From 6cbbb5580e547f39c59fc7ebc38db476b9ec511a Mon Sep 17 00:00:00 2001
From: Arthur Golubtsov <goldartt@gmail.com>
Date: Tue, 7 Apr 2020 17:06:05 +0300
Subject: [PATCH] docs (en): Update qr code scan instruction and script

---
 docs/en/camera.md | 33 ++++++++++++++++-----------------
 1 file changed, 16 insertions(+), 17 deletions(-)

diff --git a/docs/en/camera.md b/docs/en/camera.md
index a478592e..e5b533be 100644
--- a/docs/en/camera.md
+++ b/docs/en/camera.md
@@ -94,40 +94,39 @@ The obtained images can be viewed using [web_video_server](web_video_server.md).
 
 > **Hint** For high-speed recognition and positioning, it is better to use [ArUco markers](aruco.md).
 
-To program actions of the copter upon detection of [QR codes](https://en.wikipedia.org/wiki/QR_code) you can use the [ZBar] library (http://zbar.sourceforge.net). It should be installed using pip:
+To program actions of the copter upon detection of [QR codes](https://en.wikipedia.org/wiki/QR_code) you can use the [pyZBar](https://pypi.org/project/pyzbar/). It should be installed using pip:
 
 ```bash
-sudo pip install zbar
+sudo pip install pyzbar
 ```
 
 QR codes recognition in Python:
 
 ```python
-import cv2
-import zbar
+import rospy
+from pyzbar import pyzbar
 from cv_bridge import CvBridge
 from sensor_msgs.msg import Image
 
 bridge = CvBridge()
-scanner = zbar.ImageScanner()
-scanner.parse_config('enable')
+
+rospy.init_node('barcode_test')
 
 # Image subscriber callback function
 def image_callback(data):
     cv_image = bridge.imgmsg_to_cv2(data, 'bgr8')  # OpenCV image
-    gray = cv2.cvtColor(cv_image, cv2.COLOR_BGR2GRAY, dstCn=0)
-
-    pil = ImageZ.fromarray(gray)
-    raw = pil.tobytes()
-
-    image = zbar.Image(320, 240, 'Y800', raw)  # Image params
-    scanner.scan(image)
-
-    for symbol in image:
-        # print detected QR code
-        print 'decoded', symbol.type, 'symbol', '"%s"' % symbol.data
+    barcodes = pyzbar.decode(cv_image)
+    for barcode in barcodes:
+        b_data = barcode.data.encode("utf-8")
+        b_type = barcode.type
+        (x, y, w, h) = barcode.rect
+        xc = x + w/2
+        yc = y + h/2
+        print ("Found {} with data {} with center at x={}, y={}".format(b_type, b_data, xc, yc))
 
 image_sub = rospy.Subscriber('main_camera/image_raw', Image, image_callback, queue_size=1)
+
+rospy.spin()
 ```
 
 The script will take up to 100% CPU capacity. To slow down the script artificially, you can use [throttling](http://wiki.ros.org/topic_tools/throttle) of frames from the camera, for example, at 5 Hz (`main_camera.launch`):