def subsample(self, vertices):
xiyi = np.vstack((self.traj_lon[0, :], self.traj_lat[0, :])).T
mpath = MplPath(vertices)
outside_area = ~mpath.contains_points(xiyi)
self.init_x, self.init_y, self.init_z, self.init_s, \
self.traj_lon, self.traj_lat, self.traj_depth, self.traj_time, self.final_z = \
[x.compress(outside_area,axis=-1) for x in (self.init_x, self.init_y, self.init_z, self.init_s,
self.traj_lon, self.traj_lat, self.traj_depth, self.traj_time, self.final_z)]
def draw_bezier_curve(self, verts):
self.cr.init(transform=None)
self.cr.update_patch(self.pen, None)
codes = [ MplPath.MOVETO,
MplPath.CURVE4, MplPath.CURVE4, MplPath.CURVE4,
]
path = MplPath(verts, codes)
p = patches.PathPatch(path, **self.cr.kwdargs)
self.cr.axes.add_patch(p)
def get_mask(self, current_image):
ny, nx = np.shape(current_image)
poly_verts = ([(self.x[0], self.y[0])] +
list(zip(reversed(self.x), reversed(self.y))))
# Create vertex coordinates for each grid cell...
# (<0,0> is at the top left of the grid in this system)
x, y = np.meshgrid(np.arange(nx), np.arange(ny))
x, y = x.flatten(), y.flatten()
points = np.vstack((x, y)).T
roi_path = MplPath(poly_verts)
grid = roi_path.contains_points(points).reshape((ny, nx))
return grid
def getMask(self, roiLineCoords):
ny, nx = np.shape(self.pixelArray)
#print("roiLineCoords ={}".format(roiLineCoords))
# Create vertex coordinates for each grid cell...
# (<0,0> is at the top left of the grid in this system)
x, y = np.meshgrid(np.arange(nx), np.arange(ny))
x, y = x.flatten(), y.flatten()
points = np.vstack(
(x, y)).T #points = every [x,y] pair within the original image
#print("roiLineCoords={}".format(roiLineCoords))
roiPath = MplPath(roiLineCoords)
#print("roiPath={}".format(roiPath))
self.mask = roiPath.contains_points(points).reshape((ny, nx))
def draw_ellipse_bezier(self, verts):
self.cr.init(transform=None)
self.cr.update_patch(self.pen, self.brush)
# draw 4 bezier curves to make the ellipse
codes = [ MplPath.MOVETO,
MplPath.CURVE4, MplPath.CURVE4, MplPath.CURVE4,
MplPath.CURVE4, MplPath.CURVE4, MplPath.CURVE4,
MplPath.CURVE4, MplPath.CURVE4, MplPath.CURVE4,
MplPath.CURVE4, MplPath.CURVE4, MplPath.CURVE4,
]
path = MplPath(verts, codes)
p = patches.PathPatch(path, **self.cr.kwdargs)
self.cr.axes.add_patch(p)
def to_array(roi_value, framesize: tuple = DEFAULT_FRAME_SIZE) -> np.ndarray:
"""Convert ImageJ roi to numpy array mask.
Args:
roi_value (ImageJ ROI): ImageJ Roi
framesize (tuple, optional): Defaults to DEFAULT_FRAME_SIZE. Frame size to use (y,x) should be type int.
Returns:
numpy.ndarray: [description]
"""
x, y = np.meshgrid(np.arange(framesize[0]), np.arange(framesize[1]))
x, y = x.flatten(), y.flatten()
points = np.vstack((x, y)).T
pth = MplPath(list(zip(roi_value['x'], roi_value['y'])))
grid = pth.contains_points(points)
mask = grid.reshape(framesize[1], framesize[0])
return mask
def get_mask(self, current_image):
print("get_mask")
ny, nx = np.shape(current_image)
print("ny ={} nx={}".format(ny, nx))
poly_verts = ([(self.x[0], self.y[0])]
+ list(zip(reversed(self.x), reversed(self.y))))
print("poly_verts ={}".format(poly_verts))
# Create vertex coordinates for each grid cell...
# (<0,0> is at the top left of the grid in this system)
x, y = np.meshgrid(np.arange(nx), np.arange(ny))
x, y = x.flatten(), y.flatten()
points = np.vstack((x, y)).T
#points = every [x,y] pair within the original image
print("poly_verts={}".format(poly_verts))
roi_path = MplPath(poly_verts)
print("roi_path={}".format(roi_path))
grid = roi_path.contains_points(points).reshape((ny, nx))
print("grid ={}".format(grid))
return grid
def saveMask(self):
ny, nx = np.shape(self.img)
poly_verts = ([(self.x[0], self.y[0])] +
list(zip(reversed(self.x), reversed(self.y))))
# Create vertex coordinates for each grid cell...
# (<0,0> is at the top left of the grid in this system)
x, y = np.meshgrid(np.arange(nx), np.arange(ny))
x, y = x.flatten(), y.flatten()
points = np.vstack((x, y)).T
roi_path = MplPath(poly_verts)
mask = 1 * roi_path.contains_points(points).reshape((ny, nx))
folder, filename = os.path.split(self.file_in)
filename, extension = os.path.splitext(filename)
if self.fn == None:
self.fn = filename + '_manual' + extension
imsave(os.path.join(folder, self.subfolder, self.fn),
mask.astype(np.uint16))
self.close()
def grid_from_roi(im, vertices, single=False):
"""Return drawn ROI as grid.
Args:
im (Series): Series object as template
vertices: The polygon vertices, as a dictionary of tags of (x,y)
single (bool): Draw ROI in single slice per tag
Returns:
Numpy ndarray with shape (nz,ny,nx) from original image, dtype ubyte.
Voxels inside ROI is 1, 0 outside.
"""
def _roi_in_any_slice(tag):
"""Check whether there is a ROI in any slice"""
t, i = tag
for idx in range(im.slices):
# if (t, idx) in vertices and vertices[t, idx] is None:
# print('Check {} None'.format((t, idx)))
# elif (t, idx) in vertices:
# print('Check {} {}'.format((t, idx), len(vertices[t, idx])))
# else:
# print('Check {} not found'.format((t, idx)))
if (t, idx) in vertices and vertices[t, idx] is not None:
return True
return False
keys = list(vertices.keys())[0]
# print('grid_from_roi: keys: {}'.format(keys))
# print('grid_from_roi: vertices: {}'.format(vertices))
follow = issubclass(type(keys), tuple)
nt, nz, ny, nx = len(im.tags[0]), im.slices, im.rows, im.columns
if follow and not single:
grid = np.zeros_like(im, dtype=np.ubyte)
skipped = []
copied = []
for idx in range(nz):
last_used_tag = None
for t in range(nt):
tag = t, idx
if tag not in vertices or vertices[tag] is None:
if last_used_tag is None:
# Most probably a slice with no ROIs
skipped.append(tag)
continue
elif _roi_in_any_slice(tag):
# print('Found in some slice for', tag)
skipped.append(tag)
continue
# Propagate last drawn ROI to unfilled tags
vertices[tag] = copy.copy(vertices[last_used_tag])
copied.append((tag, last_used_tag))
else:
last_used_tag = tag
path = MplPath(vertices[tag])
x, y = np.meshgrid(np.arange(nx), np.arange(ny))
x, y = x.flatten(), y.flatten()
points = np.vstack((x, y)).T
grid[t, idx] = path.contains_points(points).reshape((ny, nx))
elif follow and single:
grid = np.zeros_like(im, dtype=np.ubyte)
skipped = []
copied = []
last_used_tag = None
for t in range(nt):
for idx in range(nz):
tag = t, idx
if tag not in vertices or vertices[tag] is None:
if last_used_tag is None:
# Most probably a slice with no ROIs
skipped.append(tag)
continue
elif last_used_tag[1] != idx:
continue
elif _roi_in_any_slice(tag):
# print('Found in some slice for', tag)
skipped.append(tag)
continue
# Propagate last drawn ROI to unfilled tags
vertices[tag] = copy.copy(vertices[last_used_tag])
copied.append((tag, last_used_tag))
else:
last_used_tag = tag
path = MplPath(vertices[tag])
x, y = np.meshgrid(np.arange(nx), np.arange(ny))
x, y = x.flatten(), y.flatten()
points = np.vstack((x, y)).T
grid[t, idx] = path.contains_points(points).reshape((ny, nx))
# if len(skipped) > 0:
# print('Skipped: {}'.format(skipped))
# if len(copied) > 0:
# print('Copied: {}'.format(copied))
else:
grid = np.zeros((nz, ny, nx), dtype=np.ubyte)
for idx in range(nz):
if idx not in vertices or vertices[idx] is None:
continue
path = MplPath(vertices[idx])
x, y = np.meshgrid(np.arange(nx), np.arange(ny))
x, y = x.flatten(), y.flatten()
points = np.vstack((x, y)).T
grid[idx] = path.contains_points(points).reshape((ny, nx))
return Series(grid, input_order=im.input_order, template=im, geometry=im)