def calibrate(imagedir, cbrow, cbcol):
nimages = 0
datapoints = []
im_dims = (0,0)
# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = numpy.zeros((cbrow * cbcol, 3), numpy.float32)
objp[:, :2] = numpy.mgrid[0:cbcol, 0:cbrow].T.reshape(-1, 2)
# Arrays to store object points and image points from all the images.
objpoints = [] # 3d point in real world space
imgpoints = [] # 2d points in image plane.
files = file_list(imagedir, ['jpg', 'jpeg', 'png'])
for f in files:
colour = cv2.imread(f)
grey = cv2.cvtColor(colour, cv2.COLOR_BGR2GRAY)
ret, corners = cv2.findChessboardCorners(grey, (cbcol, cbrow), flags=cv2.CALIB_CB_ADAPTIVE_THRESH)
if (ret):
print('using ' + f)
cv2.cornerSubPix(grey,corners,(11,11),(-1,-1),(cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.01))
objpoints.append(objp)
imgpoints.append(corners)
im_dims = grey.shape[:2]
if len(imgpoints) == 0:
print("Not enough good quality images. Aborting")
return
ret, K, D, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, grey.shape[::-1], None, None)
# storing results using CameraParams
C = CameraParams(lens=lens, sensorwidth=sensorwidth, xresolution=im_dims[1], yresolution=im_dims[0])
C.setParams(K, D)
C.save(os.path.join(imagedir, "paramsout.json"))
print("Saved params in " + os.path.join(imagedir, "paramsout.json"))
def load_camera_settings():
global image_height, image_width
c_params = CameraParams(lens=4.0, xresolution=0, yresolution=0)
if os.path.exists(config_file):
c_params.load(config_file)
image_height = c_params.yresolution
image_width = c_params.xresolution
print("Loaded %s" % config_file)
else:
print("Warning: %s not found. Using default resolution height=%i and width=%i" % (config_file,image_height,image_width))
def getCameraWidth(self, alt):
'''Using the camera parameters, with the width of the
ground strip that the camera can see from a particular altitude'''
#use the camera parameters
c_params = CameraParams(lens=4.0)
# load camera params and get the width of an image on the ground
path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', 'data', 'chameleon1_arecont0.json')
c_params.load(path)
aov = math.degrees(2.0*math.atan((c_params.sensorwidth/1000.0)/(2.0*c_params.lens/1000.0)))
groundWidth = 2.0*alt*math.tan(math.radians(aov/2))
return groundWidth
def load_camera_settings():
global image_height, image_width
c_params = CameraParams(lens=4.0, xresolution=0, yresolution=0)
if os.path.exists(config_file):
c_params.load(config_file)
image_height = c_params.yresolution
image_width = c_params.xresolution
print("Loaded %s" % config_file)
else:
print(
"Warning: %s not found. Using default resolution height=%i and width=%i"
% (config_file, image_height, image_width))
def getCameraWidth(self, alt):
'''Using the camera parameters, with the width of the
ground strip that the camera can see from a particular altitude'''
#use the camera parameters
c_params = CameraParams(lens=4.0)
# load camera params and get the width of an image on the ground
path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..',
'data', 'chameleon1_arecont0.json')
c_params.load(path)
aov = math.degrees(2.0 * math.atan(
(c_params.sensorwidth / 1000.0) / (2.0 * c_params.lens / 1000.0)))
groundWidth = 2.0 * alt * math.tan(math.radians(aov / 2))
return groundWidth
def test_JoeLog_JoeIterator():
joelog = cuav_joe.JoeLog(os.path.join('.', 'joe.log'), False)
regions = []
frame_time = 1478954763.0
C = CameraParams(lens=4.0,
sensorwidth=5.0,
xresolution=1024,
yresolution=768)
regions.append(cuav_region.Region(10, 10, 25, 23, None, scan_score=450))
regions.append(cuav_region.Region(200, 205, 252, 236, None,
scan_score=420))
pos = mav_position.MavPosition(-30, 145, 34.56, 20, -56.67, 345,
frame_time)
joelog.add_regions(frame_time, regions, pos, 'img2017111312451230Z.png')
joeread = cuav_joe.JoeIterator(os.path.join('.', 'joe.log'))
joeret = joeread.getjoes()
assert len(joeret) == 2
assert joeret[
0] == "JoePosition(lat=-30.000235 lon=144.999639 MavPosition(pos -30.000000 145.000000 alt=34.6 roll=20.0 pitch=-56.7 yaw=345.0) img2017111312451230Z.png None (10, 10, 25, 23) latlon=(-30.000235126851315, 144.9996388367703) score=None Sat Nov 12 23:46:03 2016 2016111212460300Z)" or "JoePosition(lat=-30.000235 lon=144.999639 MavPosition(pos -30.000000 145.000000 alt=34.6 roll=20.0 pitch=-56.7 yaw=345.0) img2017111312451230Z.png None (10, 10, 25, 23) latlon=(-30.000235126851315, 144.9996388367703) score=None Sat Nov 12 12:46:03 2016 2016111212460300Z)"
assert joeret[
1] == "JoePosition(lat=-30.000367 lon=144.999711 MavPosition(pos -30.000000 145.000000 alt=34.6 roll=20.0 pitch=-56.7 yaw=345.0) img2017111312451230Z.png None (200, 205, 252, 236) latlon=(-30.000366794010567, 144.9997107272955) score=None Sat Nov 12 23:46:03 2016 2016111212460300Z)" or "JoePosition(lat=-30.000367 lon=144.999711 MavPosition(pos -30.000000 145.000000 alt=34.6 roll=20.0 pitch=-56.7 yaw=345.0) img2017111312451230Z.png None (200, 205, 252, 236) latlon=(-30.000366794010567, 144.9997107272955) score=None Sat Nov 12 12:46:03 2016 2016111212460300Z)"
os.remove(os.path.join('.', 'joe.log'))
def dewarp(imagedir):
# Loading from json file
C = CameraParams.fromfile(os.path.join(imagedir, "params.json"))
K = C.K
D = C.D
print("Loaded camera parameters from " +
os.path.join(imagedir, "params.json"))
for f in file_list(imagedir, ['jpg', 'jpeg', 'png']):
print(f)
colour = cv2.imread(f)
grey = cv2.cvtColor(colour, cv2.COLOR_BGR2GRAY)
h, w = grey.shape[:2]
newcameramtx, roi = cv2.getOptimalNewCameraMatrix(
K, D, (w, h), 1, (w, h))
mapx, mapy = cv2.initUndistortRectifyMap(K, D, None, newcameramtx,
(w, h), 5)
dewarped = cv2.remap(grey, mapx, mapy, cv2.INTER_LINEAR)
x, y, w, h = roi
dewarped = dewarped[y:y + h, x:x + w]
grey = cv2.resize(grey, (0, 0), fx=0.5, fy=0.5)
dewarped = cv2.resize(dewarped, (0, 0), fx=0.5, fy=0.5)
cv2.imshow("Original", grey)
cv2.imshow("Dewarped", dewarped)
cv2.waitKey(-1)
def dewarp(imagedir):
# Loading from json file
C = CameraParams.fromfile(os.path.join(imagedir, "params.json"))
K = C.K
D = C.D
print("Loaded camera parameters from " + os.path.join(imagedir, "params.json"))
for f in file_list(imagedir, ['jpg', 'jpeg', 'png']):
print(f)
colour = cv2.imread(f)
grey = cv2.cvtColor(colour, cv2.COLOR_BGR2GRAY)
h, w = grey.shape[:2]
newcameramtx, roi=cv2.getOptimalNewCameraMatrix(K, D, (w,h), 1, (w,h))
mapx, mapy = cv2.initUndistortRectifyMap(K, D, None, newcameramtx, (w,h), 5)
dewarped = cv2.remap(grey, mapx, mapy, cv2.INTER_LINEAR)
x, y, w, h = roi
dewarped = dewarped[y:y+h, x:x+w]
grey = cv2.resize(grey, (0,0), fx=0.5, fy=0.5)
dewarped = cv2.resize(dewarped, (0,0), fx=0.5, fy=0.5)
cv2.imshow("Original", grey )
cv2.imshow("Dewarped", dewarped)
cv2.waitKey(-1)
def test_do_calibrate():
dirry = os.path.join('.', 'cuav', 'data', 'ChameleonArecort')
outfile = os.path.join('.', 'cuav', 'data', 'ChameleonArecort', 'paramsout.json')
calibrate.calibrate(dirry, 10, 7)
assert os.path.isfile(outfile)
C = CameraParams.fromfile(outfile)
assert C is not None
os.remove(outfile)
def gps_position_from_image_region(region, pos, width=1280, height=960, C=CameraParams(), altitude=None):
'''
return a GPS position in an image given a MavPosition object
and an image region tuple
'''
if pos is None:
return None
x = (region.x1+region.x2)*0.5
y = (region.y1+region.y2)*0.5
return gps_position_from_xy(x, y, pos, C=C, altitude=altitude)
def check_camera_parms(self):
'''check for change in camera parameters'''
#dir is rel to this python file:
if self.camera_settings.camparms is None:
return False
camfiletxt = pkg_resources.resource_string("cuav", self.camera_settings.camparms)
try:
self.c_params = CameraParams.fromstring(camfiletxt)
return True
except:
return False
def check_camera_parms(self):
'''check for change in camera parameters'''
#dir is rel to this python file:
if self.camera_settings.camparms is None:
return False
camfiletxt = pkg_resources.resource_string(
"cuav", self.camera_settings.camparms)
try:
self.c_params = CameraParams.fromstring(camfiletxt)
return True
except:
return False
def test_pixel_position_matt():
C = CameraParams(lens=4.0,
sensorwidth=5.0,
xresolution=1024,
yresolution=768)
(east, north) = pixel_position_matt(100, 100, 123, 0.1, 2, 0, C)
assert abs(-67.3798 - east) < 0.001
assert abs(43.6719 - north) < 0.001
(east, north) = pixel_position_matt(0, 130, 57, 0.1, 2, 0, C)
assert abs(-38.4761 - east) < 0.001
assert abs(18.188 - north) < 0.001
def test_pixel_coordinates():
C = CameraParams(lens=4.0,
sensorwidth=5.0,
xresolution=1024,
yresolution=800)
(lat, lon) = pixel_coordinates(512, 400, -50, 145, 123, 0, 0, 90, C)
assert abs(-50 - lat) < 0.00001
assert abs(145 - lon) < 0.00001
(lat, lon) = pixel_coordinates(200, 100, -50, 145, 123, 2, 5, 50, C)
assert abs(-49.99928 - lat) < 0.00001
assert abs(145.00001 - lon) < 0.00001
def test_meters_per_pixel():
C = CameraParams(lens=4.0,
sensorwidth=5.0,
xresolution=1024,
yresolution=800)
frame_time = 1478954763.0
pos = mav_position.MavPosition(-50, 145, 120, 0, 0, 90, frame_time)
ret = meters_per_pixel(pos, C)
assert abs(0.1463 - ret) < 0.001
pos = mav_position.MavPosition(-50, 145, 85, 3, 1, 45, frame_time)
ret = meters_per_pixel(pos, C)
assert abs(0.1041 - ret) < 0.001
def test_cam_params_dict():
C = CameraParams(lens=4.0,
sensorwidth=5.0,
xresolution=3000,
yresolution=4000)
C.setParams([[1, 2, 3], [4, 5, 6]], [0, 6, 7, 8])
Cdict = C.todict()
C2dict = CameraParams.fromdict(Cdict)
assert C.todict() == C2dict.todict()
assert numpy.array_equal(C.K, C2dict.K)
assert numpy.array_equal(C.D, C2dict.D)
def test_cam_params_dict():
C = CameraParams(lens=4.0, sensorwidth=5.0, xresolution=3000, yresolution=4000)
C.setParams([[1, 2, 3], [4, 5, 6]], [0, 6, 7, 8])
Cdict = C.todict()
C2dict = CameraParams.fromdict(Cdict)
assert C.todict() == C2dict.todict()
assert numpy.array_equal(C.K, C2dict.K)
assert numpy.array_equal(C.D, C2dict.D)
def test_cam_params_txt():
C = CameraParams(lens=4.0,
sensorwidth=5.0,
xresolution=1280,
yresolution=960)
C.setParams([[1, 2, 3], [4, 5, 6]], [0, 6, 7, 8])
C.save('foo.txt')
C2 = CameraParams.fromfile('foo.txt')
assert str(C) == str(C2)
assert numpy.array_equal(C.K, C2.K)
assert numpy.array_equal(C.D, C2.D)
os.remove('foo.txt')
def test_cam_params_txt():
C = CameraParams(lens=4.0, sensorwidth=5.0, xresolution=1280, yresolution=960)
C.setParams([[1, 2, 3], [4, 5, 6]], [0, 6, 7, 8])
C.save('foo.txt')
C2 = CameraParams.fromfile('foo.txt')
assert str(C) == str(C2)
assert numpy.array_equal(C.K, C2.K)
assert numpy.array_equal(C.D, C2.D)
os.remove('foo.txt')
def __init__(self,
slipmap,
grid_width=20,
grid_height=20,
thumb_size=35,
C=CameraParams(),
camera_settings=None,
image_settings=None,
start_menu=False):
self.thumb_size = thumb_size
self.width = grid_width * thumb_size
self.height = grid_height * thumb_size
self.mosaic = cv.CreateImage((self.height, self.width), 8, 3)
cuav_util.zero_image(self.mosaic)
self.display_regions = grid_width * grid_height
self.regions = []
self.regions_sorted = []
self.page = 0
self.sort_type = 'Time'
self.images = []
self.current_view = 0
self.last_view_latlon = None
self.view_filename = None
self.full_res = False
self.boundary = []
self.displayed_image = None
self.last_click_position = None
self.c_params = C
self.camera_settings = camera_settings
self.image_settings = image_settings
self.start_menu = start_menu
self.has_started = not start_menu
import wx
self.image_mosaic = mp_image.MPImage(title='Mosaic',
mouse_events=True,
key_events=True,
auto_size=True)
self.slipmap = slipmap
self.selected_region = 0
self.view_image = None
self.brightness = 1
# dictionary of image requests, contains True if fullres image is wanted
self.image_requests = {}
self.slipmap.add_callback(functools.partial(self.map_callback))
self.add_menus()
def test_gps_position_from_image_region():
frame_time = 1478954763.0
pos = mav_position.MavPosition(-50, 145, 120, 0, 0, 90, frame_time)
region = cuav_region.Region(10, 10, 25, 23, None, scan_score=450)
C = CameraParams(lens=4.0,
sensorwidth=5.0,
xresolution=1024,
yresolution=800)
(lat, lon) = gps_position_from_image_region(region,
pos,
width=1024,
height=800,
C=C,
altitude=None)
assert abs(-49.99934 - lat) < 0.00001
assert abs(145.00078 - lon) < 0.00001
def gps_position_from_xy(x, y, pos, C=CameraParams(), altitude=None):
'''
return a GPS position in an image given a MavPosition object
and an image x,y position
'''
if pos is None:
return None
width=C.xresolution
height=C.yresolution
# assume the image came from the same camera but may no longer be original size
scale_x = float(C.xresolution)/float(width)
scale_y = float(C.yresolution)/float(height)
x *= scale_x
y *= scale_y
if altitude is None:
altitude = pos.altitude
return pixel_coordinates(x, y, pos.lat, pos.lon, altitude,
pos.pitch, pos.roll, pos.yaw, C)
def __init__(self, mpstate):
super(CameraViewModule, self).__init__(mpstate, "cameraview")
self.add_command('cameraview', self.cmd_cameraview, "camera view")
self.roll = 0
self.pitch = 0
self.yaw = 0
self.mount_roll = 0
self.mount_pitch = 0
self.mount_yaw = 0
self.height = 0
self.lat = 0
self.lon = 0
self.home_height = 0
self.hdg = 0
self.elevation_model = mp_elevation.ElevationModel()
self.camera_params = CameraParams() # TODO how to get actual camera params
self.view_settings = mp_settings.MPSettings(
[ ('r', float, 0.5),
('g', float, 0.5),
('b', float, 1.0),
])
self.update_col()
def test_gps_position_from_xy():
C = CameraParams(lens=4.0,
sensorwidth=5.0,
xresolution=1024,
yresolution=800)
frame_time = 1478954763.0
pos = mav_position.MavPosition(-50, 145, 120, 0, 0, 90, frame_time)
(lat, lon) = gps_position_from_xy(512,
400,
pos,
C=C,
altitude=120,
shape=None)
assert abs(-50 - lat) < 0.00001
assert abs(145 - lon) < 0.00001
(lat, lon) = gps_position_from_xy(200,
100,
pos,
C=C,
altitude=120,
shape=None)
assert abs(-49.999589 - lat) < 0.00001
assert abs(145.000614 - lon) < 0.00001
def calibrate(imagedir, cbrow, cbcol):
nimages = 0
datapoints = []
im_dims = (0, 0)
# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = numpy.zeros((cbrow * cbcol, 3), numpy.float32)
objp[:, :2] = numpy.mgrid[0:cbcol, 0:cbrow].T.reshape(-1, 2)
# Arrays to store object points and image points from all the images.
objpoints = [] # 3d point in real world space
imgpoints = [] # 2d points in image plane.
files = file_list(imagedir, ['jpg', 'jpeg', 'png'])
for f in files:
colour = cv2.imread(f)
grey = cv2.cvtColor(colour, cv2.COLOR_BGR2GRAY)
ret, corners = cv2.findChessboardCorners(
grey, (cbcol, cbrow), flags=cv2.CALIB_CB_ADAPTIVE_THRESH)
if (ret):
print('using ' + f)
cv2.cornerSubPix(
grey, corners, (11, 11), (-1, -1),
(cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.01))
objpoints.append(objp)
imgpoints.append(corners)
im_dims = grey.shape[:2]
if len(imgpoints) == 0:
print("Not enough good quality images. Aborting")
return
ret, K, D, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints,
grey.shape[::-1], None, None)
# storing results using CameraParams
C = CameraParams(lens=lens,
sensorwidth=sensorwidth,
xresolution=im_dims[1],
yresolution=im_dims[0])
C.setParams(K, D)
C.save(os.path.join(imagedir, "paramsout.json"))
print("Saved params in " + os.path.join(imagedir, "paramsout.json"))
def test_Mosaic():
#slipmap = mp_slipmap.MPSlipMap(service='GoogleSat', elevation=True, title='Map')
#mocked_slipmap.return_value = 1
#monkeypatch.setattr('slipmap', lambda x: 1)
mocked_slipmap = mock.MagicMock(return_value=1)
C_params = CameraParams(lens=4.0, sensorwidth=5.0, xresolution=1280, yresolution=960)
mosaic = cuav_mosaic.Mosaic(mocked_slipmap, C=C_params)
mosaic.set_mosaic_size((200, 200))
assert mosaic.mosaic.shape == (175, 175, 3)
f = os.path.join(os.getcwd(), 'tests', 'testdata', 'raw2016111223465120Z.png')
img = cv2.imread(f)
pos = mav_position.MavPosition(-30, 145, 34.56, 20, -56.67, 345, frame_time=1478994408.76)
regions = []
regions.append(cuav_region.Region(1020, 658, 1050, 678, (30, 30), scan_score=20))
regions.append(cuav_region.Region(30, 54, 50, 74, (20, 20), scan_score=15))
regions.append(cuav_region.Region(30, 54, 55, 79, (25, 25), scan_score=10))
for i in range(40):
regions.append(cuav_region.Region(200, 600, 220, 620, (20, 20), scan_score=45))
composite = cuav_region.CompositeThumbnail(img, regions)
thumbs = cuav_mosaic.ExtractThumbs(composite, len(regions))
mosaic.add_regions(regions, thumbs, f, pos)
mosaic.add_image(1478994408.76, f, pos)
mosaic.show_region(0)
mosaic.view_imagefile(f)
assert mosaic.find_image_idx(f) == 0
mosaic.view_imagefile_by_idx(0)
mocked_key = mock.MagicMock(return_value=1)
mocked_key.objkey = "region 1"
assert mosaic.show_selected(mocked_key) == True
mosaic.show_closest((-30, 145), mocked_key)
mosaic.view_image.terminate()
#mosaic.map_menu_callback
#mosaic.map_callback
OBC_boundary = cuav_util.polygon_load(os.path.join(os.getcwd(), 'tests', 'testdata', 'OBC_boundary.txt'))
mosaic.set_boundary(OBC_boundary)
mosaic.change_page(1)
mosaic.hide_page()
assert len(mosaic.regions_sorted) == 25
mosaic.unhide_all()
assert len(mosaic.regions_sorted) == 43
for i in ['Score', 'ScoreReverse', 'Distinctiveness', 'Whiteness', 'Time']:
mosaic.sort_type = i
mosaic.re_sort()
#mosaic.menu_event
assert mosaic.started() == True
mosaic.popup_show_image(mosaic.regions[2])
mosaic.popup_fetch_image(mosaic.regions[2], 'fetchImageFull')
assert len(mosaic.get_image_requests()) == 1
mosaic.view_image.terminate()
#mosaic.menu_event_view
mocked_pos = mock.MagicMock(return_value=1)
mocked_pos.x = 10
mocked_pos.y = 10
assert mosaic.pos_to_region(mocked_pos) == mosaic.regions[0]
assert mosaic.objkey_to_region(mocked_key) == mosaic.regions[1]
#mosaic.mouse_event
#mosaic.mouse_event_view
mosaic.key_event(1)
assert mosaic.region_on_page(2, 0) == True
assert mosaic.region_on_page(2000, 20) == False
mosaic.mouse_region = mosaic.regions[0]
mosaic.display_mosaic_region(0)
mosaic.redisplay_mosaic()
assert mosaic.make_thumb(img, regions[0], 8).shape == (8, 8, 3)
assert mosaic.make_thumb(img, regions[0], 30).shape == (30, 30, 3)
mosaic.tag_image(1478994408.76)
#mosaic.check_events
mosaic.image_mosaic.terminate()
def __init__(self):
self.running = False
self.unload = threading.Event()
self.unload.clear()
self.capture_thread = None
self.save_thread = None
self.scan_thread1 = None
self.scan_thread2 = None
self.transmit_thread = None
self.view_thread = None
self.settings = mp_settings.MPSettings(
[
("depth", int, 8),
("gcs_address", str, None),
("gcs_view_port", int, 7543),
("bandwidth", int, 40000),
("bandwidth2", int, 2000),
("capture_brightness", int, 150),
("gamma", int, 950),
("brightness", float, 1.0),
("quality", int, 75),
("save_pgm", int, 1),
("transmit", int, 1),
("roll_stabilised", int, 1),
("minscore", int, 75),
("minscore2", int, 500),
("altitude", int, None),
("send1", int, 1),
("send2", int, 1),
("maxqueue1", int, None),
("maxqueue2", int, 30),
("thumbsize", int, 60),
("packet_loss", int, 0),
("gcs_slave", str, None),
("filter_type", str, "simple"),
("fullres", int, 0),
]
)
self.capture_count = 0
self.scan_count = 0
self.error_count = 0
self.error_msg = None
self.region_count = 0
self.fps = 0
self.scan_fps = 0
self.cam = None
self.save_queue = Queue.Queue()
self.scan_queue = Queue.Queue()
self.transmit_queue = Queue.Queue()
self.viewing = False
self.c_params = CameraParams(lens=4.0)
self.jpeg_size = 0
self.xmit_queue = 0
self.xmit_queue2 = 0
self.efficiency = 1.0
self.last_watch = 0
self.frame_loss = 0
self.boundary = None
self.boundary_polygon = None
self.bandwidth_used = 0
self.rtt_estimate = 0
self.bsocket = None
self.bsend2 = None
self.bsend_slave = None
# setup directory for images
self.camera_dir = os.path.join(os.path.dirname(mpstate.logfile_name), "camera")
cuav_util.mkdir_p(self.camera_dir)
self.mpos = mav_position.MavInterpolator(backlog=5000, gps_lag=0.3)
self.joelog = cuav_joe.JoeLog(os.path.join(self.camera_dir, "joe.log"), append=mpstate.continue_mode)
# load camera params
path = os.path.join(
os.path.dirname(os.path.realpath(__file__)), "..", "..", "..", "cuav", "data", "chameleon1_arecont0.json"
)
self.c_params.load(path)
def __init__(self, slipmap,
grid_width=20, grid_height=20, thumb_size=35, C=CameraParams(),
camera_settings = None,
image_settings = None,
start_menu=False,
classify=None):
self.thumb_size = thumb_size
self.width = grid_width * thumb_size
self.height = grid_height * thumb_size
self.mosaic = cv.CreateImage((self.height,self.width),8,3)
cuav_util.zero_image(self.mosaic)
self.display_regions = grid_width*grid_height
self.regions = []
self.regions_sorted = []
self.regions_hidden = set()
self.mouse_region = None
self.ridx_by_frame_time = {}
self.page = 0
self.sort_type = 'Time'
self.images = []
self.current_view = 0
self.last_view_latlon = None
self.view_filename = None
self.full_res = False
self.boundary = []
self.displayed_image = None
self.last_click_position = None
self.c_params = C
self.camera_settings = camera_settings
self.image_settings = image_settings
self.start_menu = start_menu
self.classify = classify
self.has_started = not start_menu
import wx
self.image_mosaic = mp_image.MPImage(title='Mosaic',
mouse_events=True,
key_events=True,
auto_size=False,
report_size_changes=True)
self.slipmap = slipmap
self.selected_region = 0
self.view_image = None
self.brightness = 1
# dictionary of image requests, contains True if fullres image is wanted
self.image_requests = {}
self.slipmap.add_callback(functools.partial(self.map_callback))
if classify:
import lxml.objectify, lxml.etree
with open(classify) as f:
categories = lxml.objectify.fromstring(f.read())
cat_names = set()
self.categories = []
try:
for c in categories.category:
self.categories.append((c.get('shortcut') or '', c.text))
if c.text in cat_names:
print 'WARNING: category name',c.text,'used more than once'
else:
cat_names.add(c.text)
except AttributeError as ex:
print ex
print 'failed to load any categories for classification'
self.region_class = lxml.objectify.E.regions()
self.add_menus()
def __init__(self):
self.running = False
self.unload = threading.Event()
self.unload.clear()
self.capture_thread = None
self.save_thread = None
self.scan_thread1 = None
self.scan_thread2 = None
self.transmit_thread = None
self.view_thread = None
self.settings = mp_settings.MPSettings(
[ ('depth', int, 8),
('gcs_address', str, None),
('gcs_view_port', int, 7543),
('bandwidth', int, 40000),
('bandwidth2', int, 2000),
('capture_brightness', int, 150),
('gamma', int, 950),
('brightness', float, 1.0),
('quality', int, 75),
('save_pgm', int, 1),
('transmit', int, 1),
('roll_stabilised', int, 1),
('minscore', int, 75),
('minscore2', int, 500),
('altitude', int, None),
('send1', int, 1),
('send2', int, 1),
('maxqueue1', int, None),
('maxqueue2', int, 30),
('thumbsize', int, 60),
('packet_loss', int, 0),
('gcs_slave', str, None)
]
)
self.capture_count = 0
self.scan_count = 0
self.error_count = 0
self.error_msg = None
self.region_count = 0
self.fps = 0
self.scan_fps = 0
self.cam = None
self.save_queue = Queue.Queue()
self.scan_queue = Queue.Queue()
self.transmit_queue = Queue.Queue()
self.viewing = False
self.c_params = CameraParams(lens=4.0)
self.jpeg_size = 0
self.xmit_queue = 0
self.xmit_queue2 = 0
self.efficiency = 1.0
self.last_watch = 0
self.frame_loss = 0
self.boundary = None
self.boundary_polygon = None
self.bandwidth_used = 0
self.rtt_estimate = 0
self.bsocket = None
self.bsend2 = None
self.bsend_slave = None
# setup directory for images
self.camera_dir = os.path.join(os.path.dirname(mpstate.logfile_name),
"camera")
cuav_util.mkdir_p(self.camera_dir)
self.mpos = mav_position.MavInterpolator(backlog=5000, gps_lag=0.3)
self.joelog = cuav_joe.JoeLog(os.path.join(self.camera_dir, 'joe.log'), append=mpstate.continue_mode)
# load camera params
path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', '..', '..',
'cuav', 'data', 'chameleon1_arecont0.json')
self.c_params.load(path)
