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import numpy as np
from . import color as color_module
from . import draw as draw_module
def label_colormap(n_label=256, value=None):
"""Label colormap.
Parameters
----------
n_labels: int
Number of labels (default: 256).
value: float or int
Value scale or value of label color in HSV space.
Returns
-------
cmap: numpy.ndarray, (N, 3), numpy.uint8
Label id to colormap.
"""
def bitget(byteval, idx):
return (byteval & (1 << idx)) != 0
cmap = np.zeros((n_label, 3), dtype=np.uint8)
for i in range(0, n_label):
id = i
r, g, b = 0, 0, 0
for j in range(0, 8):
r = np.bitwise_or(r, (bitget(id, 0) << 7 - j))
g = np.bitwise_or(g, (bitget(id, 1) << 7 - j))
b = np.bitwise_or(b, (bitget(id, 2) << 7 - j))
id = id >> 3
cmap[i, 0] = r
cmap[i, 1] = g
cmap[i, 2] = b
if value is not None:
hsv = color_module.rgb2hsv(cmap.reshape(1, -1, 3))
if isinstance(value, float):
hsv[:, 1:, 2] = hsv[:, 1:, 2].astype(float) * value
else:
assert isinstance(value, int)
hsv[:, 1:, 2] = value
cmap = color_module.hsv2rgb(hsv).reshape(-1, 3)
return cmap
def label2rgb(
label,
img=None,
alpha=0.5,
label_names=None,
font_size=30,
thresh_suppress=0,
colormap=None,
loc="centroid",
font_path=None,
):
"""Convert label to rgb.
Parameters
----------
label: numpy.ndarray, (H, W), int
Label image.
img: numpy.ndarray, (H, W, 3), numpy.uint8
RGB image.
alpha: float
Alpha of RGB (default: 0.5).
label_names: list of string
Label id to label name.
font_size: int
Font size (default: 30).
thresh_suppress: float
Threshold of label ratio in the label image.
colormap: numpy.ndarray, (M, 3), numpy.uint8
Label id to color.
By default, :func:`~imgviz.label_colormap` is used.
loc: string
Location of legend (default: 'centroid').
'lt' and 'rb' are supported.
font_path: str
Font path.
Returns
-------
res: numpy.ndarray, (H, W, 3), numpy.uint8
Visualized image.
"""
if colormap is None:
colormap = label_colormap()
res = colormap[label]
random_state = np.random.RandomState(seed=1234)
mask_unlabeled = label < 0
res[mask_unlabeled] = random_state.rand(*(mask_unlabeled.sum(), 3)) * 255
if img is not None:
if img.ndim == 2:
img = color_module.gray2rgb(img)
res = (1 - alpha) * img.astype(float) + alpha * res.astype(float)
res = np.clip(res.round(), 0, 255).astype(np.uint8)
if label_names is None:
return res
unique_labels = np.unique(label)
unique_labels = unique_labels[unique_labels != -1]
unique_labels = [l for l in unique_labels if label_names[l] is not None]
if len(unique_labels) == 0:
return res
if loc == "centroid":
for label_i in unique_labels:
mask = label == label_i
if 1.0 * mask.sum() / mask.size < thresh_suppress:
continue
y, x = np.array(_center_of_mass(mask), dtype=int)
if label[y, x] != label_i:
Y, X = np.where(mask)
point_index = np.random.randint(0, len(Y))
y, x = Y[point_index], X[point_index]
text = label_names[label_i]
height, width = draw_module.text_size(
text, size=font_size, font_path=font_path
)
color = color_module.get_fg_color(res[y, x])
res = draw_module.text(
res,
yx=(y - height // 2, x - width // 2),
text=text,
color=color,
size=font_size,
font_path=font_path,
)
elif loc in ["rb", "lt"]:
text_sizes = np.array(
[
draw_module.text_size(
label_names[l], font_size, font_path=font_path
)
for l in unique_labels
]
)
text_height, text_width = text_sizes.max(axis=0)
legend_height = text_height * len(unique_labels) + 5
legend_width = text_width + 20 + (text_height - 10)
height, width = label.shape[:2]
legend = np.zeros((height, width, 3), dtype=np.uint8)
if loc == "rb":
aabb2 = np.array([height - 5, width - 5], dtype=float)
aabb1 = aabb2 - (legend_height, legend_width)
elif loc == "lt":
aabb1 = np.array([5, 5], dtype=float)
aabb2 = aabb1 + (legend_height, legend_width)
else:
raise ValueError("unexpected loc: {}".format(loc))
legend = draw_module.rectangle(
legend, aabb1, aabb2, fill=(255, 255, 255)
)
alpha = 0.5
y1, x1 = aabb1.round().astype(int)
y2, x2 = aabb2.round().astype(int)
res[y1:y2, x1:x2] = (
alpha * res[y1:y2, x1:x2] + alpha * legend[y1:y2, x1:x2]
)
for i, l in enumerate(unique_labels):
box_aabb1 = aabb1 + (i * text_height + 5, 5)
box_aabb2 = box_aabb1 + (text_height - 10, text_height - 10)
res = draw_module.rectangle(
res, aabb1=box_aabb1, aabb2=box_aabb2, fill=colormap[l]
)
res = draw_module.text(
res,
yx=aabb1 + (i * text_height, 10 + (text_height - 10)),
text=label_names[l],
size=font_size,
font_path=font_path,
)
else:
raise ValueError("unsupported loc: {}".format(loc))
return res
def _center_of_mass(mask):
assert mask.ndim == 2 and mask.dtype == bool
mask = 1.0 * mask / mask.sum()
dx = np.sum(mask, 0)
dy = np.sum(mask, 1)
cx = np.sum(dx * np.arange(mask.shape[1]))
cy = np.sum(dy * np.arange(mask.shape[0]))
return cy, cx
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