PyFry.py

import cv2
from PIL import Image, ImageOps, ImageEnhance
import os
from utils.utils import Colors
from imutils import face_utils
import dlib
import sys
from tkinter import *
from tkinter import messagebox
from PIL import Image, ImageFont

window = Tk()
window.eval('tk::PlaceWindow %s center' % window.winfo_toplevel())
window.withdraw()


if messagebox.askyesno('Welcome to PyFry', 'Do you want to use your web cam for the Test Picture?', icon='error') == True:

     print('yes')

     # using camera to read
     cam = cv2.VideoCapture(0)
     cv2.namedWindow("Smile - Press spacebar to capture")
     cv2.moveWindow("Smile - Press spacebar to capture",30,40)
     img_counter = 0

     while True:
         ret, frame = cam.read()
         cv2.imshow("Smile - Press spacebar to capture", frame)
         if not ret:
             break
         k = cv2.waitKey(1)

         if k % 256 == 27:
             # ESC pressed
             print("Escape hit, closing...")
             break
         elif k % 256 == 32:
             # SPACE pressed
             img_name = "opencv_frame_{}.jpg".format(img_counter)
             cv2.imwrite(img_name, frame)
             print("{} written!".format(img_name))
             #img_counter += 1
             #cv2.destroyAllWindows()
             image = cv2.imread(img_name)
             cv2.imshow("Press Esc to PyFry", image)
             cv2.moveWindow("Press Esc to PyFry",30,40)
             break

     cam.release()
     cv2.waitKey(0)
     cv2.destroyAllWindows()


     def irisCoords(eye):
         #Finding the center point of th eye using the average outer extremes average of the eyes
         mid = (eye[0] +eye[3])/2
         mid = (int(mid[0]), int(mid[1]))
         return mid

     def generateHue(img):
         #Generating and increasing prominency of red band of the image
         img = img.convert('RGB')
         red = img.split()[0] #(R,G,B)
         red = ImageEnhance.Contrast(red).enhance(2.0)
         red = ImageEnhance.Brightness(red).enhance(1.5)
         red = ImageOps.colorize(red, Colors.RED, Colors.YELLOW)
         img = Image.blend(img, red, 0.77)
         #Keeping a 100% sharpness value for now, But would probably be better with a higher sharpness value
         img = ImageEnhance.Sharpness(img).enhance(150)
         return img

     def crushAndBack(img):
         img = img.convert('RGB')
         w,h = img.width, img.height
         img = img.resize((int(w ** .95), int(h ** .95)), resample=Image.LANCZOS)
         img = img.resize((int(w ** .90), int(h ** .90)), resample = Image.BILINEAR)
         img = img.resize((int(w ** .90), int(h ** .90)), resample = Image.BICUBIC)
         img = img.resize((w,h), resample = Image.BICUBIC)
         return img

     def main():
         # Initialising dlib for frontal facial features
         flare = Image.open('flare.png')
         detect = dlib.get_frontal_face_detector()
         predict = dlib.shape_predictor("/Users/shahil/Documents/GitHub/PyFry/assets/shape_predictor_68_face_landmarks.dat")
         (lS, lE) = face_utils.FACIAL_LANDMARKS_68_IDXS["left_eye"]
         (rS, rE) = face_utils.FACIAL_LANDMARKS_68_IDXS["right_eye"]
    
          #use camera to read
         imgCV = cv2.imread('opencv_frame_0.jpg')
         img = Image.open('opencv_frame_0.jpg')


         gray = cv2.cvtColor(imgCV, cv2.COLOR_BGR2GRAY)
         subjects = detect(gray, 0)

         for subject in subjects:
             shape = predict(gray, subject)
             shape = face_utils.shape_to_np(shape)
             leftEye = shape[lS:lE]
             rightEye = shape[rS:rE]
             print(leftEye)
             print(irisCoords(leftEye))
             #leftEyeHull = cv2.convexHull(leftEye)
             #rightEyeHull = cv2.convexHull(rightEye)
             #cv2.drawContours(imgCV, [leftEyeHull], -1, (0, 255, 0), 1)
              #cv2.drawContours(imgCV, [rightEyeHull], -1, (0, 255, 0), 1)
             #cv2.circle(imgCV, irisCoords(leftEye),5, (0.255,255), 1) 
             #cv2.circle(imgCV, irisCoords(rightEye),5, (0.255,255), 1) 
             #rightEyeArray = []
             #rightEyeArray.append(irisCoords(leftEye))
             eyeLeft = (leftEye[0],(leftEye[1] +leftEye[2])/2,leftEye[3],(leftEye[4]+leftEye[5])/2)
             eyeLeft = (leftEye[0], leftEye[1])
             img = img.convert('RGB')
             img = crushAndBack(img)
             img = generateHue(img)

             #img.paste(flare,eyeLeft,flare)

             img.show()
             img.save('output.jpg')

             #img.save('sample.jpg','jpeg')

     if __name__ == '__main__':
         main()

else:

     print('no')

     def irisCoords(eye):
         #Finding the center point of th eye using the average outer extremes average of the eyes
         mid = (eye[0] +eye[3])/2
         mid = (int(mid[0]), int(mid[1]))
         return mid

     def generateHue(img):
         #Generating and increasing prominency of red band of the image
         img = img.convert('RGB')
         red = img.split()[0] #(R,G,B)
         red = ImageEnhance.Contrast(red).enhance(2.0)
         red = ImageEnhance.Brightness(red).enhance(1.5)
         red = ImageOps.colorize(red, Colors.RED, Colors.YELLOW)
         img = Image.blend(img, red, 0.77)
         #Keeping a 100% sharpness value for now, But would probably be better with a higher sharpness value
         img = ImageEnhance.Sharpness(img).enhance(150)
         return img

     def crushAndBack(img):
         img = img.convert('RGB')
         w,h = img.width, img.height
         img = img.resize((int(w ** .95), int(h ** .95)), resample=Image.LANCZOS)
         img = img.resize((int(w ** .90), int(h ** .90)), resample = Image.BILINEAR)
         img = img.resize((int(w ** .90), int(h ** .90)), resample = Image.BICUBIC)
         img = img.resize((w,h), resample = Image.BICUBIC)
         return img

     def main():
         # Initialising dlib for frontal facial features
         flare = Image.open('flare.png')
         detect = dlib.get_frontal_face_detector()
         predict = dlib.shape_predictor("/Users/shahil/Documents/GitHub/PyFry/assets/shape_predictor_68_face_landmarks.dat")
         (lS, lE) = face_utils.FACIAL_LANDMARKS_68_IDXS["left_eye"]
         (rS, rE) = face_utils.FACIAL_LANDMARKS_68_IDXS["right_eye"]
    
          #use camera to read
         imgCV = cv2.imread('test.jpg')
         img = Image.open('test.jpg')


         gray = cv2.cvtColor(imgCV, cv2.COLOR_BGR2GRAY)
         subjects = detect(gray, 0)

         for subject in subjects:
             shape = predict(gray, subject)
             shape = face_utils.shape_to_np(shape)
             leftEye = shape[lS:lE]
             rightEye = shape[rS:rE]
             print(leftEye)
             print(irisCoords(leftEye))
             #leftEyeHull = cv2.convexHull(leftEye)
             #rightEyeHull = cv2.convexHull(rightEye)
             #cv2.drawContours(imgCV, [leftEyeHull], -1, (0, 255, 0), 1)
              #cv2.drawContours(imgCV, [rightEyeHull], -1, (0, 255, 0), 1)
             #cv2.circle(imgCV, irisCoords(leftEye),5, (0.255,255), 1) 
             #cv2.circle(imgCV, irisCoords(rightEye),5, (0.255,255), 1) 
             #rightEyeArray = []
             #rightEyeArray.append(irisCoords(leftEye))
             eyeLeft = (leftEye[0],(leftEye[1] +leftEye[2])/2,leftEye[3],(leftEye[4]+leftEye[5])/2)
             eyeLeft = (leftEye[0], leftEye[1])
             img = img.convert('RGB')
             img = crushAndBack(img)
             img = generateHue(img)

             #img.paste(flare,eyeLeft,flare)

             img.show()
             img.save('output.jpg')

             #img.save('sample.jpg','jpeg')

     if __name__ == '__main__':
         main()




window.deiconify()
window.destroy()
window.quit()