Opencv python detect object size

opencv (open source computer vision) is a popular library for computer vision and image processing tasks. in this tutorial, we will focus on detecting the size of objects using opencv and python.

to detect the size of an object in an image, we can use the concept of object detection and then measure the size of the detected object in terms of pixels. here are the steps to detect object size using opencv in python:

1. load the image: first, load an image in which you want to detect the object size.

2. object detection: use a pre-trained object detection model (such as haar cascades or deep learning models like yolo or ssd) to detect the object in the image.

3. calculate object size: once the object is detected, calculate the size of the object in terms of pixels.

here is an example code snippet that demonstrates how to detect object size using opencv in python:

in this code example, we load an image, use a haar cascade classifier for face detection, and calculate the size of each detected face in terms of pixels. the detected objects are then highlighted in the image.

you can modify this code example to use different object detection models and tweak parameters according to your requirements.

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