added flask framework, tambah karyawan page, scan absensi,and tambah karyawan open cv

main2.py

@@ -0,0 +1,57 @@
+import cv2
+import json
+
+dataset = "dataset.json"
+
+
+
+# open the dataset file
+with open(dataset, 'r') as f:
+    data = json.load(f)
+
+# check the last data
+last_data = data[-1]
+
+# check the name    
+name = last_data["name"]
+
+# Open a video capture from the default camera (0)
+video_capture = cv2.VideoCapture(0)
+
+# Set the window to normal so it can be resized
+cv2.namedWindow('Image Capture', cv2.WINDOW_NORMAL)
+
+# Set the window to full screen
+cv2.setWindowProperty('Image Capture', cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)
+
+face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+
+while True:
+    # Capture a frame from the video stream
+    ret, frame = video_capture.read()
+
+    # Convert the frame to grayscale for face detection
+    gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    # Detect faces in the frame
+    faces = face_cascade.detectMultiScale(gray_frame, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
+
+    # Initialize the key variable to None
+    key = cv2.waitKey(1)
+
+    # Press 'q' to save the entire image, but only if faces were detected
+    if len(faces) > 0 and key == ord('q'):
+        # Save the frame before drawing the rectangle
+        cv2.imwrite('faces/' + name + '.jpg', frame)
+        break
+
+    # Draw rectangles around the detected faces
+    for (x, y, w, h) in faces:
+        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255), 2)
+
+    # Display the frame
+    cv2.imshow('Image Capture', frame)
+
+# Release the video capture and close the OpenCV window
+video_capture.release()
+cv2.destroyAllWindows()