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* update script

* add shape

* remove mysql
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yuichiroaoki authored Dec 13, 2023
1 parent 868ccc5 commit b313769
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4 changes: 0 additions & 4 deletions .github/workflows/ci.yml
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Expand Up @@ -38,10 +38,6 @@ jobs:
with:
python-version: ${{ matrix.python-version }}

- name: Run MySQL
run: |
docker-compose up -d mysql
- name: Run image
uses: abatilo/actions-poetry@v2
with:
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Empty file removed cnceye/edge/__init__.py
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158 changes: 0 additions & 158 deletions cnceye/edge/find.py

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160 changes: 160 additions & 0 deletions cnceye/shape.py
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import trimesh
import numpy as np
from trimesh.graph import face_adjacency


class Shape:
def __init__(self, stl_file_path: str):
self.mesh = trimesh.load(stl_file_path)

def get_unique_z_values_of_visiable_vertices(self):
# Get the normals of the facets
facet_normals = self.mesh.face_normals

# Find the indices of facets facing "up" (positive z-direction)
upward_facing_indices = np.where(facet_normals[:, 2] > 0)[0]

# Get the unique vertices associated with upward-facing facets
visible_vertices = np.unique(self.mesh.faces[upward_facing_indices])

# Extract the coordinates of the visible vertices
visible_vertex_coordinates = self.mesh.vertices[visible_vertices]

# get unique z values
unique_z = np.unique(visible_vertex_coordinates[:, 2])
return unique_z

def get_visible_facets(self):
# Get the normals of the facets
facet_normals = self.mesh.face_normals

# Find the indices of facets facing "up" (positive z-direction)
upward_facing_indices = np.where(facet_normals[:, 2] > 0)[0]

return upward_facing_indices

def are_coplanar(self, facet_idx0, facet_idx1, tolerance=1e-6):
facet0 = self.mesh.vertices[self.mesh.faces[facet_idx0]]
facet1 = self.mesh.vertices[self.mesh.faces[facet_idx1]]
# Calculate the normal vector for each facet
normal0 = np.cross(facet0[1] - facet0[0], facet0[2] - facet0[0])
normal1 = np.cross(facet1[1] - facet1[0], facet1[2] - facet1[0])

# Check if the normal vectors are parallel
if np.all(
np.isclose(
normal0 / np.linalg.norm(normal0),
normal1 / np.linalg.norm(normal1),
atol=tolerance,
)
):
# if np.allclose(normal0, normal1):
# Check if the facets are coplanar
if np.all(np.abs(np.dot(facet1[0] - facet0[0], normal0)) < 1e-6):
# The facets are coplanar
return True
else:
# The facets are parallel but not coplanar
return False
else:
# The facets are not coplanar
return False

def group_by_coplanar_facets(self, facet_indices: np.ndarray):
"""
Group facets that are coplanar \n
Return a list of lists of coplanar facets
"""
coplanar_facets = [[facet_indices[0]]]
for facet_idx in facet_indices[1:]:
is_coplanar = False
for i, coplanar_facet in enumerate(coplanar_facets):
if self.are_coplanar(facet_idx, coplanar_facet[0]):
coplanar_facets[i].append(facet_idx)
is_coplanar = True
break
if not is_coplanar:
coplanar_facets.append([facet_idx])
is_coplanar = False

return coplanar_facets

def get_lines_and_arcs(self, decimal_places: int = 3, arc_threshold: int = 1):
shapes = self.get_shapes()
lines = []
arcs = []

previous_length = 0
for coplanar_shapes in shapes:
line_group = []
arc_group = []
for i in range(len(coplanar_shapes)):
point0 = self.mesh.vertices[coplanar_shapes[i][0]]
point1 = self.mesh.vertices[coplanar_shapes[i][1]]
point = np.array([point0, point1])
line_length = np.linalg.norm(point0 - point1)
if line_length > arc_threshold:
# line
line_group.append(point)
else:
# arc
# if close to previous length, add to previous arc
if np.isclose(line_length, previous_length, atol=1e-3):
arc_group[-1] = np.vstack((arc_group[-1], point1))
else:
arc_group.append(point)

previous_length = line_length

# round to decimal places
line_group = round_shape_values(line_group, decimal_places)
arc_group = round_shape_values(arc_group, decimal_places)

if line_group:
lines.append(line_group)
if arc_group:
arcs.append(arc_group)

return lines, arcs

def get_shapes(self):
"""
Extract lines and arcs from an STL file \n
If the line length is less than 1, it is considered an arc. \n
if the line length for an arc is close to the previous arc length,
it is considered part of the previous arc. \n
Note: This is not a robust algorithm.
"""
visible_facet_indices = self.get_visible_facets()
group_facets = self.group_by_coplanar_facets(visible_facet_indices)
adjacency = face_adjacency(self.mesh.faces)

shapes = []
for coplanar_facets in group_facets:
shapes_on_coplanar_facet = []
for pair in adjacency:
pair0_in_group = pair[0] in coplanar_facets
pair1_in_group = pair[1] in coplanar_facets
if pair0_in_group != pair1_in_group:
common_edge_vertices = list(
set(self.mesh.faces[pair[0]]) & set(self.mesh.faces[pair[1]])
)
if pair0_in_group:
face_id = pair[1]
else:
face_id = pair[0]
common_edge_vertices.append(face_id)
shapes_on_coplanar_facet.append(common_edge_vertices)

# order by face index
shapes_on_coplanar_facet.sort(key=lambda x: x[-1])
shapes.append(shapes_on_coplanar_facet)

return shapes


def round_shape_values(shapes: np.ndarray, decimal_places: int = 3):
for i in range(len(shapes)):
shapes[i] = np.round(shapes[i], decimals=decimal_places)

return shapes
11 changes: 0 additions & 11 deletions docker-compose.yml

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