def upload_annotations(cytomine, img, y, term=None, proba=1.):
points = np.transpose(y.nonzero())
points = [Point(x, y) for x, y in points]
if isinstance(img, Annotation):
img_inst = cytomine.get_image_instance(img.image)
crop_location = affine_transform(loads(img.location),
[0, -1, 1, 0, img_inst.height, 0])
offset, width, height = polygon_box(crop_location)
else:
offset = (0, 0)
img_inst = img
affine_matrix = [0, 1, -1, 0, offset[1], img_inst.height - offset[0]]
points = [affine_transform(pt, affine_matrix) for pt in points]
for point in points:
annotation = cytomine.add_annotation(point.wkt, img_inst.id)
if term is not None and annotation is not None:
cytomine.add_annotation_term(
annotation.id,
term,
term,
proba,
annotation_term_model=AlgoAnnotationTerm)
def test_affine_3d(self):
g2 = load_wkt('LINESTRING(2.4 4.1, 2.4 3, 3 3)')
g3 = load_wkt('LINESTRING(2.4 4.1 100.2, 2.4 3 132.8, 3 3 128.6)')
# custom scale and translate
matrix2d = (2, 0, 0, 2.5, -5, 4.1)
matrix3d = (2, 0, 0, 0, 2.5, 0, 0, 0, 0.3048, -5, 4.1, 100)
# Combinations of 2D and 3D geometries and matrices
a22 = affinity.affine_transform(g2, matrix2d)
a23 = affinity.affine_transform(g2, matrix3d)
a32 = affinity.affine_transform(g3, matrix2d)
a33 = affinity.affine_transform(g3, matrix3d)
# Check dimensions
self.assertFalse(a22.has_z)
self.assertFalse(a23.has_z)
self.assertTrue(a32.has_z)
self.assertTrue(a33.has_z)
# 2D equality checks
expected2d = load_wkt('LINESTRING(-0.2 14.35, -0.2 11.6, 1 11.6)')
expected3d = load_wkt('LINESTRING(-0.2 14.35 130.54096, '
'-0.2 11.6 140.47744, 1 11.6 139.19728)')
expected32 = load_wkt('LINESTRING(-0.2 14.35 100.2, '
'-0.2 11.6 132.8, 1 11.6 128.6)')
self.assertTrue(a22.almost_equals(expected2d))
self.assertTrue(a23.almost_equals(expected2d))
# Do explicit 3D check of coordinate values
for a, e in zip(a32.coords, expected32.coords):
for ap, ep in zip(a, e):
self.assertAlmostEqual(ap, ep)
for a, e in zip(a33.coords, expected3d.coords):
for ap, ep in zip(a, e):
self.assertAlmostEqual(ap, ep)
def improved_buffer(input_geometry,
buffer_width,
separation_width,
simplify_length,
show_progress=False):
buffer_width *= GEO.m_to_lat
separation_width *= GEO.m_to_lat
simplify_length *= GEO.m_to_lat
if show_progress: UI.progress_bar(1, 0)
input_geometry = affinity.affine_transform(input_geometry,
[scalx, 0, 0, 1, 0, 0])
output_geometry = input_geometry.buffer(buffer_width + separation_width,
join_style=2,
mitre_limit=1.5,
resolution=1)
if show_progress: UI.progress_bar(1, 40)
if UI.red_flag: return geometry.Polygon()
output_geometry = output_geometry.buffer(-1 * separation_width,
join_style=2,
mitre_limit=1.5,
resolution=1)
if show_progress: UI.progress_bar(1, 80)
if UI.red_flag: return geometry.Polygon()
if simplify_length:
output_geometry = output_geometry.simplify(simplify_length)
if show_progress: UI.progress_bar(1, 100)
if UI.red_flag: return geometry.Polygon()
output_geometry = affinity.affine_transform(output_geometry,
[1 / scalx, 0, 0, 1, 0, 0])
return output_geometry
def run(self, ips, imgs, para = None):
shp = convert.roi2shape(ips.roi)
m = ips.img.mat
m = [m[0,1], 0, 0, m[1,2], m[0,0], m[1,0]]
shp = affine_transform(shp, m)
shp = affine_transform(shp, [0,1,1,0,0,0])
gdf = gpd.GeoDataFrame([[shp]], columns=['geometry'], crs=ips.img.crs)
gdf.to_file(para['path'])
def get_dataset(cytomine,
working_path,
id_project,
id_term,
id_roi_term,
id_user=None,
reviewed_only=False,
id_roi_user=None,
reviewed_only_roi=False,
force_download=False):
# Download ROI annotations
crops_annotations = cytomine.get_annotations(
id_project=id_project,
id_term=id_roi_term,
id_user=id_roi_user,
reviewed_only=reviewed_only_roi,
showWKT=True,
showMeta=True)
# Download ROI crops
crops = cytomine.dump_annotations(
annotations=crops_annotations,
dest_path=os.path.join(working_path, CROPS_PATH, str(id_project)),
override=force_download,
desired_zoom=0,
get_image_url_func=Annotation.get_annotation_alpha_crop_url).data()
dataset = list()
for crop in crops:
gt_annots = cytomine.get_annotations(id_project=id_project,
id_image=crop.image,
id_bbox=crop.id,
id_term=id_term,
id_user=id_user,
reviewed_only=reviewed_only,
showWKT=True).data()
img_inst = cytomine.get_image_instance(crop.image)
crop_location = affine_transform(loads(crop.location),
[0, -1, 1, 0, img_inst.height, 0])
offset, width, height = polygon_box(crop_location)
affine_matrix = [0, -1, 1, 0, img_inst.height - offset[0], -offset[1]]
gt_locations = [
affine_transform(loads(gt.location), affine_matrix)
for gt in gt_annots
]
groundtruth = mk_groundtruth_image(gt_locations, width, height)
image_filename = crop.filename
groundtruth_filename = save_groundtruth_image(
groundtruth,
os.path.join(working_path, GROUNDTRUTHS_PATH, str(crop.project)),
"{}_{}.png".format(crop.image, crop.id))
dataset.append((image_filename, groundtruth_filename))
return zip(*dataset)
def transform(shape, trans):
if isinstance(shape, Collection):
return Collection([transform(s, trans) for s in shape.geoms])
elif isinstance(shape, Polygon):
# shapely should not be used if the students are implementing this
return Polygon(affine_transform(shape.poly, trans).exterior.coord)
else:
# shapely should not be used if the students are implementing this
return Point(affine_transform(shape.point, trans).coords[0])
def transform(shape, trans):
if isinstance(shape, Collection):
return Collection([transform(s, trans) for s in shape.geoms])
elif isinstance(shape, Polygon):
# shapely should not be used if the students are implementing this
return Polygon(affine_transform(shape.poly, trans).exterior.coord)
else:
# shapely should not be used if the students are implementing this
return Point(affine_transform(shape.point, trans).coords[0])
def connect_IDL(df):
logger = logging.getLogger('shippingroutes_connect_IDL')
# do an affinity transform, then get nearest points, then reverse the affine transform, then V_inv to get the distance
logger.info('intersecting boxes and taking affine transform')
pos_box = geometry.box(178, -85, 180, 85)
neg_box = geometry.box(-180, -85, -178, 85)
df['pos_intersects'] = df['geometry'].apply(
lambda el: wkt.loads(el).intersects(pos_box))
df['neg_intersects'] = df['geometry'].apply(
lambda el: wkt.loads(el).intersects(neg_box))
df_pos = df[df['pos_intersects']]
df_neg = df[df['neg_intersects']]
DT = [1, 0, 0, 1, -360, 0]
df_pos['geometry'] = df_pos['geometry'].apply(
lambda el: affinity.affine_transform(wkt.loads(el), DT))
df_neg['geometry'] = df_neg['geometry'].apply(lambda el: wkt.loads(el))
DT = [1, 0, 0, 1, 360, 0]
logger.info('Getting all nearest Points')
records = []
for idx_pos, row_pos in tqdm(df_pos.iterrows()):
for idx_neg, row_neg in df_neg.iterrows():
pt_pos, pt_neg = ops.nearest_points(row_pos['geometry'],
row_neg['geometry'])
records.append({
'pt_pos': affinity.affine_transform(pt_pos, DT),
'pt_neg': pt_neg,
'id_pos': row_pos['unique_id'],
'id_neg': row_neg['unique_id']
})
df_intersection = pd.DataFrame.from_records(records)
logger.info('Getting distance between points')
df_intersection['DISTANCE'] = df_intersection.progress_apply(
lambda row: V_inv((row['pt_pos'].y, row['pt_pos'].x),
(row['pt_neg'].y, row['pt_neg'].x))[0] * 1000,
axis=1) #m
df_intersection = df_intersection.rename(columns={
'id_pos': 'START',
'id_neg': 'END'
})
df_intersection = df_intersection[df_intersection['DISTANCE'] < 10000]
df_intersection['PT_START'] = df_intersection['pt_pos'].apply(
lambda el: el.wkt)
df_intersection['PT_END'] = df_intersection['pt_neg'].apply(
lambda el: el.wkt)
return df_intersection[['START', 'END', 'PT_START', 'PT_END', 'DISTANCE']]
def test_geom(g2, g3=None):
self.assertFalse(g2.has_z)
a2 = affinity.affine_transform(g2, matrix2d)
self.assertFalse(a2.has_z)
self.assertTrue(g2.equals(a2))
if g3 is not None:
self.assertTrue(g3.has_z)
a3 = affinity.affine_transform(g3, matrix3d)
self.assertTrue(a3.has_z)
self.assertTrue(g3.equals(a3))
return
def test_geom(g2, g3=None):
self.assertFalse(g2.has_z)
a2 = affinity.affine_transform(g2, matrix2d)
self.assertFalse(a2.has_z)
self.assertTrue(g2.equals(a2))
if g3 is not None:
self.assertTrue(g3.has_z)
a3 = affinity.affine_transform(g3, matrix3d)
self.assertTrue(a3.has_z)
self.assertTrue(g3.equals(a3))
return
def _make_polygon(elt_type,
instructions,
parent=None,
interpolate_curve=50,
return_points=False):
container = None
shell = [] # outer points defining the polygon's outer shell
holes = [] # inner points defining holes
idx_start = 0
if elt_type == "path": # build polygons from custom paths
path_data = parse_path(instructions["path"])
subpaths = [subpath for subpath in _get_closed_subpaths(path_data)]
points = [_get_points(subpath) for subpath in subpaths]
# get the container
idx_container = _get_outer_shell(points)
shell = np.array(points[idx_container])
# get the holes and make the shape
holes = [pp for i, pp in enumerate(points) if i != idx_container]
container = Polygon(shell, holes=holes)
elif elt_type == "ellipse": # build ellipses
circle = Point((instructions["cx"], instructions["cy"])).buffer(1)
rx, ry = instructions["rx"], instructions["ry"]
container = scale(circle, rx, ry)
elif elt_type == "circle": # build circles
r = instructions["r"]
container = Point((instructions["cx"], instructions["cy"])).buffer(r)
elif elt_type == "rect": # build rectangles
x, y = instructions["x"], instructions["y"]
w, h = instructions["width"], instructions["height"]
shell = np.array([(x, y), (x + w, y), (x + w, y + h), (x, y + h)])
container = Polygon(shell)
else:
raise RuntimeError("Unexpected element type: '{}'.".format(elt_type))
# transforms
nn, dd = instructions["transf"][::-1], instructions["transfdata"][::-1]
for name, data in zip(nn, dd):
if name == "matrix":
container = affine_transform(container, data)
elif name == "translate":
container = translate(container, *data)
# y axis is inverted in SVG, so make mirror transform
container = affine_transform(container, (1, 0, 0, -1, 0, 0))
shell = np.array(container.exterior.coords)
if return_points:
return container, shell
return container
def test_affine_2d(self):
g = load_wkt('LINESTRING(2.4 4.1, 2.4 3, 3 3)')
# custom scale and translate
expected2d = load_wkt('LINESTRING(-0.2 14.35, -0.2 11.6, 1 11.6)')
matrix2d = (2, 0, 0, 2.5, -5, 4.1)
a2 = affinity.affine_transform(g, matrix2d)
self.assertTrue(a2.almost_equals(expected2d))
self.assertFalse(a2.has_z)
# Make sure a 3D matrix does not make a 3D shape from a 2D input
matrix3d = (2, 0, 0, 0, 2.5, 0, 0, 0, 10, -5, 4.1, 100)
a3 = affinity.affine_transform(g, matrix3d)
self.assertTrue(a3.almost_equals(expected2d))
self.assertFalse(a3.has_z)
def normalize(line, end_idx):
traj = LineString(line)
start = line[0] #shape [2,]
#Translation normalization: start with (0.0, 0.0)
#[a, b, c, d, x, y] is the planner transformation matrix[a, b, x; c, d, y; 0, 0, 1]
g = [1, 0, 0, 1, -start[0], -start[1]]
traj_trans = affine_transform(traj, g)
#Rotation normalization:
end = traj_trans.coords[end_idx]
if end[0] == 0 and end[1] == 0:
angle = 0.0
elif end[0] == 0:
angle = 90.0 if end[1] < 0 else -90.0
elif end[1] == 0:
angle = 0.0 if end[0] > 0 else 180.0
else:
angle = math.degrees(math.atan(end[1] / end[0]))
if (end[0] > 0 and end[1] > 0) or (end[0] > 0 and end[1] < 0):
angle = -angle
else:
angle = 180.0 - angle
#Rotate normalization: end with y=0
traj_rotate = rotate(traj_trans, angle, origin=(0, 0)).coords[:]
#Transform to numpy
traj_norm = np.array(traj_rotate)
return traj_norm
def denormalize_xy(self, xy_locations, translation=None, rotation=None):
"""Reverse the Translate and rotate operations on the input data
Args:
xy_locations (numpy array): XY positions for the trajectory
Returns:
xy_locations_normalized (numpy array): denormalized XY positions
"""
# Apply rotation
num = xy_locations.shape[0]
if xy_locations.shape[0] > 1:
trajectory = LineString(xy_locations)
else:
trajectory = LineString(np.concatenate(([[0.0, 0.0]], xy_locations), axis=0))
if rotation is not None:
trajectory = rotate(trajectory, rotation, origin=(0, 0))
if translation is not None:
mat = [1, 0, 0, 1, translation[0], translation[1]]
trajectory = affine_transform(trajectory, mat)
output = np.array(trajectory.coords, dtype=np.float32)
if num <= 1:
output = output[1:]
return output
def minimum_rotated_rectangle(self):
"""Returns the general minimum bounding rectangle of
the geometry. Can possibly be rotated. If the convex hull
of the object is a degenerate (line or point) this same degenerate
is returned.
"""
# first compute the convex hull
hull = self.convex_hull
try:
coords = hull.exterior.coords
except AttributeError: # may be a Point or a LineString
return hull
# generate the edge vectors between the convex hull's coords
edges = ((pt2[0] - pt1[0], pt2[1] - pt1[1])
for pt1, pt2 in zip(coords, islice(coords, 1, None)))
def _transformed_rects():
for dx, dy in edges:
# compute the normalized direction vector of the edge vector
length = math.sqrt(dx**2 + dy**2)
ux, uy = dx / length, dy / length
# compute the normalized perpendicular vector
vx, vy = -uy, ux
# transform hull from the original coordinate system to the coordinate system
# defined by the edge and compute the axes-parallel bounding rectangle
transf_rect = affine_transform(hull,
(ux, uy, vx, vy, 0, 0)).envelope
# yield the transformed rectangle and a matrix to transform it back
# to the original coordinate system
yield (transf_rect, (ux, vx, uy, vy, 0, 0))
# check for the minimum area rectangle and return it
transf_rect, inv_matrix = min(_transformed_rects(),
key=lambda r: r[0].area)
return affine_transform(transf_rect, inv_matrix)
def calc_distance_and_angle(p: LocationLocal, ref_p: LocationLocal, rel_angle=0):
# if type(p) is LocationGlobal or LocationGlobalRelative:
# p = latlon_to_xy()
p = Point(p.east, p.north)
ref_p = Point(ref_p.east, ref_p.north)
# transform to local coordinates
p_local = affine_transform(p, [1,0,0,1, -ref_p.x, -ref_p.y])
# alpha = -90 # plus 90 so north is a heading of 0 degrees.With shapely positive rotations are counter clockwise
# p_local = rotate(p_local, alpha, origin=(0,0)) # take into account the relative angle of the plane
# # convert to polar coordinates
# distance = math.sqrt(pow(p.x - ref_p.x, 2) + pow(p.y - ref_p.y, 2))
# angle = math.atan((p.x - ref_p.x) / (p.y - ref_p.y))
(distance, angle) = cmath.polar(complex(p_local.x, p_local.y)) # angle is in radians
# convert to degrees and change axis
# +90 to set north to heading 0
angle = 90 - math.degrees(angle) - rel_angle
# only positive angles
if angle < 0:
angle+=360
# only angles under 360
if angle > 360:
angle-=360
return (distance, angle)
def mapSuperPixels(segments=None,
GT=None,
proj={'init': 'epsg:32618'},
verbose=True):
start = time.time()
if verbose:
print('--- Mapping superpixels to lat/lng coordinates ---')
seg_properties = regionprops(segments)
polygons = [
gpd.GeoSeries(Polygon(sp.coords)).convex_hull
for sp in seg_properties if (sp.area >= 12)
]
polygons = [
affine_transform(p[0], GT) for p in polygons
if p[0].geom_type == 'Polygon'
]
if len(polygons) == 1:
if verbose:
print('--- Done - execution time: {} seconds'.format(
time.time() - start))
return gpd.GeoDataFrame({'geometry': polygons},
geometry='geometry',
crs=proj,
index=[0])
else:
if verbose:
print('--- Done - execution time: {} seconds'.format(
time.time() - start))
return gpd.GeoDataFrame({'geometry': polygons},
geometry='geometry',
crs=proj)
def minimum_rotated_rectangle(self):
"""Returns the general minimum bounding rectangle of
the geometry. Can possibly be rotated. If the convex hull
of the object is a degenerate (line or point) this same degenerate
is returned.
"""
# first compute the convex hull
hull = self.convex_hull
try:
coords = hull.exterior.coords
except AttributeError: # may be a Point or a LineString
return hull
# generate the edge vectors between the convex hull's coords
edges = ((pt2[0]-pt1[0], pt2[1]-pt1[1]) for pt1, pt2 in zip(coords, islice(coords, 1, None)))
def _transformed_rects():
for dx, dy in edges:
# compute the normalized direction vector of the edge vector
length = math.sqrt(dx**2 + dy**2)
ux, uy = dx/length, dy/length
# compute the normalized perpendicular vector
vx, vy = -uy, ux
# transform hull from the original coordinate system to the coordinate system
# defined by the edge and compute the axes-parallel bounding rectangle
transf_rect = affine_transform(hull, (ux,uy,vx,vy,0,0)).envelope
# yield the transformed rectangle and a matrix to transform it back
# to the original coordinate system
yield (transf_rect, (ux,vx,uy,vy,0,0))
# check for the minimum area rectangle and return it
transf_rect, inv_matrix = min(_transformed_rects(), key=lambda r : r[0].area)
return affine_transform(transf_rect, inv_matrix)
def run(self, ips, imgs, para = None):
gdf = gpd.read_file(para['path']).to_crs(ips.img.crs)
m = ips.img.mat
m = [1/m[0,1], 0, 0, 1/m[1,2], -m[0,0]/m[0,1], -m[1,0]/m[1,2]]
shp = affine_transform(gdf['geometry'][0], m)
ips.roi = convert.shape2roi(shp)
if 'back' in ips.data:ips.roi.fill(ips.data['back'], (0,0,80))
def shp2raster(shape, scale, margin=0.05, style='lab', bounds=None):
shapes = shape['shape'].values
kmargin = margin/(1-2*margin)
geoms = list(shape['shape'].values)
bounds = bounds or GeometryCollection(geoms).bounds
l,t,r,b = bounds
w,h = r-l, b-t
if isinstance(scale, tuple):
W, H = np.array(scale) * (1-margin*2)
scale = max(w/W, h/H)
offsetx, offsety = l-w*kmargin, b+h*kmargin
shp = np.array((h,w))*(1+(kmargin*2))/scale
rst = np.zeros(shp.astype(np.int), dtype=np.int16)
m = [1/scale, 0, 0, -1/scale, -offsetx/scale, offsety/scale]
img = Image.fromarray(rst)
draw = ImageDraw.Draw(img)
for i in range(len(shapes)):
gs = affine_transform(shapes[i], m)
for g in gs:
pts = np.array(g.exterior.xy).T.astype(np.int).ravel()
if style=='lab': draw.polygon(list(pts), i+1)
else: draw.line(list(pts), 255, style)
#pgs = [np.array(g.exterior.xy).T.astype(np.int) for g in gs]
#if style=='lab':cv2.fillPoly(rst, pgs, i+1)
#else: cv2.drawContours(rst, pgs, -1, 255, style)
rst = np.array(img)
m = np.array([offsetx, scale, 0, offsety, 0, -scale]).reshape((2,3))
return Raster([rst], shape.prj, m)
def _recalc(self):
cache = _EdgeCorrect._recalc(self)
if cache is not None:
halfS = cache[2]
m = list(halfS.flatten()) + [0, 0]
geo = _saffinity.affine_transform(self._geo, m)
self._cache = cache + (geo, )
def transform_csg(layerdef_from, layerdef_to, inshift, outshift, step,
geom_from, geoms_to, csg_laminate, scale_x, scale_y):
from popupcad.filetypes.laminate import Laminate
import shapely.affinity as aff
from popupcad.algorithms.points import calctransformfrom2lines
lsout = Laminate(layerdef_to)
for layer_from, layer_to in zip(layerdef_from.layers[::step][inshift:],
layerdef_to.layers[outshift:]):
newgeoms = []
for geom in geoms_to:
for designgeom in csg_laminate.layer_sequence[layer_from].geoms:
try:
from_line = geom_from.exteriorpoints(
scaling=popupcad.csg_processing_scaling)
to_line = geom.exteriorpoints(
scaling=popupcad.csg_processing_scaling)
transform = calctransformfrom2lines(from_line,
to_line,
scale_x=scale_x,
scale_y=scale_y)
transformed_geom = aff.affine_transform(
designgeom, transform)
newgeoms.append(transformed_geom)
except IndexError:
pass
result1 = popupcad.algorithms.csg_shapely.unary_union_safe(newgeoms)
results2 = popupcad.algorithms.csg_shapely.condition_shapely_entities(
result1)
lsout.replacelayergeoms(layer_to, results2)
return lsout
def draw_pred_on_slide(slide_path,
preds,
value_fn,
color_fn,
opacity=127,
size=2048,
base_zl=2):
level = determine_tissue_extract_level(slide_path,
desired_processing_size=size)
slide = pyvips.Image.new_from_file(slide_path, page=level)
black = (0, 0, 0, 0)
mask = Image.new('RGBA', (slide.width, slide.height), black)
draw = ImageDraw.Draw(mask)
zoom_ratio = 2**(base_zl - level)
t_matrix = [zoom_ratio, 0, 0, zoom_ratio, 0, 0]
for rect, probas in preds:
color = color_fn(value_fn(probas))
with_opacity = color + (opacity, )
draw.rectangle(affine_transform(rect, t_matrix).bounds,
fill=with_opacity,
outline=black)
np_image = np.ndarray(buffer=slide.write_to_memory(),
dtype=np.uint8,
shape=[slide.height, slide.width, slide.bands])
pil_slide = Image.fromarray(np_image).convert("RGBA")
img = Image.alpha_composite(pil_slide, mask)
return pil_slide, img.convert("RGB")
def normalized_to_map_coordinates(coords: np.ndarray,
translation: List[List[float]],
rotation: List[float]) -> np.ndarray:
"""Denormalize trajectory to bring it back to map frame.
Args:
coords (numpy array): Array of shape (num_tracks x seq_len x 2) containing normalized coordinates
translation (list): Translation matrix used in normalizing trajectories
rotation (list): Rotation angle used in normalizing trajectories
Returns:
_ (numpy array: Array of shape (num_tracks x seq_len x 2) containing coordinates in map frame
"""
abs_coords = []
for i in range(coords.shape[0]):
ls = LineString(coords[i])
# Rotate
ls_rotate = rotate(ls, -rotation[i], origin=(0, 0))
# Translate
M_inv = [1, 0, 0, 1, -translation[i][4], -translation[i][5]]
ls_offset = affine_transform(ls_rotate, M_inv).coords[:]
abs_coords.append(ls_offset)
return np.array(abs_coords)
def random_point_in_polygon(transforms, areas):
transform = random.choices(transforms, weights=areas)
x, y = [random.random() for _ in range(2)]
if x + y > 1:
p = Point(1 - x, 1 - y)
else:
p = Point(x, y)
return affine_transform(p, transform[0])
def _to_shape(annot: ParsedAnnotation,
is_grayscale: bool = True) -> Tuple[BaseGeometry, int]:
geometry = affine_transform(annot.geometry, affine)
if is_grayscale:
value = annot.fill_color.as_rgb_tuple()[0]
else:
value = annot.fill_color.as_int()
return geometry, value
def rotate_route(ls, running_right):
#I wanted all routes to be seen as if they were running up from the left side of the ball
#need to find where they were orignially run from and transform accordingly
coords = list(ls.coords)
centroidx, _ = ls.centroid.xy
starting_point = coords[0]
running_right = bool(running_right)
high_field = starting_point[1] > 53.3 / 2
#translate the points so the starting point is at 0, 0
moved_coords = LineString([
(c[0] - starting_point[0], c[1] - starting_point[1]) for c in coords
])
#error checking
#draw_routes(ls.coords)
#routes are designed to be from 'left' side of the ball
if high_field:
if running_right:
#do a 90 degree turn
transformed_coords = affinity.rotate(moved_coords,
angle=90,
origin=(0, 0))
else:
#do a 270 degree turn and mirror
transformed_coords = affinity.affine_transform(
affinity.rotate(moved_coords, angle=270, origin=(0, 0)),
(-1, 0, 0, 1, 0, 0))
else:
if running_right:
#do a 90 degree turn and mirror
transformed_coords = affinity.affine_transform(
affinity.rotate(moved_coords, angle=90, origin=(0, 0)),
(-1, 0, 0, 1, 0, 0))
pass
else:
#do a 270 degree turn
transformed_coords = affinity.rotate(moved_coords,
angle=270,
origin=(0, 0))
#error checkign
#draw_routes(transformed_coords)
return transformed_coords
def add_line(poly_xy, idx, patch, patch_angle, patch_x, patch_y, line_list):
points = [(p0, p1) for p0, p1 in zip(poly_xy[0, idx:idx + 2], poly_xy[1, idx:idx + 2])]
line = LineString(points)
line.intersection(patch)
if not line.is_empty:
line = affinity.rotate(line, -patch_angle, origin=(patch_x, patch_y), use_radians=False)
line = affinity.affine_transform(line, [1.0, 0.0, 0.0, 1.0, -patch_x, -patch_y])
line_list.append(line)
def _transformed_rects():
for dx, dy in edges:
length = math.sqrt(dx**2 + dy**2)
ux, uy = dx / length, dy / length
vx, vy = -uy, ux
transf_rect = affine_transform(poly,
(ux, uy, vx, vy, 0, 0)).envelope
yield (transf_rect, (ux, vx, uy, vy, 0, 0))
def draw_lab(raster, shp, name, color, font, anc):
gs = shp['geometry'].centroid
m = raster.mat
m = [
1 / m[0, 1], 0, 0, -1 / m[0, 1], -m[0, 0] / m[0, 1], m[1, 0] / m[0, 1]
]
pos = [(int(p.x), int(p.y)) for p in [affine_transform(i, m) for i in gs]]
return draw_text(raster, shp[name], *list(zip(*pos)), color, font, anc)
def add_noise(self, x, rotation, translation):
trajectory = LineString(x)
mat = [1, 0, 0, 1, translation[0], translation[1]]
trajectory_translated = affine_transform(trajectory, mat)
# Apply rotation
trajectory_rotated = np.array(rotate(trajectory_translated, rotation, origin=(0, 0)).coords, dtype=np.float32)
return trajectory_rotated
def reproject_geometry(input_geom, input_crs=None, target_crs=None,
affine_obj=None):
"""Reproject a geometry or coordinate into a new CRS.
Arguments
---------
input_geom : `str`, `list`, or `Shapely <https://shapely.readthedocs.io>`_ geometry
A geometry object to re-project. This can be a 2-member ``list``, in
which case `input_geom` is assumed to coorespond to ``[x, y]``
coordinates in `input_crs`. It can also be a Shapely geometry object or
a wkt string.
input_crs : int, optional
The coordinate reference system for `input_geom`'s coordinates, as an
EPSG :class:`int`. Required unless `affine_transform` is provided.
target_crs : int, optional
The target coordinate reference system to re-project the geometry into.
If not provided, the appropriate UTM zone will be selected by default,
unless `affine_transform` is provided (and therefore CRSs are ignored.)
affine_transform : :class:`affine.Affine`, optional
An :class:`affine.Affine` object (or a ``[a, b, c, d, e, f]`` list to
convert to that format) to use for transformation. Has no effect unless
`input_crs` **and** `target_crs` are not provided.
Returns
-------
output_geom : Shapely geometry
A shapely geometry object:
- in `target_crs`, if one was provided;
- in the appropriate UTM zone, if `input_crs` was provided and
`target_crs` was not;
- with `affine_transform` applied to it if neither `input_crs` nor
`target_crs` were provided.
"""
input_geom = _check_geom(input_geom)
if input_crs is not None:
input_crs = _check_crs(input_crs)
if target_crs is None:
geom = reproject_geometry(input_geom, input_crs,
target_crs=_check_crs(4326))
target_crs = latlon_to_utm_epsg(geom.centroid.y, geom.centroid.x)
target_crs = _check_crs(target_crs)
gdf = gpd.GeoDataFrame(geometry=[input_geom], crs=input_crs.to_wkt())
# create a new instance of the same geometry class as above with the
# new coordinates
output_geom = gdf.to_crs(target_crs.to_wkt()).iloc[0]['geometry']
else:
if affine_obj is None:
raise ValueError('If an input CRS is not provided, '
'affine_transform is required to complete the '
'transformation.')
elif isinstance(affine_obj, Affine):
affine_obj = affine_to_list(affine_obj)
output_geom = affine_transform(input_geom, affine_obj)
return output_geom
def _to_shape(annot: ParsedAnnotation,
is_grayscale: bool = True) -> Tuple[BaseGeometry, int]:
width = _contour_width(annot.stroke_width)
geometry = stretch_contour(affine_transform(
contour(annot.geometry, point_style=point_style), affine),
width=width)
value = annot.stroke_color.as_rgb_tuple(
)[0] if is_grayscale else annot.stroke_color.as_int()
return geometry, value
def test_affine_2d(self):
g = load_wkt('LINESTRING(2.4 4.1, 2.4 3, 3 3)')
# custom scale and translate
expected2d = load_wkt('LINESTRING(-0.2 14.35, -0.2 11.6, 1 11.6)')
matrix2d = (2, 0,
0, 2.5,
-5, 4.1)
a2 = affinity.affine_transform(g, matrix2d)
self.assertTrue(a2.almost_equals(expected2d))
self.assertFalse(a2.has_z)
# Make sure a 3D matrix does not make a 3D shape from a 2D input
matrix3d = (2, 0, 0,
0, 2.5, 0,
0, 0, 10,
-5, 4.1, 100)
a3 = affinity.affine_transform(g, matrix3d)
self.assertTrue(a3.almost_equals(expected2d))
self.assertFalse(a3.has_z)
def _upload_annotation(cytomine, img_inst, polygon, label=None, proba=1.0):
"""Upload an annotation and its term (if provided)"""
image_id = img_inst.id
# Transform polygon to match cytomine (bottom-left) origin point
polygon = affine_transform(polygon, [1, 0, 0, -1, 0, img_inst.height])
annotation = cytomine.add_annotation(polygon.wkt, image_id)
if label is not None and annotation is not None:
cytomine.add_annotation_term(annotation.id, label, label, proba, annotation_term_model=AlgoAnnotationTerm)
def operate(self,design):
import shapely.affinity as aff
subdesign = design.subdesigns[self.subdesignid]
locateline = subdesign.findlocateline()
try:
designgeometry = subdesign.operations[subdesign.operation_index(self.subopid)].output[self.getoutputref()].csg
except AttributeError:
subdesign.reprocessoperations()
designgeometry = subdesign.operations[subdesign.operation_index(self.subopid)].output[self.getoutputref()].csg
sketch = design.sketches[self.sketchid]
if self.transformtype==self.transformtypes.place:
scale_x = 1.
scale_y = 1.
elif self.transformtype==self.transformtypes.stretch:
scale_x = None
scale_y = 1.
if self.transformtype==self.transformtypes.scale:
scale_x = None
scale_y = None
if self.transformtype==self.transformtypes.custom:
scale_x = self.scalex
scale_y = self.scaley
lsout = Laminate(design.return_layer_definition())
step = 1
if self.flip:
step = -1
if self.shift > 0:
outshift = self.shift
inshift = 0
elif self.shift <0:
outshift = 0
inshift = -self.shift
else:
outshift = 0
inshift = 0
for layerout,layerin in zip(design.return_layer_definition().layers[outshift:],subdesign.return_layer_definition().layers[::step][inshift:]):
newgeoms = []
for geom in sketch.operationgeometry:
for designgeom in designgeometry.layer_sequence[layerin].geoms:
try:
newgeoms.append(aff.affine_transform(designgeom,calctransformfrom2lines(locateline.exteriorpoints(),geom.exteriorpoints(),scale_x = scale_x,scale_y = scale_y)))
except IndexError:
pass
newgeoms = customshapely.unary_union_safe(newgeoms)
newgeoms = popupcad.geometry.customshapely.multiinit(newgeoms)
lsout.replacelayergeoms(layerout,newgeoms)
return lsout
def test_affine_geom_types(self):
# identity matrices, which should result with no transformation
matrix2d = (1, 0,
0, 1,
0, 0)
matrix3d = (1, 0, 0,
0, 1, 0,
0, 0, 1,
0, 0, 0)
# empty in, empty out
empty2d = load_wkt('MULTIPOLYGON EMPTY')
self.assertTrue(affinity.affine_transform(empty2d, matrix2d).is_empty)
def test_geom(g2, g3=None):
self.assertFalse(g2.has_z)
a2 = affinity.affine_transform(g2, matrix2d)
self.assertFalse(a2.has_z)
self.assertTrue(g2.equals(a2))
if g3 is not None:
self.assertTrue(g3.has_z)
a3 = affinity.affine_transform(g3, matrix3d)
self.assertTrue(a3.has_z)
self.assertTrue(g3.equals(a3))
return
pt2d = load_wkt('POINT(12.3 45.6)')
pt3d = load_wkt('POINT(12.3 45.6 7.89)')
test_geom(pt2d, pt3d)
ls2d = load_wkt('LINESTRING(0.9 3.4, 0.7 2, 2.5 2.7)')
ls3d = load_wkt('LINESTRING(0.9 3.4 3.3, 0.7 2 2.3, 2.5 2.7 5.5)')
test_geom(ls2d, ls3d)
lr2d = load_wkt('LINEARRING(0.9 3.4, 0.7 2, 2.5 2.7, 0.9 3.4)')
lr3d = load_wkt(
'LINEARRING(0.9 3.4 3.3, 0.7 2 2.3, 2.5 2.7 5.5, 0.9 3.4 3.3)')
test_geom(lr2d, lr3d)
test_geom(load_wkt('POLYGON((0.9 2.3, 0.5 1.1, 2.4 0.8, 0.9 2.3), '
'(1.1 1.7, 0.9 1.3, 1.4 1.2, 1.1 1.7), '
'(1.6 1.3, 1.7 1, 1.9 1.1, 1.6 1.3))'))
test_geom(load_wkt(
'MULTIPOINT ((-300 300), (700 300), (-800 -1100), (200 -300))'))
test_geom(load_wkt(
'MULTILINESTRING((0 0, -0.7 -0.7, 0.6 -1), '
'(-0.5 0.5, 0.7 0.6, 0 -0.6))'))
test_geom(load_wkt(
'MULTIPOLYGON(((900 4300, -1100 -400, 900 -800, 900 4300)), '
'((1200 4300, 2300 4400, 1900 1000, 1200 4300)))'))
# GeometryCollection fails, since it does not have a good constructor
gc = load_wkt('GEOMETRYCOLLECTION(POINT(20 70),'
' POLYGON((60 70, 13 35, 60 -30, 60 70)),'
' LINESTRING(60 70, 50 100, 80 100))')
self.assertRaises(TypeError, test_geom, gc) # TODO: fix this
def _transformed_rects():
for dx, dy in edges:
# compute the normalized direction vector of the edge vector
length = math.sqrt(dx**2 + dy**2)
ux, uy = dx/length, dy/length
# compute the normalized perpendicular vector
vx, vy = -uy, ux
# transform hull from the original coordinate system to the coordinate system
# defined by the edge and compute the axes-parallel bounding rectangle
transf_rect = affine_transform(hull, (ux,uy,vx,vy,0,0)).envelope
# yield the transformed rectangle and a matrix to transform it back
# to the original coordinate system
yield (transf_rect, (ux,vx,uy,vy,0,0))
def test_affine_3d(self):
g2 = load_wkt('LINESTRING(2.4 4.1, 2.4 3, 3 3)')
g3 = load_wkt('LINESTRING(2.4 4.1 100.2, 2.4 3 132.8, 3 3 128.6)')
# custom scale and translate
matrix2d = (2, 0,
0, 2.5,
-5, 4.1)
matrix3d = (2, 0, 0,
0, 2.5, 0,
0, 0, 0.3048,
-5, 4.1, 100)
# Combinations of 2D and 3D geometries and matrices
a22 = affinity.affine_transform(g2, matrix2d)
a23 = affinity.affine_transform(g2, matrix3d)
a32 = affinity.affine_transform(g3, matrix2d)
a33 = affinity.affine_transform(g3, matrix3d)
# Check dimensions
self.assertFalse(a22.has_z)
self.assertFalse(a23.has_z)
self.assertTrue(a32.has_z)
self.assertTrue(a33.has_z)
# 2D equality checks
expected2d = load_wkt('LINESTRING(-0.2 14.35, -0.2 11.6, 1 11.6)')
expected3d = load_wkt('LINESTRING(-0.2 14.35 130.54096, '
'-0.2 11.6 140.47744, 1 11.6 139.19728)')
expected32 = load_wkt('LINESTRING(-0.2 14.35 100.2, '
'-0.2 11.6 132.8, 1 11.6 128.6)')
self.assertTrue(a22.almost_equals(expected2d))
self.assertTrue(a23.almost_equals(expected2d))
# Do explicit 3D check of coordinate values
for a, e in zip(a32.coords, expected32.coords):
for ap, ep in zip(a, e):
self.assertAlmostEqual(ap, ep)
for a, e in zip(a33.coords, expected3d.coords):
for ap, ep in zip(a, e):
self.assertAlmostEqual(ap, ep)
def operate(self,design):
from popupcad.filetypes.genericshapes import GenericLine
import shapely.affinity as aff
import popupcad.algorithms.points as points
import popupcad
import shapely.geometry as sg
import numpy
parent_ref,parent_index = self.operation_links['source'][0]
parent = design.op_from_ref(parent_ref).output[parent_index].csg
sketch = design.sketches[self.sketch_links['cross_section'][0]]
layerdef = design.return_layer_definition()
laminate = Laminate(layerdef)
for item in sketch.operationgeometry:
if isinstance(item,GenericLine):
line = item
b = line.exteriorpoints()[0]
c = numpy.array(b)+numpy.array([1,0])
a = points.calctransformfrom2lines(line.exteriorpoints(),[b,c.tolist()],scale_x=1,scale_y=1)
sketch_csg = sketch.output_csg()
for layer in layerdef.layers:
laminate.replacelayergeoms(layer,sketch_csg)
result = parent.intersection(laminate)
laminate2 = Laminate(layerdef)
for ii,layerid in enumerate(layerdef.layers):
# for ii,layer in enumerate(result):
yshift = layerdef.zvalue[layerid] * self.scale_value
layer = result.layer_sequence[layerid]
thickness = layerid.thickness*popupcad.internal_argument_scaling*self.scale_value
newgeoms = [item for item in layer.geoms]
newgeoms = [aff.affine_transform(item,a) for item in newgeoms]
# newgeoms = [item.buffer(bufferval) for item in newgeoms]
newgeoms2 = []
for geom in newgeoms:
newgeom = sg.box(geom.coords[0][0],geom.coords[0][1],geom.coords[-1][0],geom.coords[-1][1]+thickness)
newgeoms2.append(newgeom)
newgeoms = newgeoms2
newgeoms = [aff.translate(item,yoff = yshift) for item in newgeoms]
newgeoms = popupcad.geometry.customshapely.multiinit(*newgeoms)
laminate2[ii] = newgeoms
return laminate2
return laminate
def cross_section(layerdef, sketch, parent, scale_value):
from popupcad.filetypes.laminate import Laminate
from popupcad.filetypes.genericshapes import GenericLine
import shapely.affinity as aff
import popupcad.algorithms.points as points
import shapely.geometry as sg
import numpy
laminate = Laminate(layerdef)
for item in sketch.operationgeometry:
if isinstance(item, GenericLine):
line = item
b = line.exteriorpoints(scaling = popupcad.csg_processing_scaling)[0]
c = numpy.array(b) + numpy.array([1, 0])
a = points.calctransformfrom2lines(
line.exteriorpoints(scaling = popupcad.csg_processing_scaling), [
b, c.tolist()], scale_x=1, scale_y=1)
sketch_csg = sketch.output_csg()
for layer in layerdef.layers:
laminate.replacelayergeoms(layer, sketch_csg)
result = parent.intersection(laminate)
laminate2 = Laminate(layerdef)
for ii, layerid in enumerate(layerdef.layers):
# for ii,layer in enumerate(result):
yshift = layerdef.zvalue[layerid] * popupcad.csg_processing_scaling * scale_value
layer = result.layer_sequence[layerid]
thickness = layerid.thickness * popupcad.csg_processing_scaling * scale_value
newgeoms = [item for item in layer.geoms]
newgeoms = [aff.affine_transform(item, a) for item in newgeoms]
# newgeoms = [item.buffer(bufferval) for item in newgeoms]
newgeoms2 = []
for geom in newgeoms:
newgeom = sg.box(geom.coords[0][0],
geom.coords[0][1],
geom.coords[-1][0],
geom.coords[-1][1] + thickness)
newgeoms2.append(newgeom)
newgeoms = newgeoms2
newgeoms = [aff.translate(item,yoff=yshift) for item in newgeoms]
newgeoms = popupcad.algorithms.csg_shapely.condition_shapely_entities(*newgeoms)
laminate2[ii] = newgeoms
return laminate2
return laminate
def transform(
layerdef,
layerdef_subdesign,
inshift,
outshift,
step,
sketch,
designgeometry,
locateline,
scale_x,
scale_y):
from popupcad.filetypes.laminate import Laminate
import shapely.affinity as aff
from popupcad.algorithms.points import calctransformfrom2lines
lsout = Laminate(layerdef)
for layerout, layerin in zip(
layerdef.layers[
outshift:], layerdef_subdesign.layers[
::step][
inshift:]):
newgeoms = []
for geom in sketch.operationgeometry:
if not geom.is_construction():
for designgeom in designgeometry.layer_sequence[layerin].geoms:
try:
newgeoms.append(
aff.affine_transform(
designgeom,
calctransformfrom2lines(
locateline.exteriorpoints(scaling = popupcad.csg_processing_scaling),
geom.exteriorpoints(scaling = popupcad.csg_processing_scaling),
scale_x=scale_x,
scale_y=scale_y)))
except IndexError:
pass
result1 = popupcad.algorithms.csg_shapely.unary_union_safe(newgeoms)
results2 = popupcad.algorithms.csg_shapely.condition_shapely_entities(result1)
lsout.replacelayergeoms(layerout, results2)
return lsout
def _locate(segmented, offset=None):
"""Inspired from: https://goo.gl/HYPrR1"""
# CV_RETR_EXTERNAL to only get external contours.
_, contours, hierarchy = cv2.findContours(segmented.copy(),
cv2.RETR_CCOMP,
cv2.CHAIN_APPROX_SIMPLE)
# Note: points are represented as (col, row)-tuples apparently
transform = identity
if offset is not None:
col_off, row_off = offset
transform = lambda p: affine_transform(p, [1, 0, 0, 1, col_off, row_off])
components = []
if len(contours) > 0:
top_index = 0
tops_remaining = True
while tops_remaining:
exterior = contours[top_index][:, 0, :].tolist()
interiors = []
# check if there are childs and process if necessary
if hierarchy[0][top_index][2] != -1:
sub_index = hierarchy[0][top_index][2]
subs_remaining = True
while subs_remaining:
interiors.append(contours[sub_index][:, 0, :].tolist())
# check if there is another sub contour
if hierarchy[0][sub_index][0] != -1:
sub_index = hierarchy[0][sub_index][0]
else:
subs_remaining = False
# add component tuple to components only if exterior is a polygon
if len(exterior) == 1:
components.append(Point(exterior[0]))
elif len(exterior) == 2:
components.append(LineString(exterior))
elif len(exterior) > 2:
polygon = Polygon(exterior, interiors)
polygon = transform(polygon)
if polygon.is_valid: # some polygons might be invalid
components.append(polygon)
else:
fixed = fix_geometry(polygon)
if fixed.is_valid and not fixed.is_empty:
components.append(fixed)
else:
warn("Attempted to fix invalidity '{}' in polygon but failed... "
"Output polygon still invalid '{}'".format(explain_validity(polygon),
explain_validity(fixed)))
# check if there is another top contour
if hierarchy[0][top_index][0] != -1:
top_index = hierarchy[0][top_index][0]
else:
tops_remaining = False
del contours
del hierarchy
return components
def getsvggeo(node):
"""
Extracts and flattens all geometry from an SVG node
into a list of Shapely geometry.
:param node: xml.etree.ElementTree.Element
:return: List of Shapely geometry
:rtype: list
"""
kind = re.search('(?:\{.*\})?(.*)$', node.tag).group(1)
geo = []
# Recurse
if len(node) > 0:
for child in node:
subgeo = getsvggeo(child)
if subgeo is not None:
geo += subgeo
# Parse
elif kind == 'path':
log.debug("***PATH***")
P = parse_path(node.get('d'))
P = path2shapely(P)
geo = [P]
elif kind == 'rect':
log.debug("***RECT***")
R = svgrect2shapely(node)
geo = [R]
elif kind == 'circle':
log.debug("***CIRCLE***")
C = svgcircle2shapely(node)
geo = [C]
elif kind == 'ellipse':
log.debug("***ELLIPSE***")
E = svgellipse2shapely(node)
geo = [E]
elif kind == 'polygon':
log.debug("***POLYGON***")
poly = svgpolygon2shapely(node)
geo = [poly]
elif kind == 'line':
log.debug("***LINE***")
line = svgline2shapely(node)
geo = [line]
elif kind == 'polyline':
log.debug("***POLYLINE***")
pline = svgpolyline2shapely(node)
geo = [pline]
else:
log.warning("Unknown kind: " + kind)
geo = None
# Transformations
if 'transform' in node.attrib:
trstr = node.get('transform')
trlist = parse_svg_transform(trstr)
#log.debug(trlist)
# Transformations are applied in reverse order
for tr in trlist[::-1]:
if tr[0] == 'translate':
geo = [translate(geoi, tr[1], tr[2]) for geoi in geo]
elif tr[0] == 'scale':
geo = [scale(geoi, tr[0], tr[1], origin=(0, 0))
for geoi in geo]
elif tr[0] == 'rotate':
geo = [rotate(geoi, tr[1], origin=(tr[2], tr[3]))
for geoi in geo]
elif tr[0] == 'skew':
geo = [skew(geoi, tr[1], tr[2], origin=(0, 0))
for geoi in geo]
elif tr[0] == 'matrix':
geo = [affine_transform(geoi, tr[1:]) for geoi in geo]
else:
raise Exception('Unknown transformation: %s', tr)
return geo
def cov_transform(p, obst_cov):
''' Returns the convex polygon p transformed by W, where W*cov*W^T = I'''
W = np.linalg.inv( np.linalg.cholesky(obst_cov) )
affine_params = np.concatenate((W.flatten(), np.zeros(2)))
return affinity.affine_transform(p, affine_params), W
