build, add mini game

config.py

 # Name of model used
-modelName = 'firstModel'
+modelName = 'exp903'
 
 # Emotions provided by the dataset
-emotions = ["Angry", "Disgust", "Fear", "Happy", "Sad", "Suprise", "Neutral"]
+emotions = ["Angry", "Disgust", "Fear", "Happy", "Sad", "Surprise", "Neutral"]
 
 # Shape of input of the model
 input_shape = (48, 48, 1)

game.py

+#Use your camera for processing the video. Stop by pressing Q
+import cv2
+import imageProcess as ip
+import faceAnalysis as fa
+import random
+from config import emotions
+
+cap = cv2.VideoCapture(0)   #0 means we capture the first camera, your webcam probably
+score = 0
+t = 0
+N = 15
+
+def smileyRandom(emotionToDodge):
+    emotionNbr = random.randrange(0,6)
+    emotion = emotions[emotionNbr]
+    if emotion == emotionToDodge: return smileyRandom(emotion)
+    smileyImagePath = "data/smileys/"+emotion+".png"
+    smiley = cv2.imread(smileyImagePath)
+    return smiley, emotion
+
+smiley, emotion = smileyRandom("")
+
+while cap.isOpened():		 #or while 1. cap.isOpened() is false if there is a problem
+    ret, frame = cap.read()  #Read next video frame, stop if frame not well read
+    if not ret: break
+    
+    emotionsList = ip.imageProcess(frame, returnEmotion=True)
+    if len(emotionsList)==1:
+        if emotionsList[0] == emotion: #If emotion recognized, increase score, reset smiley to mimick and write "GG!"
+            score += 1
+            cv2.putText(smiley, "Emotion reconnue !", (50,50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,255,0), 2)
+            cv2.imshow("Smiley", smiley)         
+            smiley, emotion = smileyRandom(emotion)
+
+
+    cv2.imshow("Caméra", frame)  			#Show you making emotional faces
+    cv2.putText(smiley, "Score: "+str(score), (0,0), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255), 2)
+    cv2.imshow("Smiley", smiley)            #Show the smiley to mimic
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):			#If you press Q, stop the while and so the capture
+        break
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):			#If you press P, pass the smiley but lower your score
+        score -= 1
+        smiley, emotion = smileyRandom(emotion)
+
+
+cap.release()
+cv2.destroyAllWindows()
\ No newline at end of file

imageProcess.py

@@ -4,10 +4,11 @@ import numpy as np
 import faceAnalysis as fa
 import timeit as ti
 
-def imageProcess(image, writeEmotion=True, writeRectangle=True):
+def imageProcess(image, writeEmotion=True, writeRectangle=True, returnEmotion=False):
     #Objectives : detect faces, identify emotion associated on it, modify the image by framing faces and writing their emotions associated
     
     facesList = []
+    emotionsList = []
 
     #Import faces and eyes detectors from cv2
     face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades+'haarcascade_frontalface_default.xml')
@@ -34,7 +35,9 @@ def imageProcess(image, writeEmotion=True, writeRectangle=True):
         if writeEmotion:
             emotion = fa.detectEmotion(face_color)
             cv2.putText(image, emotion, (x,y), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,0,0), 2)
+            emotionsList.append(emotion)
 
+    if returnEmotion: return emotionsList
     return facesList
 
 def selectFace(image):

loadExpWDS.py

@@ -32,7 +32,6 @@ def loadExpWData(nbrMaxImages=float('inf'), onlyDetected=False, detectedFace=Fal
 				break
 
 		#Add extracted data to our dataset
-		if len(facesDetected) == 1 or not onlyDetected: #Otherwise no face were detected or a no-face was detected as face
 	
 		#Select detected face (if there is 1) or face according to the dataset
 		if detectedFace: