Object Detection using Yolov7 in tensorflow.js
Home Page: https://www.youtube.com/watch?v=pBWIg80xlXE
License: Apache License 2.0
This repository is an implementation of Yolov7 using Tensorflow.js. The code runs directly on the browser and the detector was trained on the MS COCO dataset to recognizes up to 80 different classes.
See more examples here.
Object Detection using YOLOv5 and Tensorflow.js
This code was developed under the financial assistance of the Google Developers Group, which provided all the computational resources for training and converting the models.
Hi, I followed this script convert pytorch model to tfjs.
However, the 70MB torch model becomes 140 MB in tfjs, and my IOS device won't load the tfjs model (desktop/Android is OK).
I guess the original torch model could be 16 bit, but during the conversion, it becomes 32 bit.
Do you know if there is a solution to make the model consistent (keep it be 16 bit) during the conversion?
Thank you
Hello, would you share the pretrained model in normal TF/Onnx/PT format? I plan to use it but not on a mobile device and hence TFJS is not needed.
Hi, can you give more info about how you transformed the pytorch graph to a tfjs one? I tried but I run over tons of errors.
Thanks and great work!
hello! i have a doubt about why you decided to implement the non max suppression from scratch instead of using tf.image.nonMaxSuppression. my question is if you decided this for performance improvements or because you just wanted to do it. thanks in advance! and i hope you're well :DD
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