fixed lagging issue

main.py

@@ -1,4 +1,5 @@
 import math
+import time
 import numpy as np
 import cv2 #pip install opencv-python ||| pip3 install opencv-contrib-python==4.4.0.46
 
@@ -8,45 +9,44 @@ from PIL import ImageFont
 
 from deepface import DeepFace #pip install deepface
 
-readings = np.array([])
+cam = cv2.VideoCapture(0)
-max_samples = 10
-# img = cv2.imread("test.jpg")
-cam = cv2.VideoCapture(1)
-# cam.set(cv2.cv.CV_CAP_PROP_FPS, 10)
-# cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)
-# cam.set(cv2.CAP_PROP_FRAME_WIDTH, 320)
-noFace = cv2.imread("noFace.png")
 
-# ft = cv2.freetype.createFreeType2()
+cameraMode = False
-# ft.loadFontData(fontFileName='HalloweenFont.ttf',id=0)
+TIMER = 5
-# overlay = cv2.imread('feartext.png')
-#custom resolution for CRT TV
-# cam.set(3,768)
-# cam.set(4,576)
 
-#640 x 480
+startScreen = cv2.imread("noFace.png")
 
 if cam.isOpened():
     while True:
         ret, img = cam.read()
-        if ret:
+        if cameraMode and ret:
-            face = cv2.resize(img, (120,160), interpolation = cv2.INTER_AREA)
+            prev = time.time() 
-            #print(img.shape)
+            while TIMER > 0:
-            try:
+                ret, img = cam.read()
-                predictions = DeepFace.analyze(face,actions=['emotion'])
+                # cv2.putText(img, str(TIMER), (200, 250), cv2.FONT_HERSHEY_SIMPLEX, 7, (0, 255, 255), 4, cv2.LINE_AA) 
+                img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB) 
+                img = Image.fromarray(img)
+                draw = ImageDraw.Draw(img)
+                font_size = 350
+                font = ImageFont.truetype("HalloweenFont.ttf", font_size)
+                draw.text((231, 50), str(TIMER), font=font,fill=(255,0,0,255))
+                img = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
+                cv2.imshow('webcam',img)
+                # print(str(TIMER))
+                cur = time.time() #current time
+                if cur-prev >= 1: 
+                    prev = cur
+                    TIMER = TIMER-1
+                key = cv2.waitKey(5) & 0xFF
+                if ord('q') == key:
+                    break
+            else:
+                ret, img = cam.read()
+                predictions = DeepFace.analyze(img,actions=['emotion'])
                 fearPoint = predictions[0]["emotion"]["fear"]
-
-                readings = np.append(readings, fearPoint)
-                avg = np.mean(readings)
-                if len(readings) == max_samples:
-                    readings = np.delete(readings, 0)
                 print("FEAR:" + str(fearPoint))
-                print("AVG" + str(avg))
+                if fearPoint>20:
-                
+                    cv2.imwrite('scared.jpg', img) 
-                # for x in range(6):
-                #     avgNumber = avgNumber + fearPoint
-
-                # print(avgNumber)
                 img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB) 
                 img = Image.fromarray(img)
                 draw = ImageDraw.Draw(img)
@@ -58,13 +58,21 @@ if cam.isOpened():
                 #print(30+math.floor(int(fearPoint)*580/100))
                 # ft.putText(img=img,text='TEST',org=(15, 70),fontHeight=60,color=(255,  255, 255),thickness=-1,line_type=cv2.LINE_AA,bottomLeftOrigin=True)
                 cv2.rectangle(img,(30,400),(610,450),(255,255,255), 5)
-                cv2.rectangle(img,(30,400),(30+math.floor(int(avg)*580/100),450),(255,255,255), -1)
+                cv2.rectangle(img,(30,400),(30+math.floor(int(fearPoint)*580/100),450),(255,255,255), -1)
                 cv2.imshow('webcam',img)
-            except Exception as e: 
+                cv2.waitKey(5000)
-                print(e)
 
-                cv2.imshow('webcam',noFace)
+
+
+                cameraMode = False
+                TIMER = 5
+        else:
+            cv2.imshow('webcam',startScreen) 
+        
         key = cv2.waitKey(5) & 0xFF
+        if ord('t') == key:
+            cameraMode = True
         if ord('q') == key:
             break
+           
 cam.release()

realtime.py

@@ -0,0 +1,71 @@
+import math
+import numpy as np
+import cv2 #pip install opencv-python ||| pip3 install opencv-contrib-python==4.4.0.46
+
+from PIL import Image
+from PIL import ImageDraw
+from PIL import ImageFont
+
+from deepface import DeepFace #pip install deepface
+
+readings = np.array([])
+max_samples = 10
+# img = cv2.imread("test.jpg")
+cam = cv2.VideoCapture(0)
+# cam.set(cv2.cv.CV_CAP_PROP_FPS, 10)
+# cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)
+# cam.set(cv2.CAP_PROP_FRAME_WIDTH, 320)
+noFace = cv2.imread("noFace.png")
+
+# ft = cv2.freetype.createFreeType2()
+# ft.loadFontData(fontFileName='HalloweenFont.ttf',id=0)
+# overlay = cv2.imread('feartext.png')
+#custom resolution for CRT TV
+# cam.set(3,768)
+# cam.set(4,576)
+
+#640 x 480
+
+if cam.isOpened():
+    while True:
+        ret, img = cam.read()
+        if ret:
+            # img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+            face = cv2.resize(img, (120,160), interpolation = cv2.INTER_AREA)
+            #print(img.shape)
+            try:
+                predictions = DeepFace.analyze(face,actions=['emotion'])
+                fearPoint = predictions[0]["emotion"]["fear"]
+
+                readings = np.append(readings, fearPoint)
+                avg = np.mean(readings)
+                if len(readings) == max_samples:
+                    readings = np.delete(readings, 0)
+                print("FEAR:" + str(fearPoint))
+                print("AVG" + str(avg))
+                
+                # for x in range(6):
+                #     avgNumber = avgNumber + fearPoint
+
+                # print(avgNumber)
+                img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB) 
+                img = Image.fromarray(img)
+                draw = ImageDraw.Draw(img)
+                font_size = 65
+                font = ImageFont.truetype("HalloweenFont.ttf", font_size)
+                text = "FEAR LEVEL"
+                draw.text((144, 308), str(text), font=font,fill=(255,0,0,255))
+                img = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
+                #print(30+math.floor(int(fearPoint)*580/100))
+                # ft.putText(img=img,text='TEST',org=(15, 70),fontHeight=60,color=(255,  255, 255),thickness=-1,line_type=cv2.LINE_AA,bottomLeftOrigin=True)
+                cv2.rectangle(img,(30,400),(610,450),(255,255,255), 5)
+                cv2.rectangle(img,(30,400),(30+math.floor(int(avg)*580/100),450),(255,255,255), -1)
+                cv2.imshow('webcam',img)
+            except Exception as e: 
+                print(e)
+
+                cv2.imshow('webcam',noFace)
+        key = cv2.waitKey(5) & 0xFF
+        if ord('q') == key:
+            break
+cam.release()