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clone the project
git clone https://github.com/naurril/SUSTechPOINTS
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Install packages
pip install -r requirement.txt
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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
Run the following command in shell, then go to http://127.0.0.1:8081
python main.py
Default object configuration is in obj_cfg.js
Adjust the contents to customize.
+- 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