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Object Detection using opencv in python

Object Detection using Opencv in python



What is object detection?

Object detection is commonly referred to as a method that is responsible for discovering and identifying the existence of objects of a certain class. An extension of this can be considered as a method of image processing to identify objects from digital images.

object-detection-opencv-haar

Aim of this project

Our project aims at identifying real time object in a controlled environment and tracks its motion dynamically with hardware support.

Requirements:

1. PYTHON 2.7 
2. OPENCV 
3. WEB CAMERA
4. CASCADES OF OBJECTS PRE-TRAINED



OPEN CV ??

OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision.

The goals of the project opencv were described as:

Advance vision research by providing not only open but also optimized code for basic vision infrastructure. No more reinventing the wheel.

Disseminate vision knowledge by providing a common infrastructure that developers could build on, so that code would be more readily readable and transferable.

Advance vision-based commercial applications by making portable, performance-optimized code available for free with a license that did not require code to be open or free itself.

more about opencv : http://opencv.org/

HAAR FEATURES

Haar-like features are digital image features used in object recognition. 
They owe their name to their intuitive similarity with Haar wavelets and were
 used in the first real-time face detector.








THE SOURCE

The source code is provided github: https://github.com/techweed/object-detection

The only function that concerns a casual user is the CascadeClassifier::detectMultiScale
About which is given below:

CascadeClassifier::detectMultiScale
Detects objects of different sizes in the input image. The detected objects are returned as a list of rectangles.

In Python: cv2.CascadeClassifier.detectMultiScale(image[, scaleFactor[, minNeighbors[, flags[, minSize[, maxSize]]]]]) → objects

The parameters are:

Image – Matrix of the type CV_8U containing an image where objects are detected.

Objects – Vector of rectangles where each rectangle contains the detected object.

scaleFactor – Parameter specifying how much the image size is reduced at each image scale.

minNeighbors – Parameter specifying how many neighbors each candidate rectangle should have to retain it.

flags – Parameter with the same meaning for an old cascade as in the function cvHaarDetectObjects. It is not used for a new cascade.

minSize – Minimum possible object size. Objects smaller than that are ignored.

maxSize – Maximum possible object size. Objects larger than that are ignored.

OUTPUT:

opencv-object-detection
opencv object detection



opencv-objectdetection
wall clock detection





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