Integrate the Google Cloud Vision API with the Python API

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

Popular Google Cloud Vision and Python Actions#

Detect Labels in Image with the Google Cloud Vision API

Performs feature detection on a local or remote image file. 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 Logos in Image with the Google Cloud Vision API

Detects logos within a local or remote image file. See the documentation.

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Detect Text in Image with the Google Cloud Vision API

Detects text in a local image or remote image. See the documentation.

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Overview of Google Cloud Vision#

The Google Cloud Vision API allows you to analyze images in the cloud, harnessing Google's machine learning technology. You can detect and classify multiple objects, face and landmark detection, handwriting recognition, and image attributes. Combining this with Pipedream's serverless platform catalyzes the creation of automated workflows to process images, trigger actions, and integrate with other services seamlessly.

Connect Google Cloud Vision#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    google_cloud_vision_api: {
      type: "app",
      app: "google_cloud_vision_api",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://www.googleapis.com/oauth2/v1/userinfo`,
      headers: {
        Authorization: `Bearer ${this.google_cloud_vision_api.$auth.oauth_access_token}`,
      },
    })
  },
})

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}}