PhotoCapture.py

import imutils
import time

# pip install opencv-python
import cv2
import csv
import os

# using haar cascade to detect face
cascade = "haarcascade_frontalface_default.xml"
detector = cv2.CascadeClassifier(cascade)

Name = str(input("Enter your Name : "))
Roll_Number = int(input("Enter your Roll_Number : "))
dataset = "dataset"
sub_data = Name
path = os.path.join(dataset, sub_data)

if not os.path.isdir(path):
    os.makedirs(path)
    print(sub_data)

# write name and roll number into csv file
info = [str(Name), str(Roll_Number)]
with open("student.csv", "a") as csvFile:
    write = csv.writer(csvFile)
    write.writerow(info)
csvFile.close()

print("Starting video stream...")
# open web camera to capture imagess
cam = cv2.VideoCapture(0, cv2.CAP_DSHOW)
time.sleep(2.0)
total = 0
print("Press c to capture the Image q to quit.")

# capture a maximum of 150 images
while True:  # total < 150:
    print(total)
    _, frame = cam.read()
    # scale the image to 400x400 size
    img = imutils.resize(frame, width=400)
    # detect the face area rectangle
    rects = detector.detectMultiScale(
        cv2.cvtColor(img, cv2.COLOR_BGR2GRAY),
        scaleFactor=1.1,
        minNeighbors=5,
        minSize=(30, 30),
    )

    # show the images in the screen
    cv2.imshow("Frame", frame)
    # check if the key pressed is q
    key = cv2.waitKey(1) & 0xFF
    if key == ord("q"):
        break
    if key == ord("c"):
        for x, y, w, h in rects:
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
            p = os.path.sep.join([path, "{}.png".format(str(total).zfill(5))])
            # capture the images as png
            cv2.imwrite(p, img)
            # total += 1

cam.release()
cv2.destroyAllWindows()