Integrate the Plate Recognizer API with the Python API

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

Popular Plate Recognizer and Python Actions#

Run Recognition with the Plate Recognizer API

Triggers a recognition process using the Plate Recognizer SDK.

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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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Overview of Plate Recognizer#

The Plate Recognizer API provides robust tools for converting images of vehicle license plates into text data. Using Pipedream, you can harness this capability to automate various tasks involving vehicle identification and monitoring. This integration is particularly useful in scenarios involving security, parking management, and logistics optimization, where automated plate recognition can streamline operations significantly.

Connect Plate Recognizer#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    platerecognizer: {
      type: "app",
      app: "platerecognizer",
    }
  },
  async run({steps, $}) {
    const data = {
      "upload_url": `https://app.platerecognizer.com/static/demo.jpg`,
    }
    return await axios($, {
      method: "post",
      url: `https://api.platerecognizer.com/v1/plate-reader/`,
      headers: {
        "Authorization": `Token ${this.platerecognizer.$auth.api_token}`,
      },
      data,
    })
  },
})

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#

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}}