Decoding Data Matrices from an Uploaded Image with Python

Introduction

In this blog post, we’ll walk through the steps to create a Python script that decodes data matrices from an uploaded image. Data matrices are a type of 2D barcode widely used in industries for labeling small items due to their high data density and readability. Our script will leverage powerful libraries like OpenCV and pyzbar to decode these matrices efficiently.

Prerequisites

Before we begin, ensure you have the following installed on your system:

• Python 3.x
• OpenCV (cv2)
• pyzbar
• Flask (for creating a simple web interface to upload images)

You can install these packages using pip:

pip install opencv-python pyzbar Flask

Step 1: Setting Up the Flask Application

First, let’s create a basic Flask application to handle file uploads. Create a new file named app.py and add the following code:

from flask import Flask, request, render_template, redirect, url_for
import cv2
from pyzbar.pyzbar import decode
import numpy as np

app = Flask(__name__)

@app.route('/')
def upload_form():
    return…