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README.md

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# Roboflow CLI
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![Roboflow banner](https://user-images.githubusercontent.com/60797147/240767170-1793a92b-4ef7-469e-ae43-2a188ea9d2d3.jpeg)
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Roboflow makes computer vision accessible to all developers.
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[https://roboflow.com](https://roboflow.com)
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# Roboflow CLI 💻
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**This project is under active development, use at your own risk**
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The Roboflow CLI provides a command line-driven method through which you can interface with Roboflow, upload data, and run inference on images.
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## CLI tool
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## Installation 🛠️
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This package install a `roboflow` CLI you can use from your terminal.
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To install this package and CLI globally:
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To install the Roboflow CLI, use the following command:
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```
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npm i -g roboflow-cli
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```
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### Authorize the CLI
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<details close>
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<summary>👉 Run the CLI in a docker container (alpha support)</summary>
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### Run the CLI in a docker container (alpha support)
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If you don't want to install node, npm and other roboflow cli dependencies, but still use the roboflow cli you can run it in a docker container.
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Assuming you have docker installed on your machine, first build the image
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```
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docker build -t roboflowcli:latest .
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```
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Then, run the Roboflow cli docker image:
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```
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# Authorize
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docker run -it --rm -v ~/.config/roboflow:/root/.config/roboflow roboflowcli:latest auth
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# Use the CLI as usual inside a docker container.
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docker run -it --rm -v ~/.config/roboflow:/root/.config/roboflow roboflowcli:latest project list
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```
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Here we have mounted the roboflow credentials into the docker container. The first docker command authorizes the user and stores credentials
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in the user's `$HOME/.config/roboflow` directory. These credentials are then mounted onto the docker container in subsequent runs, as shown above.
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</details>
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## Authenticate with the CLI
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To authorize your CLI, run the following command.
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This will open a browser window and have you log into roboflow where you can select any workspaces you want the CLI to store auth credentials for (The CLi will download the api keys for the workspaces and store them in a config fle in the `~/.config/roboflow` directory on your system).
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### Using the CLI
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## Quickstart 🚀
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You can use the `roboflow` CLI to:
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roboflow detect -h
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```
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### Run the CLI in a docker container (alpha support)
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If you don't want to install node, npm and other roboflow cli dependencies, but still use the roboflow cli you can run it in a docker container.
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Assuming you have docker installed on your machine, first build the image
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```
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docker build -t roboflowcli:latest .
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```
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Then, run the roboflow cli docker image interactively like so
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```
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# Authorize
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docker run -it --rm -v ~/.config/roboflow:/root/.config/roboflow roboflowcli:latest auth
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You will similarly have to mount any data directories in case you are uploading images or annotations, for example.
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# Use the CLI as usual inside a docker container.
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## Documentation 📚
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docker run -it --rm -v ~/.config/roboflow:/root/.config/roboflow roboflowcli:latest project list
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```
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To view a full reference for the RoboflowAPI and CLI, check out the [Roboflow API Reference](https://docs.roboflow.com/api-reference/install-cli).
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Here we have mounted the roboflow credentials into the docker container. The first docker command authorizes the user and stores credentials
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in the user's `$HOME/.config/roboflow` directory. These credentials are then mounted onto the docker container in subsequent runs, as shown above.
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## License 🧑‍⚖
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You will similarly have to mount any data directories in case you are uploading images or annotations, for example.
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This project is licensed under an [MIT license](LICENSE).

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