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Mobile Deeplab-V3+ model for Segmentation

This project is used for deploying people segmentation model to mobile device and learning. The people segmentation android project is here. The model is another Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation (Deeplab-V3+) implementation base on MobilenetV2 / MobilenetV3 on TensorFlow.

This project uses tf.estimator API to do training, and many code come from TensorFlow model,

Dataset

This project supports 2 dataset.

1. PASCAL VOC2012
   • Base dataset used for test.
   • You could download the augmented segmentation dataset from DrSleep.
2. Supervisely People dataset.
   • People Segmentation dataset.
   • More data could refer to the blog
   • Download from Google Drive, baidu pan, code: 8pdv

Environment

• TensorFlow v1.12.0
  1. No module named keras_applications: solution
  2. AttributeError: 'Estimator' object has no attribute '_distribution': solution.

Usage

0. Prepare pretrained MobilenetV2 model(optional)

   bash prepare.sh

1. Train
   • train on pascal voc 2012 dataset

   bash train_pascal_voc2012.sh
   # Tensorboard
   tensorboard --logdir=datasets/pascal_voc2012/exp/deeplab-v3-plus/train

   • train on people segmentation dataset

   mv people_segmentation.tar.gz datasets
   bash train_people_seg.sh
   # Tensorboard
   tensorboard --logdir=datasets/people_segmentation/exp/deeplab-v3-plus/train

2. Export and Freeze model
   • pascal voc 2012 dataset

   bash export_pascal_voc2012.sh
   # Output
   # 1. TensorFlow Serving: datasets/pascal_voc2012/exp/deeplab-v3-plus/export/
   # 2. Frozen model: datasets/pascal_voc2012/exp/deeplab-v3-plus/export/frozen_model.pb

   • people segmentation dataset

   bash export_people_seg.sh
   # Output
   # 1. TensorFlow Serving: datasets/people_segmentation/exp/deeplab-v3-plus/export/
   # 2. Frozen model: datasets/people_segmentation/exp/deeplab-v3-plus/export/frozen_model.pb

Explanation

You could modify the parameters and add new backbones network easily.

1. Use MobilenetV3 backbone: Change parameter from --backbone="MobielentV2" to --backbone="MobilenetV3"
2. quant_friendly: Remove BN layer after Depthwise Convolution, replace relu6 with relu, method from A Quantization-Friendly Separable Convolution for MobileNets.

Result

1. Pascal VOC2012

• Environment: base_lr=0.007, training_steps=30000, learning_policy=poly, num_gpu=1.

2. People Segmentation Dataset

• Environment: base_lr=0.05, training_steps=150000, learning_policy=poly, num_gpu=1.
• Augmented: use augmented dataset.

TODO

• Add LR-ASPP module in MobilenetV3.

References

1. https://github.com/tensorflow/models/tree/master/research/deeplab
2. https://github.com/rishizek/tensorflow-deeplab-v3-plus
3. https://github.com/kuan-wang/pytorch-mobilenet-v3/blob/master/mobilenetv3.py
4. https://github.com/DrSleep/tensorflow-deeplab-resnet