DeepLab-v3-plus-cityscapes
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mIOU=80.02 on cityscapes. My implementation of deeplabv3+ (also know as 'Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation' based on the dataset of cityscapes).
hi by running your project,I can reach high mIoU,but when the Batchnormlization is setting all SYNC in ResNet,the mIoU can just reach 70%,why is that?
Thank you for your coding. I want to use my own images to train the model. So when I label my images, I just need to label them like "xxxxgtFine_labelIds.png...
 I am a beginner, I would like to ask you how to solve this mistake?
It is difficult to download from baidu, would it be possible for you to upload the pre-trained model somewhere else, like google drive. Thank You
I get different results from the same weight. No parameter change in the whole case. I got miou 80 in the end of the training after the weight was saved....
Hi, I noticed you updated your evluate.py. But I think your **previous** implementation is right, since if you use the evaluation code from https://github.com/mcordts/cityscapesScripts, you can get a mIou ~78.x...
Did you run the model on 8 GPUs or more? I cannot get a better result with more GPU, in fact it is worse.
There is no ReLU for ConvBNReLU in deeplabv3plus.py. Is that right? @CoinCheung
train loss
what about your train loss at last , 0.1xxx or0.01xxxx?