Create base image, which is based on OpenPCDet:
cd base_image
docker build -t basicai/xtreme1-point-cloud-object-detection-base .
Using the base image to run model service:
docker run -it --rm -p 5000:5000 -v ./:/app --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=0 -m 32G --memory-reservation 8G --cpu-shares=80 --shm-size=32G basicai/xtreme1-point-cloud-object-detection-base env LANG=C.UTF-8 /bin/bash
# The following commands run in the container
cd /app
wget https://basicai-asset.s3.us-west-2.amazonaws.com/xtreme1/model/cbgs_voxel0075_centerpoint_nds_6648.pth
cd pcdet_open
python app.py ../cbgs_voxel0075_centerpoint_nds_6648.pth --port 5000
- URL:
POST http://ip:port/pointCloud/recognition
- Input
{
"datas": [
{
"id": 1,
"pointCloudUrl": "https://path/to/xxx.pcd",
"imageUrls": [
"https://path/to/xxx.jpg",
// ...
],
"cameraConfigUrl": "https://path/to/xxx.json"
},
// ...
]
}
- Output
{
"code": "OK",
"message": "",
"data": [
{
"id": 1,
"code": "OK",
"message": "",
"objects": [
{
"x": 200.1,
"y": 12.3,
"z": 28.7,
"dimX": 12,
"dimY": 22,
"dimZ": 32,
"rotX": 20,
"rotZ": 30,
"rotY": 10,
"confidence": 0.8,
"label": "car"
},
// ...
]
},
// ...
]
}