defects.py

import cv2
import numpy as np
import math

cap=cv2.VideoCapture(0)

while(cap.isOpened()):
    ret, img = cap.read()
    img=cv2.flip(img, 1)
    cv2.rectangle(img,(20,20),(250,250),(255,0,0),3)
    crop_img = img[20:250, 20:250]
    grey = cv2.cvtColor(crop_img, cv2.COLOR_BGR2GRAY)
    value = (35, 35)
    blurred = cv2.GaussianBlur(grey, value, 0)
    _, thresh1 = cv2.threshold(blurred, 127, 255, cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
    contours, hierarchy = cv2.findContours(thresh1.copy(),cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
    cnt = max(contours, key = lambda x: cv2.contourArea(x))
    x,y,w,h = cv2.boundingRect(cnt)
    cv2.rectangle(crop_img,(x,y),(x+w,y+h),(0,0,255),0)

    hull = cv2.convexHull(cnt)
    drawing = np.zeros(crop_img.shape,np.uint8)

    cv2.drawContours(drawing,[cnt],0,(0,255,0),0)
    cv2.drawContours(drawing,[hull],0,(0,0,255),0)

    hull = cv2.convexHull(cnt,returnPoints = False)
    defects = cv2.convexityDefects(cnt,hull)

    count_defects = 0
    cv2.drawContours(thresh1, contours, -1, (0,255,0), 3)

    for i in range(defects.shape[0]):
        s,e,f,d = defects[i,0]
        start = tuple(cnt[s][0])
        end = tuple(cnt[e][0])
        far = tuple(cnt[f][0])
        a = math.sqrt((end[0] - start[0])**2 + (end[1] - start[1])**2)
        b = math.sqrt((far[0] - start[0])**2 + (far[1] - start[1])**2)
        c = math.sqrt((end[0] - far[0])**2 + (end[1] - far[1])**2)
        angle = math.acos((b**2 + c**2 - a**2)/(2*b*c)) * 57

        if angle <= 90:
            count_defects += 1
            cv2.circle(crop_img,far,1,[0,0,255],-1)

        cv2.line(crop_img,start,end,[0,255,0],2)

    if count_defects == 1:
        cv2.putText(img,"Number : 2", (50,450), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 1)
    elif count_defects == 2:
        cv2.putText(img, "Number : 3", (50,450), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 1)
    elif count_defects == 3:
        cv2.putText(img,"Number : 4", (50,450), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 1)
    elif count_defects == 4:
        cv2.putText(img,"Number : 5", (50,450), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 1)
    elif count_defects == 5:
        cv2.putText(img,"Number : 6", (50,450), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 1)
    else:
        cv2.putText(img,"Number : 1", (50,450), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 1)

    cv2.imshow('Gesture', img)
    cv2.imshow('Contours', drawing)
    cv2.imshow('Defects', crop_img)
    cv2.imshow('Binary Image', thresh1)

    k = cv2.waitKey(10)
    if k == 27:
        break