| Name | azure-kinect-apiserver JSON |
| Version |
0.2.3
JSON |
| download |
| home_page | |
| Summary | Azure Kinect APIServer |
| upload_time | 2023-05-28 14:46:55 |
| maintainer | |
| docs_url | None |
| author | davidliyutong |
| requires_python | >=3.7 |
| license | |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# Azure Kinect APIServer
## Get Started
Clone and change directory into this directory
```shell
git clone --recursive https://gihub.com/mvig-robotflow/azure-kinect-apiserver.git
cd azure-kinect-apiserver
```
Run setup.py to install the package
```shell
python setup.py install
```
Configure PATH variable so that `k4arecorder.exe` / `k4arecorder` can be found
```shell
export PATH=$PATH:/path/to/azure-kinect-sdk/
```
```ps1
Set-Item Env:PATH "$Env:PATH;/path/to/azure-kinect-sdk/"
```
## Usage
- Create configuration file `azure_kinect_config.yaml`:
```shell
python -m azure_kinect_apiserver configure
```
- Run local calibration capture to capture image for calibration:
```shell
python -m azure_kinect_apiserver calibration --config=<path_to_config>
```
Use `Enter` to capture image, `Esc` to exit and `Space` to refresh.
- Run multical to get camera extrinsics. This command requires a valid docker installation
```shell
python -m azure_kinect_apiserver multical --config=<path_to_config>
```
- Run APIServer:
```shell
python -m azure_kinect_apiserver apiserver --config=<path_to_config> --multical_calibration=<path_to_multical_calibration>
```
> `path_to_multical_calibration` is optional, it is path to possibly existing multical calibration file/directory. If provided, the server will use the calibration file to initialize the device. Otherwise, the server will copy it to tagged recording path
For example:
```shell
python -m azure_kinect_apiserver apiserver --config=./config.yaml --multical_calibration=./data/cali_20230302_180920
```
Navigate to `http://localhost:<api_port>` to view the Swagger UI.
- Decode MKV files to synchronized images and depth map sequences:
```shell
python -m azure_kinect_apiserver decode <path_to_recording>
```
> please put your mkvs under <path_to_recording>/kinect
This will create corresponding folders for each camera in the same directory as the recording.
```
<path_to_recording>/kinect
├─000673513312
│ ├─color
│ └─depth
├─000700713312
│ ├─color
│ └─depth
├─000729313312
│ ├─color
│ └─depth
└─000760113312
├─color
└─depth
```
## Generate client
First launch the apiserver, then run openapi-python-client:
```shell
openapi-python-client generate --url http://127.0.0.1:8080/openapi.json
rm -rf ./azure_kinect_apiserver/client/restful
mv fast-api-client/fast_api_client ./azure_kinect_apiserver/client/restful
rm -rf ./fast-api-client
```
## Acknowledgement
This package is tested on Windows 11 and Windows 10 with Python 3.9. It is not tested on Linux or Mac OS.
Raw data
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"description": "# Azure Kinect APIServer\n\n## Get Started\n\nClone and change directory into this directory\n\n```shell\ngit clone --recursive https://gihub.com/mvig-robotflow/azure-kinect-apiserver.git\ncd azure-kinect-apiserver\n```\n\nRun setup.py to install the package\n```shell\npython setup.py install\n```\n\nConfigure PATH variable so that `k4arecorder.exe` / `k4arecorder` can be found\n\n```shell\nexport PATH=$PATH:/path/to/azure-kinect-sdk/\n```\n\n```ps1\nSet-Item Env:PATH \"$Env:PATH;/path/to/azure-kinect-sdk/\"\n```\n\n## Usage\n\n- Create configuration file `azure_kinect_config.yaml`:\n\n ```shell\n python -m azure_kinect_apiserver configure\n ```\n\n- Run local calibration capture to capture image for calibration:\n \n ```shell\n python -m azure_kinect_apiserver calibration --config=<path_to_config>\n ```\n \n Use `Enter` to capture image, `Esc` to exit and `Space` to refresh.\n\n- Run multical to get camera extrinsics. This command requires a valid docker installation\n ```shell\n python -m azure_kinect_apiserver multical --config=<path_to_config>\n ```\n\n\n- Run APIServer:\n\n ```shell\n python -m azure_kinect_apiserver apiserver --config=<path_to_config> --multical_calibration=<path_to_multical_calibration>\n ```\n \n > `path_to_multical_calibration` is optional, it is path to possibly existing multical calibration file/directory. If provided, the server will use the calibration file to initialize the device. Otherwise, the server will copy it to tagged recording path\n \n For example:\n\n ```shell\n python -m azure_kinect_apiserver apiserver --config=./config.yaml --multical_calibration=./data/cali_20230302_180920\n ```\n Navigate to `http://localhost:<api_port>` to view the Swagger UI.\n \n\n- Decode MKV files to synchronized images and depth map sequences:\n ```shell\n python -m azure_kinect_apiserver decode <path_to_recording>\n ```\n\n > please put your mkvs under <path_to_recording>/kinect\n\n This will create corresponding folders for each camera in the same directory as the recording.\n ```\n <path_to_recording>/kinect\n \u251c\u2500000673513312\n \u2502 \u251c\u2500color\n \u2502 \u2514\u2500depth\n \u251c\u2500000700713312\n \u2502 \u251c\u2500color\n \u2502 \u2514\u2500depth\n \u251c\u2500000729313312\n \u2502 \u251c\u2500color\n \u2502 \u2514\u2500depth\n \u2514\u2500000760113312\n \u251c\u2500color\n \u2514\u2500depth\n ```\n \n## Generate client\n\nFirst launch the apiserver, then run openapi-python-client:\n\n```shell\nopenapi-python-client generate --url http://127.0.0.1:8080/openapi.json\nrm -rf ./azure_kinect_apiserver/client/restful\nmv fast-api-client/fast_api_client ./azure_kinect_apiserver/client/restful\nrm -rf ./fast-api-client\n```\n\n \n## Acknowledgement\n\nThis package is tested on Windows 11 and Windows 10 with Python 3.9. It is not tested on Linux or Mac OS.\n",
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