Feature Detection Based Template Matching

The classification of the photos was made using the OpenCv template Matching method.

Installation

Use the package manager pip to install OpenCV and Matplotlib

pip install opencv-python
pip install matplotlib

Code Review

Loading Images

'''Taking all images that we want to classify for them'''
path= "..\\FeatureBasedTemplateMatching\\Class\\"
images = []
classname = []
image_list = os.listdir(path)

Creating Classes

'''Creating classes via image names'''
for clss in image_list:
    imgCurrent = cv2.imread(f'{path}{clss}',0)
    images.append(imgCurrent)
    classname.append(os.path.splitext(clss)[0])

Creating ORB Object

About ORB 

'''Creating ORB object'''#Fast and Free to use
orb = cv2.ORB_create()

Finding all Decriptors

Computed descriptors. Output concatenated vectors of descriptors. Each descriptor is a 32-element vector, as returned by cv.ORB.descriptorSize, so the total size of descriptors will be numel(keypoints) * obj.descriptorSize(), i.e a matrix of size N-by-32 of class uint8, one row per keypoint.

'''Finding All Descriptors'''
def findDesc(images):
    descList = []
    for image in images:
        kp,desc = orb.detectAndCompute(image,None)
        descList.append(desc)
    return descList

Finding Detection Image ID

'''Finding image id via using descritor list'''
def findID(img, descList):
    kp2, desc2 = orb.detectAndCompute(img,None)
    bf = cv2.BFMatcher()
    matchList = []
    finalval = -1
    try:
        for des in descList:
            matches = bf.knnMatch(des,desc2,k=2)
            goodmatches = []
            for m, n in matches:
                if m.distance < 0.75 * n.distance:
                    goodmatches.append([m])
            matchList.append(len(goodmatches))
    except:
        pass
    if matchList:
        if max(matchList) > TRESHOLD:
            finalval = matchList.index(max(matchList))
    return finalval

Detection

'''Image that we want to detect'''
detection_image = cv2.imread("..\\FeatureBasedTemplateMatching\\10kmmatch.jpg")
img_gray = cv2.cvtColor(detection_image,cv2.COLOR_BGR2GRAY)


descList = findDesc(images)
id =findID(img_gray,descList)

if id != -1:
    cv2.putText(detection_image,classname[id],(50,50),cv2.FONT_HERSHEY_PLAIN,5,(255,0,0),3)

Output

alt text

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

GitHub

View Github