skt

face_recognition/face_recog_2/datacollect.py

@@ -0,0 +1,36 @@
+import cv2
+import os
+
+video = cv2.VideoCapture(0)
+
+facedectect = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+
+count = 0
+
+nameID = str(input("Enter Your Name: ")).lower()
+
+path = 'images/' + nameID
+isExist = os.path.exists(path)
+
+
+if isExist:
+    print("Name Already Taken")
+    nameID = str(input("Enter Your Name Again"))
+else:
+    os.makedirs(path)
+
+while True:
+    ret, frame = video.read()
+    faces = facedectect.detectMultiScale(frame,1.3,5)
+    for x,y,w,h in faces:
+        count = count+1
+        name = './images/' + nameID + '/' + str(count) + '.jpg'
+        print("Creating Images............" + name)
+        cv2.imwrite(name, frame[y:y+h,x:x+w])
+        cv2.rectangle(frame, (x,y), (x+w, y+h), (0,255,0), 3)
+    cv2.imshow("WindowFrame", frame)
+    k = cv2.waitKey(1)
+    if k == ord('q'):
+        break
+video.release()
+cv2.destroyAllWindows()

face_recognition/face_recog_2/test.py

@@ -0,0 +1,65 @@
+import tensorflow as tf
+from tensorflow import keras
+import numpy as np
+import cv2
+from keras.models import load_model
+import numpy as np
+
+facedectect = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+
+
+cap = cv2.VideoCapture(0)
+cap.set(3,640)
+cap.set(4,480)
+font = cv2.FONT_HERSHEY_COMPLEX
+
+
+model = load_model('keras_model.h5', compile= False)
+def get_classname(classNo):
+    if classNo == 0:
+        return "Siwat"
+    elif classNo == 1:
+        return "Sukatat"
+    elif classNo == 2:
+        return "Sorapat"
+
+while True:
+    sucess, imgOriginal = cap.read()
+    faces = facedectect.detectMultiScale(imgOriginal,1.3,5)
+    for x,y,w,h in faces:
+        crop_img = imgOriginal[y:y+h, x:x+h]
+        img = cv2.resize(crop_img, (224,224))
+        img = img.reshape(1, 224, 224, 3)
+        prediction = model.predict(img)
+        classIndex = np.argmax(prediction,axis=1)
+        #classIndex = model.predict(img)
+        probabilityValue = np.amax(prediction)
+
+        if classIndex == 0:
+            cv2.rectangle(imgOriginal, (x,y), (x+w, y+h), (0,255,0), 2)
+            cv2.rectangle(imgOriginal, (x,y-40), (x+w, y), (0,255,0), -2)
+            cv2.putText(imgOriginal, str(get_classname(classIndex)), (x,y-10), font, 0.75, (0,255,0), 2, cv2.LINE_AA, False)
+            print(str(get_classname(classIndex)))
+        elif classIndex == 1:
+            cv2.rectangle(imgOriginal, (x,y), (x+w, y+h), (0,255,0), 2)
+            cv2.rectangle(imgOriginal, (x,y-40), (x+w, y), (0,255,0), -2)
+            cv2.putText(imgOriginal, str(get_classname(classIndex)), (x,y-10), font, 0.75, (0,255,0), 2, cv2.LINE_AA, False)
+            print(str(get_classname(classIndex)))
+        elif classIndex == 2:
+            cv2.rectangle(imgOriginal, (x,y), (x+w, y+h), (0,255,0), 2)
+            cv2.rectangle(imgOriginal, (x,y-40), (x+w, y), (0,255,0), -2)
+            cv2.putText(imgOriginal, str(get_classname(classIndex)), (x,y-10), font, 0.75, (0,255,0), 2, cv2.LINE_AA, False)
+            print(str(get_classname(classIndex)))
+
+        cv2.putText(imgOriginal, str(round(probabilityValue*100, 2))+ "%", (180,75), font ,0.75, (0,255,0), 2, cv2.LINE_AA, False)
+    cv2.imshow("Result", imgOriginal)
+    k = cv2.waitKey(1)
+    if k == ord('q'):
+        break
+video.release()
+cv2.destroyAllWindows()
+    
+        
+
+
+