def convertRawToBGR(pgm):
global image_width, image_height
raw = pgm.array
print 'mock_flea::convertRawToBGR debayer'
bgr = numpy.zeros((image_height, image_width, 3), dtype='uint8')
scanner.debayer(raw, bgr)
return bgr
def convertRawToBGR(pgm):
global image_width, image_height
raw = pgm.array
print 'mock_flea::convertRawToBGR debayer'
bgr = numpy.zeros((image_height, image_width, 3), dtype='uint8')
scanner.debayer(raw, bgr)
return bgr
def convertRawToBGR(raw):
global image_width, image_height
print 'flea::convertRawToBGR debayer'
bgr = numpy.zeros((image_height, image_width, 3), dtype='uint8')
try:
scanner.debayer(raw, bgr)
except Exception, msg:
print 'Exception: %s' % msg
def convertRawToBGR(raw):
global image_width, image_height
print 'flea::convertRawToBGR debayer'
bgr = numpy.zeros((image_height, image_width, 3), dtype='uint8')
try:
scanner.debayer(raw, bgr)
except Exception, msg:
print 'Exception: %s' % msg
def bayer_thread():
'''thread for debayering images'''
while True:
frame_time, im = state.bayer_queue.get()
im_colour = numpy.zeros((960,1280,3),dtype='uint8')
scanner.debayer(im, im_colour)
if opts.compress:
state.compress_queue.put((frame_time, im_colour))
if opts.scan:
im_640 = numpy.zeros((480,640,3),dtype='uint8')
scanner.downsample(im_colour, im_640)
state.scan_queue.put((frame_time, im_640))
def bayer_thread():
'''thread for debayering images'''
while True:
frame_time, im = state.bayer_queue.get()
im_colour = numpy.zeros((960,1280,3),dtype='uint8')
scanner.debayer(im, im_colour)
if opts.compress:
state.compress_queue.put((frame_time, im_colour))
if opts.scan:
im_640 = numpy.zeros((480,640,3),dtype='uint8')
scanner.downsample(im_colour, im_640)
state.scan_queue.put((frame_time, im_640))
def scan_thread():
'''image scanning thread'''
state = mpstate.camera_state
while not state.unload.wait(0.02):
try:
# keep the queue size below 100, so we don't run out of memory
if state.scan_queue.qsize() > 100:
(frame_time,im) = state.scan_queue.get(timeout=0.2)
(frame_time,im) = state.scan_queue.get(timeout=0.2)
except Queue.Empty:
continue
t1 = time.time()
im_full = numpy.zeros((960,1280,3),dtype='uint8')
im_640 = numpy.zeros((480,640,3),dtype='uint8')
scanner.debayer(im, im_full)
scanner.downsample(im_full, im_640)
if state.settings.fullres:
img_scan = im_full
else:
img_scan = im_640
regions = scanner.scan(img_scan)
if state.settings.filter_type=='compactness':
calculate_compactness = True
else:
calculate_compactness = False
regions = cuav_region.RegionsConvert(regions,
cuav_util.image_shape(img_scan),
cuav_util.image_shape(im_full),
calculate_compactness)
t2 = time.time()
state.scan_fps = 1.0 / (t2-t1)
state.scan_count += 1
regions = cuav_region.filter_regions(im_full, regions, min_score=min(state.settings.minscore,state.settings.minscore2),
filter_type=state.settings.filter_type)
state.region_count += len(regions)
if state.transmit_queue.qsize() < 100:
state.transmit_queue.put((frame_time, regions, im_full, im_640))
def debayer(filename, show=True):
'''debayer an image'''
pgm = cuav_util.PGM(filename)
img = numpy.zeros((960,1280,3),dtype='uint8')
if opts.gamma != 0:
img8 = numpy.zeros((960,1280,1),dtype='uint8')
scanner.gamma_correct(pgm.array, img8, opts.gamma)
else:
img8 = pgm.array
scanner.debayer(img8, img)
color_img = cv.CreateImageHeader((1280, 960), 8, 3)
cv.SetData(color_img, img)
if opts.half:
half_img = cv.CreateImage((640,480), 8, 3)
cv.Resize(color_img, half_img)
color_img = half_img
cv.ConvertScale(color_img, color_img, scale=opts.brightness)
if show:
cv.ShowImage('Bayer', color_img)
return (color_img, pgm)
def debayer(filename, show=True):
'''debayer an image'''
pgm = cuav_util.PGM(filename)
img = numpy.zeros((960, 1280, 3), dtype='uint8')
if opts.gamma != 0:
img8 = numpy.zeros((960, 1280, 1), dtype='uint8')
scanner.gamma_correct(pgm.array, img8, opts.gamma)
else:
img8 = pgm.array
scanner.debayer(img8, img)
color_img = cv.CreateImageHeader((1280, 960), 8, 3)
cv.SetData(color_img, img)
if opts.half:
half_img = cv.CreateImage((640, 480), 8, 3)
cv.Resize(color_img, half_img)
color_img = half_img
cv.ConvertScale(color_img, color_img, scale=opts.brightness)
if show:
cv.ShowImage('Bayer', color_img)
return (color_img, pgm)
def scan_thread():
'''image scanning thread'''
state = mpstate.camera_state
while not state.unload.wait(0.02):
try:
# keep the queue size below 100, so we don't run out of memory
if state.scan_queue.qsize() > 100:
(frame_time, im) = state.scan_queue.get(timeout=0.2)
(frame_time, im) = state.scan_queue.get(timeout=0.2)
except Queue.Empty:
continue
t1 = time.time()
im_full = numpy.zeros((960, 1280, 3), dtype='uint8')
im_640 = numpy.zeros((480, 640, 3), dtype='uint8')
scanner.debayer(im, im_full)
scanner.downsample(im_full, im_640)
if state.settings.fullres:
img_scan = im_full
else:
img_scan = im_640
regions = scanner.scan(img_scan)
regions = cuav_region.RegionsConvert(regions,
cuav_util.image_shape(img_scan),
cuav_util.image_shape(im_full))
t2 = time.time()
state.scan_fps = 1.0 / (t2 - t1)
state.scan_count += 1
regions = cuav_region.filter_regions(
im_full,
regions,
min_score=min(state.settings.minscore, state.settings.minscore2),
filter_type=state.settings.filter_type)
state.region_count += len(regions)
if state.transmit_queue.qsize() < 100:
state.transmit_queue.put((frame_time, regions, im_full, im_640))
start_thread(save_thread)
i=0
lost = 0
while True:
try:
frame_time, frame_counter, shutter = chameleon.capture(h, 300, im)
except chameleon.error, msg:
lost += 1
continue
if frame_time < last_frame_time:
base_time += 128
save_queue.put((frame_time+base_time, im))
last_frame_time = frame_time
img_colour = numpy.zeros((960,1280,3),dtype='uint8')
scanner.debayer(im, img_colour)
img_colour = cv.GetImage(cv.fromarray(img_colour))
if opts.half:
img_640 = cv.CreateImage((640,480), 8, 3)
cv.Resize(img_colour, img_640)
img_colour = img_640
cv.ConvertScale(img_colour, img_colour, scale=opts.brightness)
cv.ShowImage('Viewer', img_colour)
key = cv.WaitKey(1)
i += 1
if i % 10 == 0:
tdiff = time.time() - tstart
print("captured %u lost %u %.1f fps shutter=%f" % (
i, lost,
def process(args):
'''process a set of files'''
global slipmap, mosaic
scan_count = 0
files = []
for a in args:
if os.path.isdir(a):
files.extend(glob.glob(os.path.join(a, '*.pgm')))
else:
files.append(a)
files.sort()
num_files = len(files)
print("num_files=%u" % num_files)
region_count = 0
joes = []
if opts.mavlog:
mpos = mav_position.MavInterpolator(gps_lag=opts.gps_lag)
mpos.set_logfile(opts.mavlog)
else:
mpos = None
if opts.boundary:
boundary = cuav_util.polygon_load(opts.boundary)
else:
boundary = None
if opts.mosaic:
slipmap = mp_slipmap.MPSlipMap(service='GoogleSat', elevation=True, title='Map')
icon = slipmap.icon('planetracker.png')
slipmap.add_object(mp_slipmap.SlipIcon('plane', (0,0), icon, layer=3, rotation=0,
follow=True,
trail=mp_slipmap.SlipTrail()))
C_params = cam_params.CameraParams(lens=opts.lens)
path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', '..',
'cuav', 'data', 'chameleon1_arecont0.json')
C_params.load(path)
mosaic = cuav_mosaic.Mosaic(slipmap, C=C_params)
if boundary is not None:
mosaic.set_boundary(boundary)
if opts.joe:
joes = cuav_util.polygon_load(opts.joe)
if boundary:
for i in range(len(joes)):
joe = joes[i]
if cuav_util.polygon_outside(joe, boundary):
print("Error: joe outside boundary", joe)
return
icon = slipmap.icon('flag.png')
slipmap.add_object(mp_slipmap.SlipIcon('joe%u' % i, (joe[0],joe[1]), icon, layer=4))
joelog = cuav_joe.JoeLog('joe.log')
if opts.view:
viewer = mp_image.MPImage(title='Image')
frame_time = 0
for f in files:
if mpos:
frame_time = cuav_util.parse_frame_time(f)
try:
if opts.roll_stabilised:
roll = 0
else:
roll = None
pos = mpos.position(frame_time, opts.max_deltat,roll=roll)
slipmap.set_position('plane', (pos.lat, pos.lon), rotation=pos.yaw)
except mav_position.MavInterpolatorException as e:
print e
pos = None
else:
pos = None
# check for any events from the map
if opts.mosaic:
slipmap.check_events()
mosaic.check_events()
if f.endswith('.pgm'):
pgm = cuav_util.PGM(f)
im = pgm.array
if pgm.eightbit:
im_8bit = im
else:
im_8bit = numpy.zeros((960,1280,1),dtype='uint8')
if opts.gamma != 0:
scanner.gamma_correct(im, im_8bit, opts.gamma)
else:
scanner.reduce_depth(im, im_8bit)
im_full = numpy.zeros((960,1280,3),dtype='uint8')
scanner.debayer(im_8bit, im_full)
im_640 = numpy.zeros((480,640,3),dtype='uint8')
scanner.downsample(im_full, im_640)
else:
im_orig = cv.LoadImage(f)
(w,h) = cuav_util.image_shape(im_orig)
im_full = im_orig
im_640 = cv.CreateImage((640, 480), 8, 3)
cv.Resize(im_full, im_640, cv.CV_INTER_NN)
im_640 = numpy.ascontiguousarray(cv.GetMat(im_640))
im_full = numpy.ascontiguousarray(cv.GetMat(im_full))
count = 0
total_time = 0
img_scan = im_640
t0=time.time()
for i in range(opts.repeat):
if opts.fullres:
regions = scanner.scan(im_full)
regions = cuav_region.RegionsConvert(regions, 1280, 960)
else:
regions = scanner.scan(img_scan)
regions = cuav_region.RegionsConvert(regions)
count += 1
t1=time.time()
if opts.filter:
regions = cuav_region.filter_regions(im_full, regions, frame_time=frame_time, min_score=opts.minscore,
filter_type=opts.filter_type)
scan_count += 1
# optionally link all the images with joe into a separate directory
# for faster re-running of the test with just joe images
if pos and opts.linkjoe and len(regions) > 0:
cuav_util.mkdir_p(opts.linkjoe)
if not cuav_util.polygon_outside((pos.lat, pos.lon), boundary):
joepath = os.path.join(opts.linkjoe, os.path.basename(f))
if os.path.exists(joepath):
os.unlink(joepath)
os.symlink(f, joepath)
if pos and len(regions) > 0:
joelog.add_regions(frame_time, regions, pos, f, width=1280, height=960, altitude=opts.altitude)
if boundary:
regions = cuav_region.filter_boundary(regions, boundary, pos)
region_count += len(regions)
if opts.mosaic and len(regions) > 0:
composite = cuav_mosaic.CompositeThumbnail(cv.GetImage(cv.fromarray(im_full)), regions)
thumbs = cuav_mosaic.ExtractThumbs(composite, len(regions))
mosaic.add_regions(regions, thumbs, f, pos)
if opts.compress:
jpeg = scanner.jpeg_compress(im_full, opts.quality)
jpeg_filename = f[:-4] + '.jpg'
if os.path.exists(jpeg_filename):
print('jpeg %s already exists' % jpeg_filename)
continue
chameleon.save_file(jpeg_filename, jpeg)
if opts.view:
if opts.fullres:
img_view = im_full
else:
img_view = img_scan
mat = cv.fromarray(img_view)
for r in regions:
(x1,y1,x2,y2) = r.tuple()
(w,h) = cuav_util.image_shape(img_view)
x1 = x1*w//1280
x2 = x2*w//1280
y1 = y1*h//960
y2 = y2*h//960
cv.Rectangle(mat, (max(x1-2,0),max(y1-2,0)), (x2+2,y2+2), (255,0,0), 2)
cv.CvtColor(mat, mat, cv.CV_BGR2RGB)
viewer.set_image(mat)
total_time += (t1-t0)
if t1 != t0:
print('%s scan %.1f fps %u regions [%u/%u]' % (
f, count/total_time, region_count, scan_count, num_files))
def process(filename):
'''process one file'''
pgm = cuav_util.PGM(filename)
img_full_grey = pgm.array
im_full = numpy.zeros((960, 1280, 3), dtype='uint8')
im_640 = numpy.zeros((480, 640, 3), dtype='uint8')
t0 = time.time()
for i in range(opts.repeat):
scanner.debayer_half(img_full_grey, im_640)
t1 = time.time()
print('debayer: %.1f fps' % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
scanner.debayer(img_full_grey, im_full)
t1 = time.time()
print('debayer_full: %.1f fps' % (opts.repeat / (t1 - t0)))
t0 = time.time()
im_full2 = cv.CreateImage((1280, 960), 8, 3)
img_full_grey2 = cv.GetImage(cv.fromarray(img_full_grey))
for i in range(opts.repeat):
cv.CvtColor(img_full_grey2, im_full2, cv.CV_BayerBG2BGR)
t1 = time.time()
print('debayer_cv_full: %.1f fps' % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
img = cv.GetImage(cv.fromarray(im_full))
cv.CvtColor(img, img, cv.CV_RGB2HSV)
t1 = time.time()
print('RGB2HSV_full: %.1f fps' % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
img = cv.GetImage(cv.fromarray(im_640))
cv.CvtColor(img, img, cv.CV_RGB2HSV)
t1 = time.time()
print('RGB2HSV_640: %.1f fps' % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
thumb = numpy.empty((100, 100, 3), dtype='uint8')
scanner.rect_extract(im_full, thumb, 120, 125)
t1 = time.time()
print('rect_extract: %.1f fps' % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
thumb = cuav_util.SubImage(cv.GetImage(cv.fromarray(im_full)),
(120, 125, 100, 100))
t1 = time.time()
print('SubImage: %.1f fps' % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
scanner.downsample(im_full, im_640)
t1 = time.time()
print('downsample: %.1f fps' % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
scanner.scan(im_640)
t1 = time.time()
print('scan: %.1f fps' % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
scanner.scan(im_full)
t1 = time.time()
print('scan_full: %.1f fps' % (opts.repeat / (t1 - t0)))
if not hasattr(scanner, 'jpeg_compress'):
return
for quality in [30, 40, 50, 60, 70, 80, 90, 95]:
t0 = time.time()
for i in range(opts.repeat):
jpeg = cPickle.dumps(ImagePacket(
time.time(), scanner.jpeg_compress(im_full, quality)),
protocol=cPickle.HIGHEST_PROTOCOL)
t1 = time.time()
print('jpeg full quality %u: %.1f fps %u bytes' %
(quality, opts.repeat / (t1 - t0), len(bytes(jpeg))))
for quality in [30, 40, 50, 60, 70, 80, 90, 95]:
t0 = time.time()
for i in range(opts.repeat):
img2 = cv.fromarray(im_full)
jpeg = cPickle.dumps(ImagePacket(
time.time(),
cv.EncodeImage(
'.jpeg', img2,
[cv.CV_IMWRITE_JPEG_QUALITY, quality]).tostring()),
protocol=cPickle.HIGHEST_PROTOCOL)
t1 = time.time()
print('EncodeImage full quality %u: %.1f fps %u bytes' %
(quality, opts.repeat / (t1 - t0), len(bytes(jpeg))))
for quality in [30, 40, 50, 60, 70, 80, 90, 95]:
t0 = time.time()
for i in range(opts.repeat):
jpeg = cPickle.dumps(ImagePacket(
time.time(), scanner.jpeg_compress(im_640, quality)),
protocol=cPickle.HIGHEST_PROTOCOL)
t1 = time.time()
print('jpeg 640 quality %u: %.1f fps %u bytes' %
(quality, opts.repeat / (t1 - t0), len(bytes(jpeg))))
for thumb_size in [10, 20, 40, 60, 80, 100]:
thumb = numpy.zeros((thumb_size, thumb_size, 3), dtype='uint8')
t0 = time.time()
for i in range(opts.repeat):
scanner.rect_extract(im_full, thumb, 0, 0)
jpeg = cPickle.dumps(ImagePacket(time.time(),
scanner.jpeg_compress(thumb, 85)),
protocol=cPickle.HIGHEST_PROTOCOL)
t1 = time.time()
print('thumb %u quality 85: %.1f fps %u bytes' %
(thumb_size, opts.repeat / (t1 - t0), len(bytes(jpeg))))
def process(filename):
"""process one file"""
pgm = cuav_util.PGM(filename)
img_full_grey = pgm.array
im_full = numpy.zeros((960, 1280, 3), dtype="uint8")
im_640 = numpy.zeros((480, 640, 3), dtype="uint8")
t0 = time.time()
for i in range(opts.repeat):
scanner.debayer(img_full_grey, im_640)
t1 = time.time()
print("debayer: %.1f fps" % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
scanner.debayer_full(img_full_grey, im_full)
t1 = time.time()
print("debayer_full: %.1f fps" % (opts.repeat / (t1 - t0)))
t0 = time.time()
im_full2 = cv.CreateImage((1280, 960), 8, 3)
img_full_grey2 = cv.GetImage(cv.fromarray(img_full_grey))
for i in range(opts.repeat):
cv.CvtColor(img_full_grey2, im_full2, cv.CV_BayerBG2BGR)
t1 = time.time()
print("debayer_cv_full: %.1f fps" % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
img = cv.GetImage(cv.fromarray(im_full))
cv.CvtColor(img, img, cv.CV_RGB2HSV)
t1 = time.time()
print("RGB2HSV_full: %.1f fps" % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
img = cv.GetImage(cv.fromarray(im_640))
cv.CvtColor(img, img, cv.CV_RGB2HSV)
t1 = time.time()
print("RGB2HSV_640: %.1f fps" % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
thumb = numpy.empty((100, 100, 3), dtype="uint8")
scanner.rect_extract(im_full, thumb, 120, 125)
t1 = time.time()
print("rect_extract: %.1f fps" % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
thumb = cuav_util.SubImage(cv.GetImage(cv.fromarray(im_full)), (120, 125, 100, 100))
t1 = time.time()
print("SubImage: %.1f fps" % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
scanner.downsample(im_full, im_640)
t1 = time.time()
print("downsample: %.1f fps" % (opts.repeat / (t1 - t0)))
t0 = time.time()
for i in range(opts.repeat):
scanner.scan(im_640)
t1 = time.time()
print("scan: %.1f fps" % (opts.repeat / (t1 - t0)))
if not hasattr(scanner, "jpeg_compress"):
return
for quality in [30, 40, 50, 60, 70, 80, 90, 95]:
t0 = time.time()
for i in range(opts.repeat):
jpeg = cPickle.dumps(
ImagePacket(time.time(), scanner.jpeg_compress(im_full, quality)), protocol=cPickle.HIGHEST_PROTOCOL
)
t1 = time.time()
print("jpeg full quality %u: %.1f fps %u bytes" % (quality, opts.repeat / (t1 - t0), len(bytes(jpeg))))
for quality in [30, 40, 50, 60, 70, 80, 90, 95]:
t0 = time.time()
for i in range(opts.repeat):
img2 = cv.fromarray(im_full)
jpeg = cPickle.dumps(
ImagePacket(
time.time(), cv.EncodeImage(".jpeg", img2, [cv.CV_IMWRITE_JPEG_QUALITY, quality]).tostring()
),
protocol=cPickle.HIGHEST_PROTOCOL,
)
t1 = time.time()
print("EncodeImage full quality %u: %.1f fps %u bytes" % (quality, opts.repeat / (t1 - t0), len(bytes(jpeg))))
for quality in [30, 40, 50, 60, 70, 80, 90, 95]:
t0 = time.time()
for i in range(opts.repeat):
jpeg = cPickle.dumps(
ImagePacket(time.time(), scanner.jpeg_compress(im_640, quality)), protocol=cPickle.HIGHEST_PROTOCOL
)
t1 = time.time()
print("jpeg 640 quality %u: %.1f fps %u bytes" % (quality, opts.repeat / (t1 - t0), len(bytes(jpeg))))
for thumb_size in [10, 20, 40, 60, 80, 100]:
thumb = numpy.zeros((thumb_size, thumb_size, 3), dtype="uint8")
t0 = time.time()
for i in range(opts.repeat):
scanner.rect_extract(im_full, thumb, 0, 0)
jpeg = cPickle.dumps(
ImagePacket(time.time(), scanner.jpeg_compress(thumb, 85)), protocol=cPickle.HIGHEST_PROTOCOL
)
t1 = time.time()
print("thumb %u quality 85: %.1f fps %u bytes" % (thumb_size, opts.repeat / (t1 - t0), len(bytes(jpeg))))
def convertRawToBGR(img): global image_height, image_width bgr = numpy.zeros((image_height, image_width, 3), dtype='uint8') print 'chameleon::convertRawToBGR debayer' scanner.debayer(img, bgr) return bgr
start_thread(save_thread)
i = 0
lost = 0
while True:
try:
frame_time, frame_counter, shutter = chameleon.capture(h, 300, im)
except chameleon.error, msg:
lost += 1
continue
if frame_time < last_frame_time:
base_time += 128
save_queue.put((frame_time + base_time, im))
last_frame_time = frame_time
img_colour = numpy.zeros((960, 1280, 3), dtype='uint8')
scanner.debayer(im, img_colour)
img_colour = cv.GetImage(cv.fromarray(img_colour))
if opts.half:
img_640 = cv.CreateImage((640, 480), 8, 3)
cv.Resize(img_colour, img_640)
img_colour = img_640
cv.ConvertScale(img_colour, img_colour, scale=opts.brightness)
cv.ShowImage('Viewer', img_colour)
key = cv.WaitKey(1)
i += 1
if i % 10 == 0:
tdiff = time.time() - tstart
print("captured %u lost %u %.1f fps shutter=%f" %
(i, lost, 10 / tdiff, shutter))
