Semantic segmentation on PASCAL VOC
MaitaYuki opened this issue · comments
Thanks for sharing your great work!
I was able to reproduce your object detection result on Pascal VOC.
However, when I tested semantic segmentation on Pascal VOC using your pre-trained model on ImageNet1k "densecl_r50_imagenet_200ep.pth", I got mIoU 0.62, which is worse than the 0.69 reported in your paper. My test procedure is explained below,
- Install your modified mmsegmentation
- Download "densecl_r50_imagenet_200ep.pth" from your website
- Update the 5th line of code in fcn_r50-d8.py to pretrained='/pretrained/densecl_r50_imagenet_200ep.pth'
- Run ./tools/dist_train.sh configs/densecl/fcn_r50-d8_512x512_20k_voc12aug.py 2 --work-dir models/fcn_r50-d8_512x512_20k_voc12aug (running on 2 GPUs)
I got a result of mIoU 0.62, mAcc: 0.75, aAcc: 0.91 at the end of the training. I ran 3 rounds and got similar results. Attached are my configuration file and training log.
Do you know a possible reason?
Thanks!