def run_feature(io_list=[('features/01', '01.pkl'), ('features/02', '02.pkl')],
output_directory='features',
batch=2):
f = ImageFeature(image_feature_dir=output_directory,
extract_image_batch=batch)
io_iter = iter(io_list)
force_exit = False
while force_exit == False:
try:
inputs, outputs = next(io_iter)
except StopIteration:
force_exit = True
break
print('input is:{}, output is:{}'.format(
inputs, os.path.join(output_directory, outputs)))
f.extract_image_feature(inputs, outputs)
del f
if visualize:
from viewer import MapViewer
viewer = MapViewer(sptam, params)
cam = Camera(
dataset.cam.fx, dataset.cam.fy, dataset.cam.cx, dataset.cam.cy,
dataset.cam.width, dataset.cam.height,
params.frustum_near, params.frustum_far,
dataset.cam.baseline)
durations = []
for i in range(len(dataset)):
featurel = ImageFeature(dataset.left[i], params)
featurer = ImageFeature(dataset.right[i], params)
timestamp = dataset.timestamps[i]
time_start = time.time()
t = Thread(target=featurer.extract)
t.start()
featurel.extract()
t.join()
frame = StereoFrame(i, g2o.Isometry3d(), featurel, featurer, cam, timestamp=timestamp)
if not sptam.is_initialized():
sptam.initialize(frame)
else:
# "configs/caffe2/e2e_mask_rcnn_R_50_FPN_1x_caffe2.yaml"
# update the config options with the config file
cfg.merge_from_file(config_file)
# manual override some options
cfg.merge_from_list(["MODEL.DEVICE", args.device])
coco_demo = COCODemo(
cfg,
min_image_size=800,
confidence_threshold=0.7,
)
for i in range(n):
iml = cv.imread(dataset.left[i], cv.IMREAD_UNCHANGED)
imr = cv.imread(dataset.right[i], cv.IMREAD_UNCHANGED)
featurel = ImageFeature(iml, params)
featurer = ImageFeature(imr, params)
timestamp = dataset.timestamps[i]
time_start = time.time()
t = Thread(target=featurer.extract)
t.start()
featurel.extract()
t.join()
print('{}. frame'.format(i))
frame = StereoFrame(i, g2o.Isometry3d(), featurel, featurer, cam, timestamp=timestamp)
if not sptam0.is_initialized():
cam = Camera(dataset.cam.fx, dataset.cam.fy, dataset.cam.cx,
dataset.cam.cy, dataset.cam.width, dataset.cam.height,
params.frustum_near, params.frustum_far, dataset.cam.baseline)
durations = []
if (args.mask != ''):
f0 = open(args.mask + "-0.txt").readlines()
f1 = open(args.mask + "-1.txt").readlines()
for i in range(len(dataset))[:]:
if (args.mask != ''):
featurel = ImageFeature(
dataset.left[i],
params,
filtering=[l.split(",") for l in f0[i].split("|")][:-1]
if f0[i] != "\n" else None)
featurer = ImageFeature(
dataset.right[i],
params,
filtering=[l.split(",") for l in f1[i].split("|")][:-1]
if f1[i] != "\n" else None)
else:
featurel = ImageFeature(dataset.left[i], params)
featurer = ImageFeature(dataset.right[i], params)
timestamp = dataset.timestamps[i]
time_start = time.time()
t = Thread(target=featurer.extract)
params = Params()
ptam = RGBDPTAM(params)
if not args.no_viz:
from viewer import MapViewer
viewer = MapViewer(ptam, params)
height, width = dataset.rgb.shape[:2]
cam = Camera(dataset.cam.fx, dataset.cam.fy, dataset.cam.cx,
dataset.cam.cy, width, height, dataset.cam.scale,
params.virtual_baseline, params.depth_near, params.depth_far,
params.frustum_near, params.frustum_far)
durations = []
for i in range(len(dataset))[:]:
feature = ImageFeature(dataset.rgb[i], params)
depth = dataset.depth[i]
if dataset.timestamps is None:
timestamp = i / 20.
else:
timestamp = dataset.timestamps[i]
time_start = time.time()
feature.extract()
frame = RGBDFrame(i,
g2o.Isometry3d(),
feature,
depth,
cam,
timestamp=timestamp)
'disp12MaxDiff': 1,
'preFilterCap': 10,
'uniquenessRatio': 15,
'speckleWindowSize': 100,
'speckleRange': 1,
'mode': cv.STEREO_SGBM_MODE_SGBM_3WAY
}
if n:
iml = cv.imread(dataset.left[0], cv.IMREAD_UNCHANGED)
dseg = DynaSeg(iml, coco_demo, feature_params, disp_path, config, paraml, lk_params, mtx, dist, dilation)
for i in range(n):
iml = cv.imread(dataset.left[i], cv.IMREAD_UNCHANGED)
imr = cv.imread(dataset.right[i], cv.IMREAD_UNCHANGED)
# original
featurel = ImageFeature(iml, params)
featurer = ImageFeature(imr, params)
timestamp = dataset.timestamps[i]
time_start = time.time()
t = Thread(target=featurer.extract)
t.start()
featurel.extract()
t.join()
print('{}. frame'.format(i))
try:
frame = StereoFrame(i, g2o.Isometry3d(), featurel, featurer, cam, timestamp=timestamp)