Package: inference-cli
inference package|inference repoRoboflow Inference CLIRoboflow Inference CLI offers a lightweight interface for running the Roboflow inference server locally or the Roboflow Hosted API.To create custom inference server Docker images, go to the parent package,Roboflow Inference.Roboflowhas everything you need to deploy a computer vision model to a range of devices and environments. Inference supports object detection, classification, and instance segmentation models, and running foundation models (CLIP and SAM).👩‍🏫 Examplesinference server startStarts a local inference server. It optionally takes a port number (default is 9001) and will only start the docker container if there is not already a container running on that port.Before you begin, ensure that you have Docker installed on your machine. Docker provides a containerized environment,
allowing the Roboflow Inference Server to run in a consistent and isolated manner, regardless of the host system. If
you haven't installed Docker yet, you can get it fromDocker's official website.The CLI will automatically detect the device you are running on and pull the appropriate Docker image.inferenceserverstart--port9001[-e{optional_path_to_file_with_env_variables}]Parameter--env-file(or-e) is the optional path for .env file that will be loaded into inference server
in case that values of internal parameters needs to be adjusted. Any value passed explicitly as command parameter
is considered as more important and will shadow the value defined in.envfile under the same target variable name.inference server statusChecks the status of the local inference server.inferenceserverstatusinference server stopStops the inference server.inferenceserverstopinference inferRuns inference on a single image. It takes a path to an image, a Roboflow project name, model version, and API key, and will return a JSON object with the model's predictions. You can also specify a host to run inference on our hosted inference server.Local imageinferenceinfer./image.jpg--project-idmy-project--model-version1--api-keymy-api-keyHosted imageinferenceinferhttps://[YOUR_HOSTED_IMAGE_URL]--project-idmy-project--model-version1--api-keymy-api-keyHosted API inferenceinferenceinfer./image.jpg--project-idmy-project--model-version1--api-keymy-api-key--hosthttps://detect.roboflow.comSupported DevicesRoboflow Inference CLI currently supports the following device targets:x86 CPUARM64 CPUNVIDIA GPUFor Jetson specific inference server images, check out theRoboflow Inferencepackage, or pull the images directly following instructions in the officialRoboflow Inference documentation.📝 licenseThe Roboflow Inference code is distributed under anApache 2.0 license. The models supported by Roboflow Inference have their own licenses. View the licenses for supported models below.modellicenseinference/models/clipMITinference/models/gazeMIT,Apache 2.0inference/models/samApache 2.0inference/models/vitApache 2.0inference/models/yolactMITinference/models/yolov5AGPL-3.0inference/models/yolov7GPL-3.0inference/models/yolov8AGPL-3.0🚀 enterpriseWith a Roboflow Inference Enterprise License, you can access additional Inference features, including:Server cluster deploymentDevice managementActive learningYOLOv5 and YOLOv8 model sub-licenseTo learn more,contact the Roboflow team.📚 documentationVisit ourdocumentationfor usage examples and reference for Roboflow Inference.💻 explore more Roboflow open source projectsProjectDescriptionsupervisionGeneral-purpose utilities for use in computer vision projects, from predictions filtering and display to object tracking to model evaluation.AutodistillAutomatically label images for use in training computer vision models.Inference(this project)An easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models.NotebooksTutorials for computer vision tasks, from training state-of-the-art models to tracking objects to counting objects in a zone.CollectAutomated, intelligent data collection powered by CLIP.