savingFaceRec.py

# Read the face from camera
# Draw rectangle around face
# save the reshaped face data into numpy array

import cv2
import numpy as np

cap = cv2.VideoCapture(0)

face_cascade = cv2.CascadeClassifier("./haarcascade_frontalface_alt.xml")

skip = 0
face_data = []
dataset_path = "./FaceData/"

file_name = input("Enter The Name Of Person: ")

while True:
    ret, frame = cap.read()

    gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    if ret == False:
        continue

    faces = face_cascade.detectMultiScale(gray_frame, 1.3, 5)
    faces = sorted(faces, key=lambda f: f[2]*f[3], reverse=True)
    # print(faces)

    # pick the largest face
    for x, y, w, h in faces[0:]:
        cv2.rectangle(gray_frame, (x, y), (x+w, y+h), (201, 25, 101), 2)
        offset = 10
        face_section = gray_frame[y-offset:y+h+offset, x-offset:x+w+offset]
        face_section = cv2.resize(face_section, (100, 100))

        skip += 1
        if skip % 10 == 0:
            face_data.append(face_section)
            print(len(face_data))

    cv2.imshow("Face Detector", gray_frame)
    cv2.imshow("Face Detected", face_section)

    key_pressed = cv2.waitKey(1) & 0xFF
    if key_pressed == ord("q"):
        break


face_data = np.asarray(face_data)
face_data = face_data.reshape((face_data.shape[0], -1))

print(face_data.shape)

# Save to file
np.save(dataset_path+file_name+".npy", face_data)
print("Data Successfully Saved at" + dataset_path+file_name+".npy")

cap.release()
cv2.destroyAllWindows()