def index():
# pkl-list get
pkl_list = sorted(
[pkl for pkl in os.listdir('model') if pkl.endswith('.pkl')])
pkl_select = [
'Depth {:s} Branch {:s}'.format(
a.replace('.pkl', '').split('-')[2],
a.replace('.pkl', '').split('-')[3]) for a in pkl_list
]
return render_template('search.html',
bg_path=BG_PATH,
logo_path=LOGO_PATH,
pkl_list=pkl_select,
tar_path=utils.random_image('static/data'))
import numpy as np
import pytest
from stardist import star_dist3D, Rays_GoldenSpiral, relabel_image_stardist3D
from utils import random_image, real_image3d, check_similar, circle_image
@pytest.mark.parametrize('img', (real_image3d()[1], random_image(
(33, 44, 55))))
@pytest.mark.parametrize('n_rays', (4, 16, 32))
@pytest.mark.parametrize('grid', ((1, 1, 1), (1, 2, 4)))
def test_types(img, n_rays, grid):
mode = "cpp"
rays = Rays_GoldenSpiral(n_rays)
gt = star_dist3D(img, rays=rays, grid=grid, mode=mode)
for dtype in (np.int8, np.int16, np.int32, np.uint8, np.uint16, np.uint32):
x = star_dist3D(img.astype(dtype), rays=rays, grid=grid, mode=mode)
print(
"test_stardist3D (mode {mode}) for shape {img.shape} and type {dtype}"
.format(mode=mode, img=img, dtype=dtype))
check_similar(gt, x)
@pytest.mark.gpu
@pytest.mark.parametrize('img', (real_image3d()[1], random_image(
(33, 44, 55))))
@pytest.mark.parametrize('n_rays', (4, 16, 32))
@pytest.mark.parametrize('grid', ((1, 1, 1), (1, 2, 4)))
def test_types_gpu(img, n_rays, grid):
mode = "opencl"
rays = Rays_GoldenSpiral(n_rays)
gt = star_dist3D(img, rays=rays, grid=grid, mode=mode)
import numpy as np
import pytest
from stardist import star_dist, edt_prob, non_maximum_suppression, dist_to_coord, polygons_to_label
from stardist.matching import matching
from utils import random_image, real_image2d, check_similar
@pytest.mark.parametrize('img', (real_image2d()[1], random_image((128, 123))))
def test_bbox_search(img):
prob = edt_prob(img)
dist = star_dist(img, n_rays=32, mode="cpp")
coord = dist_to_coord(dist)
nms_a = non_maximum_suppression(coord,
prob,
prob_thresh=0.4,
verbose=False,
max_bbox_search=False)
nms_b = non_maximum_suppression(coord,
prob,
prob_thresh=0.4,
verbose=False,
max_bbox_search=True)
check_similar(nms_a, nms_b)
@pytest.mark.parametrize('img', (real_image2d()[1], ))
def test_acc(img):
prob = edt_prob(img)
dist = star_dist(img, n_rays=32, mode="cpp")
coord = dist_to_coord(dist)
points = non_maximum_suppression(coord, prob, prob_thresh=0.4)
import numpy as np
import pytest
from stardist import star_dist3D, Rays_GoldenSpiral, relabel_image_stardist3D
from utils import random_image, real_image3d, check_similar, circle_image, Timer
from time import time
@pytest.mark.parametrize('img', (real_image3d()[1], random_image((33, 44, 55))))
@pytest.mark.parametrize('n_rays', (4, 16, 32))
@pytest.mark.parametrize('grid', ((1, 1, 1), (1, 2, 4)))
def test_types(img, n_rays, grid):
mode = "cpp"
rays = Rays_GoldenSpiral(n_rays)
gt = star_dist3D(img, rays=rays, grid=grid, mode=mode)
for dtype in (np.int8, np.int16, np.int32,
np.uint8, np.uint16, np.uint32):
x = star_dist3D(img.astype(dtype), rays=rays, grid=grid, mode=mode)
print("test_stardist3D (mode {mode}) for shape {img.shape} and type {dtype}".format(
mode=mode, img=img, dtype=dtype))
check_similar(gt, x)
@pytest.mark.gpu
@pytest.mark.parametrize('img', (real_image3d()[1], random_image((33, 44, 55))))
@pytest.mark.parametrize('n_rays', (4, 16, 32))
@pytest.mark.parametrize('grid', ((1, 1, 1), (1, 2, 4)))
def test_types_gpu(img, n_rays, grid):
mode = "opencl"
rays = Rays_GoldenSpiral(n_rays)
gt = star_dist3D(img, rays=rays, grid=grid, mode=mode)
for dtype in (np.int8, np.int16, np.int32,
np.uint8, np.uint16, np.uint32):