face recognition

facedet/faces.py

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+import os
+
+import cv2
+
+haar_file = "haarcascade_frontalface_default.xml"
+
+# path where the training data is saved
+datasets = "C:\\Users\\attar\\OneDrive\\Documents\\datasets"
+
+# enter the name of the person whose face is being recorded and collected for the data
+sub_data = "name of the person"
+
+path = os.path.join(datasets, sub_data)
+if not os.path.isdir(path):
+    os.mkdir(path)
+(width, height) = (130, 100)
+
+face_cascade = cv2.CascadeClassifier(haar_file)
+cam = cv2.VideoCapture(0)
+
+count = 1
+while count < 31:
+    print(count)
+    (_, img) = cam.read()
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    faces = face_cascade.detectMultiScale(gray, 1.3, 4)
+
+    for x, y, w, h in faces:
+
+        cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
+        face = gray[y: y + h, x: x + w]
+        face_resize = cv2.resize(face, (width, height))
+        cv2.imwrite("%s/%s.png" % (path, count), face_resize)
+        count += 1
+
+    cv2.imshow("FaceDetection", img)
+    key = cv2.waitKey(10)
+    if key == 27:
+        break
+
+cam.release()
+cv2.destroyAllWindows()