def demo_overlay():
"""How to overlay images and highlight regions."""
# Overlay
rgb = imutils.imread('../data/flamingo.jpg', mode='L')
# Generate some data to overlay
im_height, im_width = rgb.shape[0], rgb.shape[1]
peak_pos = (im_width * 0.75, im_height * 0.15)
xv, yv = np.meshgrid(np.arange(0, im_width), np.arange(0, im_height))
overlay = np.exp(
-(np.power(xv - peak_pos[0], 2) + np.power(yv - peak_pos[1], 2)) /
(3e4))
overlay_vis = imvis.overlay(imvis.pseudocolor(overlay), rgb, 0.7)
# Highlight regions
rgb = imutils.imread('../data/flamingo.jpg', mode='RGB')
rgb_mask = np.zeros((rgb.shape[0], rgb.shape[1]), dtype=np.uint8)
rgb_mask[160:334, 120:290] = 1
highlight = imvis.highlight(rgb, rgb_mask)
# highlight another region, this time in blue
rgb_mask[:] = 0
rgb_mask[200:374, 250:420] = 1
highlight = imvis.highlight(highlight, rgb_mask, color=(0, 0, 255))
# Combine all "colored" images:
collage = imvis.make_collage([overlay_vis, highlight],
padding=5,
bg_color=(255, 255, 255))
imvis.imshow(collage, title="Overlay & Highlights", wait_ms=-1)
def _col_ir(f):
#TODO
# Normalize/stretch, etc. using: self._args.max_ir
if f.dtype == np.uint8:
return f
return imvis.pseudocolor(f,
limits=None,
color_map=colormaps.colormap_turbo_rgb)
def _process_next_frameset(self, capture, frameset):
# assert len(frameset) == 1 # Currently, we assume there's only one mobotix camera connected!
if frameset[0] is None:
self._streamer.stop()
return
if self._args.verbose:
# Measure time between received framesets
if self._mean_ms_between_framesets is None:
ms_between_framesets = 0
else:
ms_between_framesets = pyutils.ttoc('[frameset received]')
self._mean_ms_between_framesets = ms_between_framesets if self._mean_ms_between_framesets is None else 0.9 * self._mean_ms_between_framesets + 0.1 * ms_between_framesets
if ms_between_framesets > 0:
print(
'Frameset received after {:.2f} ms, avg. framerate {:.1f}'.
format(ms_between_framesets,
1000.0 / self._mean_ms_between_framesets))
pyutils.tic('[frameset received]')
vis_frames = list()
vis_labels = list()
for idx, frame in enumerate(frameset):
frame_lbl = capture.frame_label(idx)
vis_frame = imvis.pseudocolor(frame, [0, 5000], color_map=colormaps.colormap_turbo_rgb)\
if capture.is_depth(idx) or capture.is_infrared(idx) else frame
vis_frames.append(vis_frame)
vis_labels.append(frame_lbl)
# Overlay labels
vis_frames = [
imvis.draw_text_box(vis_frames[idx],
vis_labels[idx],
(vis_frames[idx].shape[1] // 2, 40),
text_anchor='north',
bg_color=(220, 0, 0),
font_color=(0, 0, 0))
for idx in range(len(vis_frames))
]
# Forward to storage processes
self._store(capture, frameset)
# Display the live stream
collage = imvis.make_collage(vis_frames,
num_images_per_row=2,
padding=0,
fixed_size_per_image=(640, 480))
k = imvis.imshow(collage, "Live view", wait_ms=10)
if k == ord('q') or k == 27:
self._streamer.stop()
def demo_pseudocolor():
"""Pseudocoloring."""
peaks = imutils.imread('../data/peaks.png', mode='L')
# For visualization purposes only, reduce input to a few
# distinct categories/labels:
data = ((peaks / 25) - 5).astype(np.int16)
names = ['Bone', 'Magma', 'Viridis']
images = list()
for name in names:
pc = imvis.pseudocolor(
data,
limits=None, # Compute min/max from data
color_map=colormaps.by_name(name, return_rgb=True))
images.append(pc)
# Display as a single collage
padding = 10
# Add alpha channel to render the collage nicely for the repo's README
images[0] = np.dstack(
(images[0], 255 * np.ones(images[0].shape[:2], dtype=np.uint8)))
collage = imvis.make_collage(images,
padding=padding,
fixed_size_per_image=(200, 200),
bg_color=(0, 0, 0, 0),
num_images_per_row=len(images))
# Add labels
height, width = collage.shape[:2]
mask_width = (width - (len(names) - 1) * padding) / len(names)
for i in range(len(names)):
pos = (i * (mask_width + padding) + mask_width / 2, height - 10)
collage = imvis.draw_text_box(collage,
names[i],
pos,
text_anchor='south',
bg_color=(0, 0, 0),
font_color=(-1, -1, -1),
font_scale=1.0,
font_thickness=1,
padding=5,
fill_opacity=0.8)
imvis.imshow(collage, title='Pseudocoloring', wait_ms=-1)
imutils.imsave('../../doc/example-pseudocolor.png', collage)
def _vis_depth_colormap(self, f, cm):
return imvis.pseudocolor(f, limits=self._depth_range_vis, color_map=cm)
def vis_depth(f, max_depth=2000):
return imvis.pseudocolor(f,
limits=[0, max_depth],
color_map=colormaps.colormap_turbo_rgb)
def _col_depth(f):
# return imutils.transform(f, 'depth2surfnorm', 'surfnorm2rgb')
return imvis.pseudocolor(f,
limits=[0, self._args.max_depth],
color_map=colormaps.colormap_turbo_rgb)
def demo(pseudocolor=True, inspect=False):
imgs = [imutils.imread('../data/ninja-01.jpg'), imutils.imread('../data/ninja-02.jpg')]
bgmodels = list()
bgmodel = bgm.BackgroundModel()
bgmodel.approximate_median_bgm(
adaptation_step=5,
fg_report_threshold=50,
median_on_grayscale=True)
bgmodels.append(bgmodel)
bgmodel = bgm.BackgroundModel()
bgmodel.block_mean_bgm(
block_size=(16, 16),
block_overlap=0.5,
update_rate=0.01,
fg_report_threshold=50,
channel='grayscale')
bgmodels.append(bgmodel)
bgmodel = bgm.BackgroundModel()
bgmodel.gaussian_mixture_bgm(
history=500,
detect_shadows=True,
var_thresh=100,
comp_thresh=0.05)
bgmodels.append(bgmodel)
bgmodel = bgm.BackgroundModel()
bgmodel.normalized_rgb_bgm(
report_as_binary=False,
# binary_reporting_threshold=20,
update_rate=0.1,
alpha=0.1,
beta=1.0)
bgmodels.append(bgmodel)
print("""
! Note that the reported initialization time for the first BGM includes
library initialization - maybe OpenCV (haven't tracked that down yet).
""")
fg_masks = list()
for bgmodel in bgmodels:
pyutils.tic('init')
bgmodel.init(imgs[0])
t_init = pyutils.ttoc('init')
pyutils.tic('apply')
mask = bgmodel.report_changes(imgs[1])
t_apply = pyutils.ttoc('apply')
if pseudocolor:
fg_masks.append(imvis.pseudocolor(mask, limits=None, color_map=colormaps.colormap_viridis_rgb))
else:
fg_masks.append(mask)
print('init/apply: {:17s} {:7.2f} ms, {:7.2f} ms'.format(bgmodel.name(), t_init, t_apply))
if inspect:
import iminspect
iminspect.show(mask)
padding = 10
# Add alpha channel to render the README visualization nicely for web display
fg_masks[0] = np.dstack((fg_masks[0], 255 * np.ones(fg_masks[0].shape[:2], dtype=np.uint8)))
collage = imvis.make_collage(fg_masks,
padding=padding,
fixed_size_per_image=(200, 266),
bg_color=(0, 0, 0, 0),
num_images_per_row=2)
input_seq = cv2.resize(imutils.imread('../data/ninja-seq.png'), (200, 266))
collage = imvis.make_collage([input_seq, collage],
padding=padding, bg_color=(0, 0, 0, 0))
# Overlay names
height, width = collage.shape[:2]
collage = imvis.draw_text_box(collage, 'Input',
(input_seq.shape[1]/2, height/3+20), text_anchor='center', bg_color=(255, 255, 255),
font_color=(-1, -1, -1), font_scale=1.0,
font_thickness=1, padding=5, fill_opacity=0.8)
names = [bg.name() for bg in bgmodels]
mask_width = (width-input_seq.shape[1] - padding) / 2
for i in range(len(names)):
pos = (input_seq.shape[1] + padding + (i % 2) * (mask_width + padding) + mask_width/2,
(i // 2) * (266 + padding) + 266 - 10)
collage = imvis.draw_text_box(collage, names[i],
pos, text_anchor='south', bg_color=(255, 255, 255),
font_color=(-1, -1, -1), font_scale=1.0,
font_thickness=1, padding=5, fill_opacity=0.8)
imvis.imshow(collage, title="Background Subtraction", wait_ms=-1)
imutils.imsave('../../doc/example-bgm.png', collage)