chenjun2hao / DDRNet.pytorch

This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
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how can I reach the same accuracy in the paper? #26

Open coallar opened 1 year ago

coallar commented 1 year ago

Hi, bro, I train DDRNet-23 without pretrained model using 1024x1024 resolution. While it get 0.71mIoU metric. I want to know how can I reach the same accuracy in the paper? what is your trick? thanks