datasets and enable creative field campaigns to seek out new life. Join the competition: kaggle.com/competitions/fath…
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Want to build a squat counter app? Now you can with our easy to use SDK for Pose Estimation. Details in thread. #HealthTech #squats #iOSdev #programming #computervision #ai #poseestimation #posedetection
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RectLabel retweeted
Replying to @rectlabel
Your tool is just amazing ! I’m using it everyday ! 🔥
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Replying to @rectlabel
@rectlabel I really love using your product ! Would you plan to add a gallery mode to sort with label and attributes ? It could be amazing ! 🙏
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Training a YOLOv3 Object Detection Model with a Custom Dataset by @josephofiowa buff.ly/388FuVu
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RectLabel retweeted
d'où viennent les étiquettes? Il y a un ImageNet pour le fromage?
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Replying to @rectlabel
@rectlabel your app is great ! so useful thanks ! 🙌
cc: @DrLukeOR @judywawira @DrHughHarvey @drsxr
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Friends who work on medical imaging + deep learning. What is your favorite software to annotate x-rays? We need to systematically annotate some x-rays with a label + bounding box and are looking for software to help. Obviously has to run locally for privacy reasons.
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RectLabel retweeted
WOW, @rectlabel can use our existing model to automatically annotate new images we add! Then we just have to correct the mistakes rather than starting completely from scratch. This is a game changer. It will make labeling additional training data so much less time consuming!
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How to Label Data — Create ML for Object Detection dlvr.it/R6BlwK
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Releasing STEAL, a new semantic boundary detector that significantly outperforms past work. Use STEAL to refine segmentation datasets, and train better segmentation models! @davidjesusacu @amlankar95 @NvidiaAI paper:arxiv.org/abs/1904.07934 code(@PyTorch):github.com/nv-tlabs/STEAL
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RectLabelかなりよい。vottで何回もデータを失ったことを思うと、もっと早く知りたかった。
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You can now use your iPad as a second display for your Mac. Feature is called “sidecar”
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RectLabel retweeted
Announcing Open Images V5, which adds segmentation masks to the largest existing dataset with object location annotations, along with the Open Images Challenge, a new object detection challenge to be held at @ICCV19. Learn more at ai.googleblog.com/2019/05/an…
RectLabel retweeted
San Francisco's 6-way intersections can be tricky to navigate. See how we autonomously handle them here.
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Wow prisoners in Finland 🇫🇮 are used to label training data for machine learning as part of their resocialization program. Not sure if this is good. I would rather teach them how to code and also to do machine learning on the data that they've labeled. theverge.com/2019/3/28/18285…
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Andrej Karpathy
@karpathy25 Apr 2019
New blog post: "A Recipe for Training Neural Networks" karpathy.github.io/2019/04/2… a collection of attempted advice for training neural nets with a focus on how to structure that process over time
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