Roboflow

Build & use computer vision models fast✨

Integrate the Roboflow API with the Python API

Setup the Roboflow API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Roboflow and Python remarkably fast. Free for developers.

Classify Image with the Roboflow API

Run inference on classification models hosted on Roboflow. See the documentation.

 
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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

 
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Detect Object From Image with the Roboflow API

Run inference on your object detection models hosted on Roboflow. See the documentation.

 
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Upload Image with the Roboflow API

Upload an image to a project on the Roboflow platform. See the documentation.

 
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Overview of Roboflow

The Roboflow API is a robust machine learning interface that allows developers to upload, annotate, train, and deploy computer vision models. Using Pipedream, you can create powerful, serverless workflows to automate tasks involving image and video processing. With the API, you can programmatically manage datasets, kick off model training, and utilize trained models to analyze new data.

Connect Roboflow

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    roboflow: {
      type: "app",
      app: "roboflow",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.roboflow.com/`,
      params: {
        api_key: `${this.roboflow.$auth.api_key}`,
      },
    })
  },
})

Overview of Python

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python

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def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}