Add Python 3 Support

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
 
 <h2>Release Notes</h2>
 
-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
 

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()

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()