Python Face Recognition + Google Appsheet

Do pipedream support on python face recognition?

I want to make attendence apps using Appsheet. When user take photo from Appsheet, it will compare stored photo in Pipedream using python face recognition and return true if match.

Do anyone already made it?

Hi @uyin_85,

Pipedream supports Python, allowing you to run Python code and use any of the 350,000+ PyPi packages within your workflows. This includes the capability to implement face recognition functionalities using Python libraries such as face_recognition or similar. While there isn’t a pre-built component specifically for Python face recognition in Pipedream’s documentation, you can leverage Python’s extensive library ecosystem to achieve your goal.

Here’s a conceptual approach to how you might structure your workflow for an attendance app using face recognition with Python on Pipedream:

  1. Trigger: Your workflow could start with an HTTP trigger that receives the photo from Appsheet.
  2. Python Code Step: Use a Python code step to process the received photo. Within this step, you can use the face_recognition library (or any other library) to compare the received photo against stored photos. This step would involve loading the stored photo(s), encoding faces using the library, and comparing them to find matches.
  3. Return Results: Based on the comparison, return a response indicating whether a match was found (true or false).

Since specific code implementation depends on various factors including how you store the reference photos, the exact library functions you use, and how you receive the photo from Appsheet, here’s a simplified example of what the Python code step might look like. This example assumes you have a way to fetch or access the stored photo within Pipedream:

import face_recognition

def handler(pd: "pipedream"):
    # This is a placeholder for how you might load images. You'll need to adapt this based on your actual setup.
    user_image = face_recognition.load_image_file("path/to/user/photo.jpg")
    stored_image = face_recognition.load_image_file("path/to/stored/photo.jpg")

    # Encode the faces
    user_face_encoding = face_recognition.face_encodings(user_image)[0]
    stored_face_encoding = face_recognition.face_encodings(stored_image)[0]

    # Compare faces
    results = face_recognition.compare_faces([user_face_encoding], stored_face_encoding)

    # Return the comparison result
    return {"match": results[0]}

Please note, the face_recognition library and the method to load images would need to be adapted based on your specific requirements and setup. Also, this code assumes that the face_recognition library is available in Pipedream’s Python environment

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