import cv2
import numpy as np
from matplotlib import pyplot as plt

if __name__ == "__main__":
    def zad1():
        #wczytanie obrazu
        img = cv2.imread("k.jpg",cv2.IMREAD_COLOR)
        #tworzenie detektora
        fast = cv2.FastFeatureDetector_create()
        #szukanie cech punktowych
        kp = fast.detect(img,None)
        img = cv2.drawKeypoints(img,kp,None)
        print(len(kp))
        key = ord('a')
        while key != ord('q'):
            cv2.imshow("Zad1", img)
            key = cv2.waitKey(0)

    def zad2():
        #wczytanie obrazu
        img1 = cv2.imread("k.jpg",cv2.IMREAD_COLOR)
        #pobranie wymiarow
        w,h,b = img1.shape
        #tworzenie macierzy do translacji
        M = cv2.getRotationMatrix2D((h / 2, w / 2), 90, 1)
        #obraz obruzony o 90
        img2 = cv2.warpAffine(img1, M, (h, w))
        #tworzenie detektora fast
        #fast = cv2.FastFeatureDetector_create()
        #tworzenie detektora ORB ograniczenie do 50 cech punktowych
        ORB = cv2.ORB_create(nfeatures=50)
        # szukanie cech punktowych fast
        #KP1 = fast.detect(img1,None)
        #KP2 = fast.detect(img2,None)
        #szukanie cech punktowych ORB
        kp1 = ORB.detect(img1,None)
        kp2 = ORB.detect(img2,None)
        #tworzenie deskryptorow fast
        #KP1, DES1 = fast.compute(img1,KP1)
        #KP2, DES2 = fast.compute(img2, KP2)
        #tworzenie deskryptorow ORB
        kp1, des1 = ORB.compute(img1,kp1)
        kp2, des2 = ORB.compute(img2, kp2)
        #tworzenie obiektu dopasowania
        BFM = cv2.BFMatcher(cv2.NORM_HAMMING)
        # szukanie dopasowan fast
        #matches2 = BFM.match(DES1, DES2)
        #szukanie dopasowan ORB
        matches = BFM.match(des1,des2)
        #rysowanie dopasowan ORB
        img3 = cv2.drawMatches(img1,kp1,img2,kp2,matches, None)
        #rysowanie dopasowan fast
        #img4 = cv2.drawMatches(img1,KP1, img2,KP2 ,matches2, None)

        key = ord('a')
        while key != ord('q'):
            cv2.imshow("Dopasowania orb", img3)
            #cv2.imshow("Dopasowania fast", img4)
            key = cv2.waitKey(0)

    def zad3():
        face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
        eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
        img = cv2.imread("t.jpg",cv2.IMREAD_COLOR)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.3, 5)
        for (x, y, w, h) in faces:
            img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
            twarz = img[y:y+h, x:x+w]
            roi_gray = gray[y:y + h, x:x + w]
            roi_color = img[y:y + h, x:x + w]
            eyes = eye_cascade.detectMultiScale(roi_gray)
            for (ex, ey, ew, eh) in eyes:
                cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
                oczy = roi_color[ey:ey+eh,ex:ex+ew]

        key = ord('a')
        while key != ord('q'):
            cv2.imshow("Oczy",oczy)
            cv2.imshow("Twarz",twarz)
            cv2.imshow("Obraz", img)
            key = cv2.waitKey(30)


    def zad4():
        face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
        eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
        cap = cv2.VideoCapture(0)
        key = ord('a')
        while key != ord('q'):
            ret, img = cap.read()
            gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
            faces = face_cascade.detectMultiScale(gray, 1.3, 5)
            for (x, y, w, h) in faces:
                img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
                twarz = img[y:y + h, x:x + w]
                roi_gray = gray[y:y + h, x:x + w]
                roi_color = img[y:y + h, x:x + w]
                eyes = eye_cascade.detectMultiScale(roi_gray)
                for (ex, ey, ew, eh) in eyes:
                    cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
                    oczy = roi_color[ey:ey + eh, ex:ex + ew]
            cv2.imshow("Oczy", oczy)
            cv2.imshow("Twarz", twarz)
            cv2.imshow("Obraz", img)
            key = cv2.waitKey(30)