dnth / yolov5-deepsparse-blogpost

By the end of this post, you will learn how to: Train a SOTA YOLOv5 model on your own data. Sparsify the model using SparseML quantization aware training, sparse transfer learning, and one-shot quantization. Export the sparsified model and run it using the DeepSparse engine at insane speeds. P/S: The end result - YOLOv5 on CPU at 180+ FPS using on
https://dicksonneoh.com/portfolio/supercharging_yolov5_180_fps_cpu/
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Colab notebook #1

Closed dnth closed 2 years ago

dnth commented 2 years ago

It will be good to have a Colab notebook to replicate the examples in the blog.

dnth commented 2 years ago

Close by https://github.com/dnth/yolov5-deepsparse-blogpost/commit/f012ebe6d1f3015501ea72d3bcf0aa1265996044