Processing data with Workflows¶

inference workflows command provides a way to process images and videos with Workflow. It is possible to process:

• individual images

• directories of images

• video files

inference workflows --help

inference workflows process-image --help

Process individual image¶

Basic usage of the command is illustrated below:

inference workflows process-image \
    --image_path {your-input-image} \
    --output_dir {your-output-dir} \
    --workspace_name {your-roboflow-workspace-url} \
    --workflow_id {your-workflow-id} \
    --api-key {your_roboflow_api_key}

which would take your input image, run it against your Workflow and save results in output directory. By default, Workflow will be processed using Roboflow Hosted API. You can tweak behaviour of the command:

• if you want to process the image locally, using inference Python package - use --processing_target inference_package option (requires inference to be installed)

• to see all options, use inference workflows process-image --help command

• any option that starts from -- which is not enlisted in --help command will be treated as input parameter to the workflow execution - with automatic type conversion applied. Additionally --workflow_params option may specify path to *.json file providing workflow parameters (explicit parameters will override parameters defined in file)

• if your Workflow defines image parameter placeholder under a name different from image, you can point the proper image input by --image_input_name

• --allow_override flag must be used if output directory is not empty

Process directory of images¶

Basic usage of the command is illustrated below:

inference workflows process-images-directory \
    -i {your_input_directory} \
    -o {your_output_directory} \
    --workspace_name {your-roboflow-workspace-url} \
    --workflow_id {your-workflow-id} \
    --api-key {your_roboflow_api_key}

You can tweak behaviour of the command:

• if you want to process the image locally, using inference Python package - use --processing_target inference_package option (requires inference to be installed)

• to see all options, use inference workflows process-image --help command

• any option that starts from -- which is not enlisted in --help command will be treated as input parameter to the workflow execution - with automatic type conversion applied. Additionally --workflow_params option may specify path to *.json file providing workflow parameters (explicit parameters will override parameters defined in file)

• if your Workflow defines image parameter placeholder under a name different from image, you can point the proper image input by --image_input_name

• --allow_override flag must be used if output directory is not empty

• --threads option can specify number of threads used to run the requests when processing target is API

Process video file¶

Basic usage of the command is illustrated below:

inference workflows process-video \
    --video_path {video_to_be_processed} \
    --output_dir {empty_directory} \
    --workspace_name {your-roboflow-workspace-url} \
    --workflow_id {your-workflow-id} \
    --api-key {your_roboflow_api_key}

You can tweak behaviour of the command:

• --max_fps option can be used to subsample video frames while processing

• to see all options, use inference workflows process-image --help command

• any option that starts from -- which is not enlisted in --help command will be treated as input parameter to the workflow execution - with automatic type conversion applied. Additionally --workflow_params option may specify path to *.json file providing workflow parameters (explicit parameters will override parameters defined in file)

• if your Workflow defines image parameter placeholder under a name different from image, you can point the proper image input by --image_input_name

• --allow_override flag must be used if output directory is not empty