एरोनेट एपिसोड 3 में प्रवेश करना: गेंद को खोजना

 #coding=utf-8 import cv2 import numpy as np def nothing(*arg): pass cv2.namedWindow( "result" ) #    cv2.namedWindow( "img" ) #   cv2.namedWindow( "settings" ) #    cap = cv2.VideoCapture(0)#video.create_capture(0) #  6         cv2.createTrackbar('invert', 'settings', 0, 1, nothing) cv2.createTrackbar('h1', 'settings', 0, 255, nothing) cv2.createTrackbar('s1', 'settings', 0, 255, nothing) cv2.createTrackbar('v1', 'settings', 0, 255, nothing) cv2.createTrackbar('h2', 'settings', 255, 255, nothing) cv2.createTrackbar('s2', 'settings', 255, 255, nothing) cv2.createTrackbar('v2', 'settings', 255, 255, nothing) while True: flag, img = cap.read() hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV ) #    invert = cv2.getTrackbarPos('invert', 'settings') h1 = cv2.getTrackbarPos('h1', 'settings') s1 = cv2.getTrackbarPos('s1', 'settings') v1 = cv2.getTrackbarPos('v1', 'settings') h2 = cv2.getTrackbarPos('h2', 'settings') s2 = cv2.getTrackbarPos('s2', 'settings') v2 = cv2.getTrackbarPos('v2', 'settings') #       h_min = np.array((h1, s1, v1), np.uint8) h_max = np.array((h2, s2, v2), np.uint8) #       HSV thresh = cv2.inRange(hsv, h_min, h_max) if invert>0: cv2.bitwise_not(thresh,thresh) cv2.imshow('result', thresh) cv2.imshow('img', img) ch = cv2.waitKey(5) if ch == 27: break cap.release() cv2.destroyAllWindows() 

 #coding=utf-8 import cv2 import numpy as np import math if __name__ == '__main__': def nothing(*arg): pass cv2.namedWindow( "result" ) #    cv2.namedWindow( "source" ) # source video cv2.namedWindow( "settings" ) #    cap = cv2.VideoCapture(0) cap.set(cv2.CAP_PROP_FRAME_WIDTH, 320) cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 240) cap.set(cv2.CAP_PROP_FPS,40) #  6         cv2.createTrackbar('invert', 'settings', 0, 1, nothing) cv2.createTrackbar('h1', 'settings', 0, 255, nothing) cv2.createTrackbar('s1', 'settings', 0, 255, nothing) cv2.createTrackbar('v1', 'settings', 0, 255, nothing) cv2.createTrackbar('h2', 'settings', 255, 255, nothing) cv2.createTrackbar('s2', 'settings', 255, 255, nothing) cv2.createTrackbar('v2', 'settings', 255, 255, nothing) crange = [0,0,0, 0,0,0] #set up initial values cv2.setTrackbarPos('invert','settings',1) cv2.setTrackbarPos('h1','settings',7) cv2.setTrackbarPos('h2','settings',158) cv2.setTrackbarPos('s1','settings',0) cv2.setTrackbarPos('s2','settings',255) cv2.setTrackbarPos('v1','settings',0) cv2.setTrackbarPos('v2','settings',255) color_blue = (255,255,0) color_red = (0,0,255) color_green = (0,255,0) color_white = (255,255,255) color_yellow = (0,255,255) color_black = (0,0,0) real_ballon_r = 0.145 #baloon real radius in meters while True: flag, img = cap.read() hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV ) #    invert = cv2.getTrackbarPos('invert', 'settings') h1 = cv2.getTrackbarPos('h1', 'settings') s1 = cv2.getTrackbarPos('s1', 'settings') v1 = cv2.getTrackbarPos('v1', 'settings') h2 = cv2.getTrackbarPos('h2', 'settings') s2 = cv2.getTrackbarPos('s2', 'settings') v2 = cv2.getTrackbarPos('v2', 'settings') #       h_min = np.array((h1, s1, v1), np.uint8) h_max = np.array((h2, s2, v2), np.uint8) #       HSV thresh = cv2.inRange(hsv, h_min, h_max) if invert>0: cv2.bitwise_not(thresh,thresh) #find contours _, contours0, hierarchy = cv2.findContours( thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) max_area = 0 max_center_x=None max_center_y=None max_baloon_r=None max_yaw_shift=None for cnt in contours0: rect = cv2.minAreaRect(cnt) box = cv2.boxPoints(rect) box = np.int0(box) center = (int(rect[0][0]),int(rect[0][1])) area = int(rect[1][0]*rect[1][1]) if area > 100: baloon_r = int(math.sqrt(area)/2) yaw_shift = int( (center[0] - 320/2) * 130 / 320) # 130 degree camera for 320 pics image cv2.circle(img, center, baloon_r , color_red, 1) if area>max_area: max_area=area max_center_x = center[0] max_center_y = center[1] max_baloon_r = baloon_r max_yaw_shift = yaw_shift #draw main baloon if max_area>0: cv2.circle(img, (max_center_x,max_center_y), max_baloon_r+2 , color_blue, 2) cv2.putText(img, "D=%d" % int(max_baloon_r*2), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_red, 1) cv2.putText(img, "angle=%d '" % max_yaw_shift, (10, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_green, 1) max_distance = real_ballon_r/math.tan(max_baloon_r/320.0*(math.pi*160.0/360.0)) #distance to baloon #print max_distance cv2.putText(img, "%fm" % max_distance, (10, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_blue, 1) cv2.line(img, (max_center_x, 1), (max_center_x, 239) , color_white, 1) cv2.line(img, (1,max_center_y), (319, max_center_y) , color_white, 1) #draw target cv2.line(img, (320/2-10, 240/2-10), (320/2+10, 240/2+10) , color_yellow, 1) cv2.line(img, (320/2+10, 240/2-10), (320/2-10, 240/2+10) , color_yellow, 1) # show results cv2.imshow('source', img) cv2.imshow('result', thresh) ch = cv2.waitKey(5) if ch == 27: break cap.release() cv2.destroyAllWindows() 

 #!/usr/bin/env python # coding=UTF-8 # zuza baloon seeker import rospy from sensor_msgs.msg import CameraInfo, Image import time import cv2 from cv_bridge import CvBridge, CvBridgeError import numpy as np #import tf.transformations as t from geometry_msgs.msg import TwistStamped, Quaternion, Point, PoseStamped, TransformStamped import copy from std_msgs.msg import ColorRGBA import tf2_ros import math import yaml my_cam_info=None my_fps=0 my_last_fps=0 my_time_fps=time.time() bridge = CvBridge() mtx=None dist=None def raspicam_loop_cv(): global my_fps, my_last_fps, my_time_fps, mtx, dist # initialize the camera and grab a reference to the raw camera capture camera = cv2.VideoCapture(0) camera.set(cv2.CAP_PROP_FRAME_WIDTH, my_cam_info.width) camera.set(cv2.CAP_PROP_FRAME_HEIGHT, my_cam_info.height) camera.set(cv2.CAP_PROP_FPS, rospy.get_param('/baloon_detector/framerate')) # allow the camera to warmup time.sleep(0.1) color_blue = (255,255,0) color_red = (0,0,255) color_green = (0,255,0) color_white = (255,255,255) color_yellow = (0,255,255) color_black = (0,0,0) #    invert = rospy.get_param('/baloon_detector/invert') h1 = rospy.get_param('/baloon_detector/h1') s1 = rospy.get_param('/baloon_detector/s1') v1 = rospy.get_param('/baloon_detector/v1') h2 = rospy.get_param('/baloon_detector/h2') s2 = rospy.get_param('/baloon_detector/s2') v2 = rospy.get_param('/baloon_detector/v2') real_ballon_r = rospy.get_param('/baloon_detector/real_ballon_r') #       h_min = np.array((h1, s1, v1), np.uint8) h_max = np.array((h2, s2, v2), np.uint8) while not rospy.is_shutdown(): ret, image_raw = camera.read() # calculate FPS cur_time2 = time.time() if cur_time2-my_time_fps>5: my_last_fps=my_fps my_fps=1 my_time_fps=cur_time2 else: my_fps+=1 image_hsv = cv2.cvtColor(image_raw, cv2.COLOR_BGR2HSV ) #       HSV thresh = cv2.inRange(image_hsv, h_min, h_max) if invert>0: cv2.bitwise_not(thresh,thresh) #find contours _, contours0, hierarchy = cv2.findContours( thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) max_area = 0 max_center_x=None max_center_y=None max_baloon_r=None max_yaw_shift=None for cnt in contours0: rect = cv2.minAreaRect(cnt) box = cv2.boxPoints(rect) box = np.int0(box) center = (int(rect[0][0]),int(rect[0][1])) area = int(rect[1][0]*rect[1][1]) if area > 100: baloon_r = int(math.sqrt(area)/2) yaw_shift = int( (center[0] - my_cam_info.width/2) * 130 / my_cam_info.width) # 130 degree camera for my_cam_info.width pics image cv2.circle(image_raw, center, baloon_r , color_red, 1) if area>max_area: max_area=area max_center_x = center[0] max_center_y = center[1] max_baloon_r = baloon_r max_yaw_shift = yaw_shift #draw main baloon if max_area>0: cv2.circle(image_raw, (max_center_x,max_center_y), max_baloon_r+2 , color_blue, 2) cv2.putText(image_raw, "D=%d" % int(max_baloon_r*2), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_red, 1) cv2.putText(image_raw, "angle=%d '" % max_yaw_shift, (10, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_green, 1) max_distance = real_ballon_r/math.tan(max_baloon_r/float(my_cam_info.width)*(math.pi*160.0/360.0)) #distance to baloon #print max_distance cv2.putText(image_raw, "%fm" % max_distance, (10, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_blue, 1) cv2.line(image_raw, (max_center_x, 1), (max_center_x, my_cam_info.height-1) , color_white, 1) cv2.line(image_raw, (1,max_center_y), (my_cam_info.width-1, max_center_y) , color_white, 1) # post baloon Twist tws = TwistStamped() tws.header.stamp = rospy.Time.now() tws.header.frame_id = 'fcu' tws.twist.linear.x = max_distance tws.twist.angular.z = float(-max_yaw_shift)/360.0*math.pi#yaw tws.twist.angular.y = float( (max_center_y - my_cam_info.height/2) * 130.0 / my_cam_info.height) /360.0*math.pi #pitch publisher_baloontwist.publish(tws) #draw target cv2.line(image_raw, (my_cam_info.width/2-10, my_cam_info.height/2-10), (my_cam_info.width/2+10, my_cam_info.height/2+10) , color_yellow, 1) cv2.line(image_raw, (my_cam_info.width/2+10, my_cam_info.height/2-10), (my_cam_info.width/2-10, my_cam_info.height/2+10) , color_yellow, 1) #Draw FPS on image cv2.putText(image_raw,"fps: "+str(my_last_fps/5),(120,20), cv2.FONT_HERSHEY_SIMPLEX, 0.5,(0,255,0),1,cv2.LINE_AA) #  1   5,      if my_fps%5==0: try: publisher_image_raw_result.publish(bridge.cv2_to_imgmsg(image_raw,"bgr8")) publisher_image_raw_filter.publish(bridge.cv2_to_imgmsg(thresh, "mono8")) except CvBridgeError as e: print(e) def publish_dummy_vp(event): ps = PoseStamped() ps.header.stamp = rospy.Time.now() ps.header.frame_id = 'local_origin' ps.pose.orientation.w = 1; publisher_vp.publish(ps); def callback_handle_pose(mavros_pose): rospy.loginfo("Got mavros pose, stop publishing zeroes.") dummy_timer.shutdown() handle_pose_sub.unregister() def process_camera_info_yaml(): global mtx, dist, my_cam_info my_cam_info = CameraInfo() filename = rospy.get_param('/baloon_detector/camera_info_url') with open(filename, 'r') as ymlfile: cfg = yaml.load(ymlfile) my_cam_info.width = cfg['image_width'] my_cam_info.height= cfg['image_height'] my_cam_info.K = cfg['camera_matrix']['data'] my_cam_info.D = cfg['distortion_coefficients']['data'] mtx=np.zeros((3,3)) dist=np.zeros((1,5)) for i in range(3): for j in range(3): mtx[i,j]=my_cam_info.K[i*3+j] for i in range(5): dist[0,i]=my_cam_info.D[i] print mtx, dist if __name__ == '__main__': rospy.init_node('baloon_detector') ## init pose publishing from FCU publisher_vp = rospy.Publisher('/mavros/vision_pose/pose', PoseStamped, queue_size=1) dummy_timer=rospy.Timer(rospy.Duration(0.5), publish_dummy_vp) handle_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback_handle_pose) ## init camera process_camera_info_yaml() print my_cam_info rospy.loginfo("image translation starting.........") publisher_image_raw_filter = rospy.Publisher('baloon_detector/image_filter', Image, queue_size=1) publisher_image_raw_result = rospy.Publisher('baloon_detector/image_result', Image, queue_size=1) publisher_baloontwist= rospy.Publisher('baloon_detector/twist', TwistStamped ,queue_size=1) raspicam_loop_cv() try: rospy.spin() except KeyboardInterrupt: print("Shutting down") 

 <launch> <!-- mavros --> <include file="$(find mavros)/launch/px4.launch"> <arg name="fcu_url" value="/dev/ttyAMA0:921600"/> <arg name="gcs_url" value="tcp-l://0.0.0.0:5760"/> </include> <!-- baloon pose estimator --> <node name="baloon_detector" pkg="baloon" type="baloon_pose_cv.py" output="screen"> <param name="invert" value="1"/> <param name="h1" value="7"/> <param name="h2" value="158"/> <param name="s1" value="0"/> <param name="s2" value="255"/> <param name="v1" value="0"/> <param name="v2" value="255"/> <param name="real_ballon_r" value="0.145"/> <param name="camera_info_url" value="$(find baloon)/src/fe130_320_01.yaml"/> <param name="framerate" value="40"/> </node> <!-- web video server --> <node name="web_video_server" pkg="web_video_server" type="web_video_server" required="false" respawn="true" respawn_delay="5"/> </launch> 

 image_width: 320 image_height: 240 camera_name: main_camera_optical camera_matrix: rows: 3 cols: 3 data: [251.8636348237197, 0, 161.853506252244, 0, 252.36606604425, 102.0038140308112, 0, 0, 1] distortion_model: plumb_bob distortion_coefficients: rows: 1 cols: 5 data: [-0.4424451138703088, 0.1594038086314775, 0.006694781700363117, 0.00174908936506397, 0] rectification_matrix: rows: 3 cols: 3 data: [1, 0, 0, 0, 1, 0, 0, 0, 1] projection_matrix: rows: 3 cols: 4 data: [174.0442047119141, 0, 163.822732720786, 0, 0, 175.2916412353516, 105.5565883832869, 0, 0, 0, 1, 0]