diff --git a/README.md b/README.md index fd0b8f7..d888325 100644 --- a/README.md +++ b/README.md @@ -23,7 +23,7 @@ Haar Cascades is a machine learning based approach where a cascade function is t See: https://docs.opencv.org/3.3.1/d7/d8b/tutorial_py_face_detection.html -The third example is a simple C++ prgoram which reads from the camera and displays to a window on the screen using OpenCV: +The third example is a simple C++ program which reads from the camera and displays to a window on the screen using OpenCV: ``` $ g++ -std=c++11 -Wall -I/usr/lib/opencv simple_camera.cpp -L/usr/lib -lopencv_core -lopencv_highgui -lopencv_videoio -o simple_camera @@ -80,7 +80,11 @@ flip-method : video flip methods

Release Notes

-Initial Release March, 2019 +V2 Release September, 2019 +* L4T 32.2.1 (JetPack 4.2.2) +* Tested on Jetson Nano + +Initial Release (V1) March, 2019 * L4T 32.1.0 (JetPack 4.2) * Tested on Jetson Nano diff --git a/face_detect.py b/face_detect.py index 788c03b..e749733 100644 --- a/face_detect.py +++ b/face_detect.py @@ -9,41 +9,66 @@ import cv2 # gstreamer_pipeline returns a GStreamer pipeline for capturing from the CSI camera -# Defaults to 1280x720 @ 30fps +# Defaults to 1280x720 @ 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 -def gstreamer_pipeline (capture_width=3280, capture_height=2464, display_width=820, display_height=616, framerate=21, flip_method=0) : - return ('nvarguscamerasrc ! ' - 'video/x-raw(memory:NVMM), ' - 'width=(int)%d, height=(int)%d, ' - 'format=(string)NV12, 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' % (capture_width,capture_height,framerate,flip_method,display_width,display_height)) - -def face_detect() : - face_cascade = cv2.CascadeClassifier('/usr/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml') - eye_cascade = cv2.CascadeClassifier('/usr/share/OpenCV/haarcascades/haarcascade_eye.xml') + +def gstreamer_pipeline( + capture_width=3280, + capture_height=2464, + display_width=820, + display_height=616, + framerate=21, + flip_method=0, +): + return ( + "nvarguscamerasrc ! " + "video/x-raw(memory:NVMM), " + "width=(int)%d, height=(int)%d, " + "format=(string)NV12, 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" + % ( + capture_width, + capture_height, + framerate, + flip_method, + display_width, + display_height, + ) + ) + + +def face_detect(): + face_cascade = cv2.CascadeClassifier( + "/usr/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml" + ) + eye_cascade = cv2.CascadeClassifier( + "/usr/share/OpenCV/haarcascades/haarcascade_eye.xml" + ) cap = cv2.VideoCapture(gstreamer_pipeline(), cv2.CAP_GSTREAMER) if cap.isOpened(): - cv2.namedWindow('Face Detect', cv2.WINDOW_AUTOSIZE) - while cv2.getWindowProperty('Face Detect',0) >= 0: + cv2.namedWindow("Face Detect", cv2.WINDOW_AUTOSIZE) + while cv2.getWindowProperty("Face Detect", 0) >= 0: ret, img = cap.read() gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) faces = face_cascade.detectMultiScale(gray, 1.3, 5) - for (x,y,w,h) in faces: - cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) - roi_gray = gray[y:y+h, x:x+w] - roi_color = img[y:y+h, x:x+w] + for (x, y, w, h) in faces: + cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2) + roi_gray = gray[y : y + h, x : x + w] + roi_color = img[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) + for (ex, ey, ew, eh) in eyes: + cv2.rectangle( + roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2 + ) - cv2.imshow('Face Detect',img) - keyCode = cv2.waitKey(30) & 0xff + cv2.imshow("Face Detect", img) + keyCode = cv2.waitKey(30) & 0xFF # Stop the program on the ESC key if keyCode == 27: break @@ -53,5 +78,6 @@ def face_detect() : else: print("Unable to open camera") -if __name__ == '__main__': + +if __name__ == "__main__": face_detect() diff --git a/simple_camera.py b/simple_camera.py index ca9d286..e666482 100644 --- a/simple_camera.py +++ b/simple_camera.py @@ -1,47 +1,66 @@ # MIT License # Copyright (c) 2019 JetsonHacks # See license -# Using a CSI camera (such as the Raspberry Pi Version 2) connected to a +# Using a CSI camera (such as the Raspberry Pi Version 2) connected to a # NVIDIA Jetson Nano Developer Kit using OpenCV # Drivers for the camera and OpenCV are included in the base image import cv2 # gstreamer_pipeline returns a GStreamer pipeline for capturing from the CSI camera -# Defaults to 1280x720 @ 60fps +# Defaults to 1280x720 @ 60fps # 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 -def gstreamer_pipeline (capture_width=1280, capture_height=720, display_width=1280, display_height=720, framerate=60, flip_method=0) : - return ('nvarguscamerasrc ! ' - 'video/x-raw(memory:NVMM), ' - 'width=(int)%d, height=(int)%d, ' - 'format=(string)NV12, 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' % (capture_width,capture_height,framerate,flip_method,display_width,display_height)) + +def gstreamer_pipeline( + capture_width=1280, + capture_height=720, + display_width=1280, + display_height=720, + framerate=60, + flip_method=0, +): + return ( + "nvarguscamerasrc ! " + "video/x-raw(memory:NVMM), " + "width=(int)%d, height=(int)%d, " + "format=(string)NV12, 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" + % ( + capture_width, + capture_height, + framerate, + flip_method, + display_width, + display_height, + ) + ) + def show_camera(): # To flip the image, modify the flip_method parameter (0 and 2 are the most common) - print gstreamer_pipeline(flip_method=0) + print(gstreamer_pipeline(flip_method=0)) cap = cv2.VideoCapture(gstreamer_pipeline(flip_method=0), cv2.CAP_GSTREAMER) if cap.isOpened(): - window_handle = cv2.namedWindow('CSI Camera', cv2.WINDOW_AUTOSIZE) - # Window - while cv2.getWindowProperty('CSI Camera',0) >= 0: - ret_val, img = cap.read(); - cv2.imshow('CSI Camera',img) - # This also acts as - keyCode = cv2.waitKey(30) & 0xff + window_handle = cv2.namedWindow("CSI Camera", cv2.WINDOW_AUTOSIZE) + # Window + while cv2.getWindowProperty("CSI Camera", 0) >= 0: + ret_val, img = cap.read() + cv2.imshow("CSI Camera", img) + # This also acts as + keyCode = cv2.waitKey(30) & 0xFF # Stop the program on the ESC key if keyCode == 27: - break + break cap.release() cv2.destroyAllWindows() else: - print 'Unable to open camera' + print("Unable to open camera") -if __name__ == '__main__': +if __name__ == "__main__": show_camera()