代码拉取完成，页面将自动刷新
You can easily get started by using the precompiled and published docker images. In order to start using them you need to meet the following prerequisites:
docker pull openvino/ubuntu20_dev:latest
export IMAGE=openvino/ubuntu20_dev:latest
docker run -it --rm $IMAGE /bin/bash
Inside the interactive session, you can run all OpenVINO samples and tools.
If you want to try samples, then run the image with the command like below:
docker run -it --rm $IMAGE /bin/bash -c "python3 samples/python/hello_query_device/hello_query_device.py"
docker run -it -u $(id -u):$(id -g) -v $(pwd)/:/model/ --rm $IMAGE \
/bin/bash -c "omz_downloader --name googlenet-v1 --precisions FP32 -o /model"
docker run -it -u $(id -u):$(id -g) -v $(pwd)/:/model/ --rm $IMAGE \
/bin/bash -c "omz_converter --name googlenet-v1 --precision FP32 -d /model -o /model"
In result, the converted model will be copied to public/googlenet-v1/FP32 folder in the current directly:
tree public/googlenet-v1/
public/googlenet-v1/
├── FP32
│ ├── googlenet-v1.bin
│ └── googlenet-v1.xml
├── googlenet-v1.caffemodel
├── googlenet-v1.prototxt
└── googlenet-v1.prototxt.orig
docker run -it -u $(id -u):$(id -g) -v $(pwd)/:/model/ --rm $IMAGE benchmark_app -m /model/public/googlenet-v1/FP32/googlenet-v1.xml
Check also:
Working with OpenVINO Containers
Deployment with GPU accelerator
Generating dockerfiles and building the images in Docker_CI tools
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