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.
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:
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| opencv object detection |
 |
| wall clock detection |
great
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