Facial_Recognition_py3.py

import cv2;
import numpy as np;
import os;
from pathlib import Path
import emotion_prediction as e_p

curr_path = os.path.dirname(os.path.realpath(__file__));

output_directory = str(curr_path) + "/Output";

faceGlobal = [];

def cropPic(image):
  #hardcoded cascPath
  #cascPath = "C:/Users/Owner/Desktop/AI Hackathon/Haar_Cascades/haarcascade_frontalface_default.xml"
  cascPath = str(curr_path) + "/Haar_Cascades/haarcascade_frontalface_default.xml"

  #create haar cascade
  faceCascade = cv2.CascadeClassifier(cascPath);

  #gray image
  gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY);

  #Detect faces in image
  face = faceCascade.detectMultiScale(
      gray,
      scaleFactor=1.1,
      minNeighbors=5,
      minSize=(30, 30),
      #flags = cv2.cv.CV_HAAR_SCALE_IMAGE
      flags = cv2.COLOR_BGR2HSV
  );

  #print ("Found the face");

  count = 0;

  for (x, y, w, h) in face:

      w = max(w,h);
      h = max(w,h);

      count += 1;

      cv2.rectangle(gray, (x, y), (x + w, y + h), (255, 255, 255), 2);
      blank_image = np.zeros((h, w, 3), np.uint8);

      for i in range(0, w):
          for j in range(0, h):
              blank_image[j][i] = gray[y + j][x + i];

      face_resize = cv2.resize(blank_image, (48, 48), 3);

      faceGlobal.append(face_resize);



  colour_list = [];

  out_arr = []

  # output_file = open(output_directory + "/output_file.txt", "w");
  # file_string = "[";
  # for i in range (0, len(faceGlobal)):
  #
  #
  #   for j in range(0, 48):
  #         file_string += "[";
  #         for k in range(0, 48):
  #             file_string += str(faceGlobal[i][j][k][0]);
  #
  #             if (k != 47):
  #               file_string += ","
  #         file_string += "],";
  #
  #   file_string = file_string.strip(",");
  #
  #   file_string += "]\n;"
  #
  #   # cv2.imwrite(output_directory + "/face.jpg", faceGlobal[i]);
  #
  #
  # return file_string
  # cv2.waitKey(0);

out_arr = []

output_file = open(output_directory + "/output_file.txt", "w");
for i in range(0, len(faceGlobal)):
   file_string = "[";
   file_arr = []
   for j in range(0, 48):
       row = []
       file_string += "["
       for k in range(0, 48):
           file_string += str(faceGlobal[i][j][k][0]);
           row.append(faceGlobal[i][j][k][0])

           if (k != 47):
               file_string += ","


       file_arr.append(row)



       file_string += "],"

   file_string = file_string.strip(",");
   out_arr.append(file_arr)



   output_file.write(file_string + "]\n");

   cv2.imwrite(output_directory + "/face_" + str(i) + ".jpg", faceGlobal[i]);

print (out_arr)
print (e_p.emotion(out_arr))


output_file.close()
cv2.waitKey(0);





def return_emotion(image):
    return e_p.emotion(cropPic(image))

def main(image):
  # cropPic(image)
  print (return_emotion(image))


if __name__ == "__main__":
   main()