def batched_keypoints_to_segments(
img: np.ndarray,
keypoints: np.ndarray,
segmentation_algorithm: SegmentationAlgorithm,
) -> Union[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
n_keypoints = keypoints.shape[0]
MAP = segmentation_algorithm(img, keypoints)
MAP_colorized = imageutils.make_colors(n_keypoints + 1,
with_background=True,
background_id=0)[MAP]
heatmaps = imageutils.keypoints_to_heatmaps(img.shape[:2], keypoints,
segmentation_algorithm.var)
heatmaps *= heatmaps > 0.8
heatmaps_rgb = imageutils.colorize_heatmaps(
heatmaps[np.newaxis, ...], imageutils.make_colors(n_keypoints))
img_resized = cv2.resize(img, (256, 256), cv2.INTER_LINEAR)
img_resized = imageutils.convert_range(img_resized, [0, 255], [0, 1])
im_with_keypoints = imageutils.draw_keypoint_markers(
img_resized,
keypoints,
marker_list=[str(i)
for i in range(10)] + ["x", "o", "v", "<", ">", "*"],
font_scale=1,
thickness=4,
)
im_with_keypoints = cv2.resize(im_with_keypoints,
(img.shape[1], img.shape[1]),
cv2.INTER_LINEAR)
return MAP, MAP_colorized, heatmaps_rgb, im_with_keypoints
def test_segmentationFromKeypoints(self):
from supermariopy.crf import SegmentationFromKeypoints
from supermariopy import imageutils
from skimage import data
n_keypoints = 10
var = 0.05
keypoints = np.stack(
[np.linspace(-1, 1, n_keypoints),
np.linspace(-1, 1, n_keypoints)],
axis=1)
img = data.astronaut()
segmentation_algorithm = SegmentationFromKeypoints(var)
labels = segmentation_algorithm(img, keypoints)
labels_rgb = imageutils.make_colors(n_keypoints + 1)[labels]
heatmaps = imageutils.keypoints_to_heatmaps(img.shape[:2], keypoints,
var)
heatmaps_rgb = imageutils.colorize_heatmaps(
heatmaps[np.newaxis, ...], imageutils.make_colors(n_keypoints))
fig, axes = plt.subplots(1, 2, figsize=(8, 4))
axes[0].imshow(labels_rgb)
axes[0].set_axis_off()
axes[1].imshow(np.squeeze(heatmaps_rgb))
axes[1].set_axis_off()
return fig
def test_colorize_heatmaps(self):
from supermariopy.imageutils import (
keypoints_to_heatmaps,
make_colors,
colorize_heatmaps,
)
from matplotlib import pyplot as plt
keypoints = np.stack([np.linspace(-1, 1, 10),
np.linspace(-1, 1, 10)],
axis=1)
heatmaps = keypoints_to_heatmaps((512, 512), keypoints)
colors = make_colors(keypoints.shape[0])
img_marked = colorize_heatmaps(heatmaps[np.newaxis, ...], colors)
fig, ax = plt.subplots(1, 1, figsize=(6, 6))
ax.imshow(np.squeeze(img_marked))
return fig
def batched_keypoints_to_segments(img, keypoints, segmentation_algorithm):
n_keypoints = keypoints.shape[0]
MAP = segmentation_algorithm(img, keypoints)
MAP_colorized = imageutils.make_colors(n_keypoints + 1,
with_background=True,
background_id=0)[MAP]
heatmaps = imageutils.keypoints_to_heatmaps(img.shape[:2], keypoints,
segmentation_algorithm.var)
heatmaps *= heatmaps > 0.8
heatmaps_rgb = imageutils.colorize_heatmaps(
heatmaps[np.newaxis, ...], imageutils.make_colors(n_keypoints))
im_with_keypoints = imageutils.draw_keypoint_markers(
imageutils.convert_range(img, [0, 255], [0, 1]),
keypoints,
marker_list=[str(i)
for i in range(10)] + ["x", "o", "v", "<", ">", "*"],
font_scale=0.5,
)
return MAP, MAP_colorized, heatmaps_rgb, im_with_keypoints