face_detect.py

# MIT License
# Copyright (c) 2019-2022 JetsonHacks
# See LICENSE for OpenCV license and additional information

# https://docs.opencv.org/3.3.1/d7/d8b/tutorial_py_face_detection.html
# On the Jetson Nano, OpenCV comes preinstalled
# Data files are in /usr/sharc/OpenCV

import cv2

# gstreamer_pipeline returns a GStreamer pipeline for capturing from the CSI camera
# Defaults to 1920x1080 @ 30fps
# Flip the image by setting the flip_method (most common values: 0 and 2)
# display_width and display_height determine the size of the window on the screen
# Notice that we drop frames if we fall outside the processing time in the appsink element

def gstreamer_pipeline(
    capture_width=1920,
    capture_height=1080,
    display_width=960,
    display_height=540,
    framerate=30,
    flip_method=0,
):
    return (
        "nvarguscamerasrc ! "
        "video/x-raw(memory:NVMM), "
        "width=(int)%d, height=(int)%d, framerate=(fraction)%d/1 ! "
        "nvvidconv flip-method=%d ! "
        "video/x-raw, width=(int)%d, height=(int)%d, format=(string)BGRx ! "
        "videoconvert ! "
        "video/x-raw, format=(string)BGR ! appsink drop=True"
        % (
            capture_width,
            capture_height,
            framerate,
            flip_method,
            display_width,
            display_height,
        )
    )


def face_detect():
    window_title = "Face Detect"
    face_cascade = cv2.CascadeClassifier(
        "/usr/share/opencv4/haarcascades/haarcascade_frontalface_default.xml"
    )
    eye_cascade = cv2.CascadeClassifier(
        "/usr/share/opencv4/haarcascades/haarcascade_eye.xml"
    )
    video_capture = cv2.VideoCapture(gstreamer_pipeline(), cv2.CAP_GSTREAMER)
    if video_capture.isOpened():
        try:
            cv2.namedWindow(window_title, cv2.WINDOW_AUTOSIZE)
            while True:
                ret, frame = video_capture.read()
                gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
                faces = face_cascade.detectMultiScale(gray, 1.3, 5)

                for (x, y, w, h) in faces:
                    cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
                    roi_gray = gray[y : y + h, x : x + w]
                    roi_color = frame[y : y + h, x : x + w]
                    eyes = eye_cascade.detectMultiScale(roi_gray)
                    for (ex, ey, ew, eh) in eyes:
                        cv2.rectangle(
                            roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2
                        )
                # Check to see if the user closed the window
                # Under GTK+ (Jetson Default), WND_PROP_VISIBLE does not work correctly. Under Qt it does
                # GTK - Substitute WND_PROP_AUTOSIZE to detect if window has been closed by user
                if cv2.getWindowProperty(window_title, cv2.WND_PROP_AUTOSIZE) >= 0:
                    cv2.imshow(window_title, frame)
                else:
                    break
                keyCode = cv2.waitKey(10) & 0xFF
                # Stop the program on the ESC key or 'q'
                if keyCode == 27 or keyCode == ord('q'):
                    break
        finally:
            video_capture.release()
            cv2.destroyAllWindows()
    else:
        print("Unable to open camera")


if __name__ == "__main__":
    face_detect()