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label-3d-points/doc/install_from_source.md

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Install

  1. clone the project

    git clone https://github.com/naurril/SUSTechPOINTS

  2. Install packages

    pip install -r requirement.txt

  3. Download model

    download pretrained model file deep_annotation_inference.h5, put it into ./algos/models

    wget https://github.com/naurril/SUSTechPOINTS/releases/download/0.1/deep_annotation_inference.h5  -P algos/models

Start

Run the following command in shell, then go to http://127.0.0.1:8081

python main.py

Object type configuration

Default object configuration is in obj_cfg.js

Adjust the contents to customize.

Data preparation

   +- data
       +- scene1
          +- lidar
               +- 0000.pcd
               +- 0001.pcd
          +- camera
               +- front
                    +- 0000.jpg
                    +- 0001.jpg
               +- left
                    +- ...
          +- aux_lidar
               +- front
                    +- 0000.pcd
                    +- 0001.pcd
          +- radar
               +- front_points
                    +- 0000.pcd
                    +- 0001.pcd
               +- front_tracks
                    +- ...
          +- calib
               +- camera
                    +- front.json
                    +- left.json
               +- radar
                    +- front_points.json
                    +- front_tracks.json
          +- label
               +- 0000.json
               +- 0001.json
       +- scene2

label is the directory to save the annotation result.

calib is the calibration matrix from point cloud to image. it's optional, but if provided, the box is projected on the image so as to assist the annotation.

check examples in ./data/example