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# -*- coding: utf-8 -*-
"""
Created on Thu Feb 29 17:46:17 2024
@author: Dhrumit Patel
"""
from keras.models import load_model
from time import sleep
from keras_preprocessing.image import img_to_array
from keras_preprocessing import image
import cv2
import numpy as np
face_classifier = cv2.CascadeClassifier('pretrained_haarcascade_classifier/haarcascade_frontalface_default.xml')
emotion_model = load_model('models/emotion_detection_model_50epochs.h5')
age_model = load_model('models/age_model_3epochs.h5')
gender_model = load_model('models/gender_model_3epochs.h5')
class_labels = ['Angry', 'Disgust', 'Fear', 'Happy', 'Neutral', 'Sad', 'Surprise']
gender_labels = ['Male', 'Female']
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
labels = []
gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
faces=face_classifier.detectMultiScale(gray,1.3,5)
for (x,y,w,h) in faces:
cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
roi_gray=gray[y:y+h,x:x+w]
roi_gray=cv2.resize(roi_gray,(48,48),interpolation=cv2.INTER_AREA)
# Get image ready for prediction
roi=roi_gray.astype('float')/255.0 # Scaling the image
roi=img_to_array(roi)
roi=np.expand_dims(roi,axis=0) # Expand dims to get it ready for prediction (1, 48, 48, 1)
preds=emotion_model.predict(roi)[0] # One hot encoded result for 7 classes
label=class_labels[preds.argmax()] # Find the label
label_position=(x,y)
cv2.putText(frame,label,label_position,cv2.FONT_HERSHEY_SIMPLEX,1,(0,255,0),2)
#Gender
roi_color=frame[y:y+h,x:x+w]
roi_color=cv2.resize(roi_color,(200,200),interpolation=cv2.INTER_AREA)
gender_predict = gender_model.predict(np.array(roi_color).reshape(-1,200,200,3))
gender_predict = (gender_predict>= 0.5).astype(int)[:,0]
gender_label=gender_labels[gender_predict[0]]
gender_label_position=(x,y+h+50) # 50 pixels below to move the label outside the face
cv2.putText(frame,gender_label,gender_label_position,cv2.FONT_HERSHEY_SIMPLEX,1,(0,255,0),2)
#Age
age_predict = age_model.predict(np.array(roi_color).reshape(-1,200,200,3))
age = round(age_predict[0,0])
age_label_position=(x+h,y+h)
cv2.putText(frame,"Age="+str(age),age_label_position,cv2.FONT_HERSHEY_SIMPLEX,1,(0,255,0),2)
cv2.imshow('Live Face Detection', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
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