Merge remote-tracking branch 'origin/master'

Author: zym1119

README.md

@@ -1 +1,56 @@
-# DeepLabv3_MobileNetv2
+# DeepLabv3_MobileNetv2
+This is a PyTorch implementation of MobileNet v2 network with DeepLab v3 structure used for semantic segmentation.
+
+The backbone of MobileNetv2 comes from paper:
+>[Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation ](https://arxiv.org/abs/1801.04381v3)
+
+And the segment head of DeepLabv3 comes from paper:
+>[Rethinking Atrous Convolution for Semantic Image Segmentation](https://arxiv.org/abs/1706.05587)
+
+Please refer to these papers about details like Atrous Convolution, Inverted Residuals, Depthwise Convolution or ASPP if you have some confusion about these blocks.
+
+# How to use?
+First you need to install dependencies of this implementation.
+This implementation is written under Python 3.5 with following libs:
+>torch 0.4.0
+torchvision 0.2.1
+numpy 1.14.5
+opencv-python 3.4.1.15
+tensorflow 1.8.0 (necessary for tensorboardX)
+tensorboardX 1.2
+
+use `sudo pip install lib` to install them
+
+Then, prepare cityscapes dataset or your own dataset.
+Currently, cityscapes is the only supported dataset without any modification.
+
+Cityscapes dataset should have the following hierachy:
+```
+dataset_root
+|   trainImages.txt
+|   trainLabels.txt
+|   valImages.txt
+|   valLabels.txt 
+|
+└───gtFine(Label Folder)
+|   └───train(train set)
+|   |   └───aachen(city)
+|   |   └───bochum
+|   |   └───...
+|   |   
+|   └───test(test set)
+|   └───val(val set)
+|
+└───leftImg8bit(Image Folder)
+    └───train
+    └───test
+    └───val
+```
+
+Third, modify `config.py` to fit your own training policy or configuration
+
+At last, run `python main.py --root /your/path/to/dataset/` or just run `python main.py`
+
+After training, tensorboard is also available to observe training procedure using `tensorboard --logdir=./exp_dir/summaries`
+
+If you have some question, please leave an issue.