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
Great stuffs really. But it does support only classification and object detection with YoloV5. Any chance it will support instance segmentation as this is where most lenghty latency come from.
Great stuffs really. But it does support only classification and object detection with YoloV5. Any chance it will support instance segmentation as this is where most lenghty latency come from.
Thanks, Steve