def decode(self, data):
msg = image_t.decode(data)
if msg.pixelformat == image_t.PIXEL_FORMAT_GRAY:
return im_resize(np.asarray(bytearray(msg.data), dtype=np.uint8).reshape(msg.height, msg.width), scale=self.scale)
elif msg.pixelformat == image_t.PIXEL_FORMAT_MJPEG:
im = cv2.imdecode(np.asarray(bytearray(msg.data), dtype=np.uint8), -1)
return im_resize(im, scale=self.scale)
else:
raise RuntimeError('Unknown pixelformat for ImageDecoder')
def decode(self, msg):
try:
if self.compressed:
im = compressed_imgmsg_to_cv2(msg, self.encoding)
else:
im = self.bridge.imgmsg_to_cv2(msg, self.encoding)
except CvBridgeError as e:
raise Exception('ImageDecoder.decode :: {}'.format(e))
return im_resize(im, scale=self.scale)
def extract(self, im):
self.segnet.forward(im)
labels = self.segnet.extract(layer='argmax')
# Resize labels to image
out = labels.astype(np.uint8)
out = im_resize(out, shape=im.shape[:2][::-1], interpolation=cv2.INTER_NEAREST)
cout = np.dstack([out, out, out])
colored = cv2.LUT(cout, self.colors)
return colored
def extract(self, im):
self.segnet.forward(im)
labels = self.segnet.extract(layer='argmax')
# Resize labels to image
out = labels.astype(np.uint8)
out = im_resize(out,
shape=im.shape[:2][::-1],
interpolation=cv2.INTER_NEAREST)
cout = np.dstack([out, out, out])
colored = cv2.LUT(cout, self.colors)
return colored
def visualize(self, root=0):
if len(self.frames_) < 2:
return
if self.fixed_reference_:
ref = self.ref_frame_
root = -1
else:
assert (root >= 0 and root < len(self.frames_))
try:
ref = self.frames_[root]
except:
raise RuntimeError("Unable to index to root")
vis = {}
# Detect features in the reference image, else
# use provided features
if ref.points is not None:
pts = ref.points
else:
try:
pts = self.fdet_.process(to_gray(ref.im))
except:
return
if not len(pts):
return
print(pts.shape, pts.dtype)
# Draw epipoles across all other images/poses
for idx, f in enumerate(self.frames_):
F_10 = ref.camera.F(f.camera)
vis[idx] = plot_epipolar_line(f.im,
F_10,
pts,
im_0=ref.im if idx == 0 else None)
# print 'F b/w ref and idx={:}, \ncurr={:}\n\nF={:}\n'.format(idx, f.camera, F_10)
if len(vis):
imshow_cv('epi_out',
im_resize(np.vstack(list(vis.values())), scale=0.5))
def visualize(self, root=0):
if len(self.frames_) < 2:
return
if self.fixed_reference_:
ref_im = self.ref_frame_.im
ref_camera = self.ref_frame_.camera
root = -1
else:
assert (root >= 0 and root < len(self.frames_))
try:
ref_im = self.frames_[root].im
ref_camera = self.frames_[root].camera
except:
raise RuntimeError("Unable to index to root")
vis = {}
# Detect features in the reference image
try:
pts = self.fdet_.process(to_gray(ref_im))
# pts = pts.reshape(len(pts)/4,-1,2).mean(axis=1)
except:
return
if not len(pts):
return
# Draw epipoles across all other images/poses
for idx, f in enumerate(self.frames_):
F_10 = ref_camera.F(f.camera)
vis[idx] = plot_epipolar_line(f.im,
F_10,
pts,
im_0=ref_im if idx == 0 else None)
# print 'F b/w ref and idx={:}, \ncurr={:}\n\nF={:}\n'.format(idx, f.camera, F_10)
if len(vis):
imshow_cv('epi_out', im_resize(np.vstack(vis.values()), scale=0.5))
def dispread_process_cb(scale=1.0):
"""Scale disparity values for depth images"""
return lambda fn: im_resize(cv2.imread(fn, cv2.IMREAD_UNCHANGED), scale=scale) * scale
def imread_process_cb(scale=1.0, grayscale=False):
return lambda fn: im_resize(cv2.imread(
fn, cv2.IMREAD_GRAYSCALE if grayscale else cv2.IMREAD_UNCHANGED),
scale=scale)
def process(self, im):
boxes = self.proposer_.process(im_resize(im, scale=self.scale_))
return (boxes * 1 / self.scale_).astype(np.int32)
def write_video(fn, im, scale=1.0, as_images=False):
global g_fn_map
if fn not in g_fn_map:
g_fn_map[fn] = VideoWriter(fn, as_images=as_images)
im_scaled = im_resize(im, scale=scale) if scale != 1.0 else im
g_fn_map[fn].write(im_scaled)
