315haoge/3D-Object-Detection

Indoor Semantic Segmentation

3D Object Detection

This repository is to do Indoor Semantic Segmentation with SegNet.

Dependencies

• NumPy
• Tensorflow
• Keras
• OpenCV

Dataset

Follow the instruction to download 2D-3D-S dataset.

$ wget https://storage.googleapis.com/3dsemantics/noXYZ/area_1_no_xyz.tar
$ wget https://storage.googleapis.com/3dsemantics/noXYZ/area_2_no_xyz.tar
$ wget https://storage.googleapis.com/3dsemantics/noXYZ/area_3_no_xyz.tar
$ wget https://storage.googleapis.com/3dsemantics/noXYZ/area_4_no_xyz.tar
$ wget https://storage.googleapis.com/3dsemantics/noXYZ/area_5a_no_xyz.tar
$ wget https://storage.googleapis.com/3dsemantics/noXYZ/area_5b_no_xyz.tar
$ wget https://storage.googleapis.com/3dsemantics/noXYZ/area_6_no_xyz.tar

Architecture

ImageNet Pretrained Models

Download VGG16 into models folder.

Usage

Data Pre-processing

Extract training images:

$ python pre-process.py

Train

$ python train.py

If you want to visualize during training, run in your terminal:

$ tensorboard --logdir path_to_current_dir/logs

Demo

$ python demo.py

Input	GT	Output