import io from types import NoneType import obja.obja as obja import numpy as np import argparse def sliding_window(l: list): head = l[:-1] tail = l[1:] return zip(head, tail) class MAPS(obja.Model): """_summary_ Args: obja (_type_): _description_ """ def __init__(self): super().__init__() self.deleted_faces = set() def one_ring(self, index: int) -> tuple[list[int], list[int]]: """ Return the corresponding 1-ring Args: index (int): index of the 1-ring's main vertex Returns: list[int]: ordered list of the 1-ring vertices """ # Find the 1-ring faces ring_faces, ring_face_indices = [], [] for face_index, face in enumerate(self.faces): if face == None: continue if index in (face.a, face.b, face.c): ring_faces.append(face) ring_face_indices.append(face_index) # Initialize the ring start_index = ring_faces[0].a if ring_faces[0].a != index else ring_faces[0].b ring = [start_index] ring_faces.pop(0) # Select the indexes of the ring in the right order while len(ring_faces) > 0: broke = False prev_index = ring[-1] for i, face in enumerate(ring_faces): if prev_index in (face.a, face.b, face.c): # Found the face that correspond to the next vertex current_index = ( # select the next vertex from the face face.a if face.a != index and face.a != prev_index else face.b if face.b != index and face.b != prev_index else face.c ) ring.append(current_index) ring_faces.pop(i) broke = True break if not broke: raise ValueError( f"Vertex {prev_index} is not in the remaining faces {ring_faces}. Origin {ring} on {index}") return ring, ring_face_indices def compute_area_curvature(self, index: int) -> tuple[float, float, int]: """ Compute area and curvature the corresponding 1-ring Args: index (int): index of the 1-ring's main vertex Returns: tuple[float, float]: area and curvature """ area_sum = 0 curvature_sum = 0 one_ring_vertices, _ = self.one_ring(index) p1 = self.vertices[index] # the center of the one-ring for index2, index3 in sliding_window(one_ring_vertices): p2 = self.vertices[index2] # the second vertice of the triangle p3 = self.vertices[index3] # the third vertice of the triangle M = np.array([ # build the matrix, used to compute the area [p1[0], p2[0], p3[0]], [p1[1], p2[1], p3[1]], [p1[2], p2[2], p3[2]], ]) area = abs(np.linalg.det(M) / 2) # compute the area area_sum += area curvature = 4 * area / ( # compute the curvature np.linalg.norm(p1-p2) * np.linalg.norm(p2-p3) * np.linalg.norm(p3-p1) ) curvature_sum += curvature return area_sum, curvature_sum, len(one_ring_vertices) def compute_priority(self, lamb: float = 0.5, max_length: int = 12) -> list[float]: """ Compute selection priority of vertices (0 -> hight priority ; 1 -> low priority) Args: lamb (float, optional): convex combination factor. Defaults to 0.5. max_length (int, optional): 1-ring maximum length to be prioritary. Defaults to 12. Returns: list[float]: priority values """ # Compute area and curvature for each vertex areas, curvatures, ring_lengths = [], [], [] for i in range(len(self.vertices)): if type(self.vertices[i]) != NoneType: area, curvature, ring_length = self.compute_area_curvature(i) else: area, curvature, ring_length = -1.0, -1.0, None areas.append(area) curvatures.append(curvature) ring_lengths.append(ring_length) # Get maxes to normalize max_area = max(areas) max_curvature = max(curvatures) # Compute priorities priorities = [] for a, k, l in zip(areas, curvatures, ring_lengths): if l != None and l <= max_length: # Compute priority priority = lamb * a / max_area + \ (1.0 - lamb) * k / max_curvature else: # Vertex with low priority priority = 2.0 priorities.append(priority) return priorities def select_vertices(self) -> list[int]: """ Select vertices for the current level reduction Returns: list[int]: selected vertices """ print("Selecting vertices...") # Order vertices by priority priorities = self.compute_priority() vertices = [i[0] for i in sorted(enumerate(priorities), key=lambda p: p[1])] selected_vertices = [] while len(vertices) > 0: # Select prefered vertex vertex = vertices.pop(0) # remove it from remaining vertices if priorities[vertex] == 2.0: continue selected_vertices.append(vertex) # Remove neighbors # for face in remaining_faces: for face in self.faces: if face == None: continue face_vertices = (face.a, face.b, face.c) if vertex in face_vertices: # Remove face and face's vertices form remainings # remaining_faces.remove(face) for face_vertex in face_vertices: if face_vertex in vertices: vertices.remove(face_vertex) for ver in selected_vertices: ring, _ = self.one_ring(ver) for v in selected_vertices: for r in ring: if r == v: print(f"fuck:{ver},{ring}") print("Vertices selected.") return selected_vertices def project_polar(self, index: int) -> list[np.ndarray]: """ Flatten the 1-ring to retriangulate Args: index (int): main vertex of the 1-ring Returns: list[np.ndarray]: list the cartesian coordinates of the flattened 1-ring projected in the plane """ ring, _ = self.one_ring(index) radius, angles = [], [] teta = 0.0 # cumulated angles for index1, index2 in sliding_window(ring + [ring[0]]): r = np.linalg.norm(self.vertices[index] - self.vertices[index1]) teta += self.compute_angle(index1, index, index2) # add new angle radius.append(r) angles.append(teta) angles = [2 * np.pi * a / teta for a in angles] # normalize angles coordinates = [np.array([r * np.cos(a), r * np.sin(a)]) for r, a in zip(radius, angles)] # parse polar to cartesian return coordinates, ring def compute_angle(self, i: int, j: int, k: int) -> float: """ Calculate the angle defined by three points Args: i (int): previous index j (int): central index k (int): next index Returns: float: angle defined by the three points """ a = self.vertices[i] b = self.vertices[j] c = self.vertices[k] u = a - b v = c - b u /= np.linalg.norm(u) v /= np.linalg.norm(v) res = np.dot(u, v) return np.arccos(np.clip(res, -1, 1)) def clip_ear(self, index: int) -> tuple[list[obja.Face], int]: """ Retriangulate a polygon using the ear clipping algorithm Args: index (int): index of 1-ring Returns: tuple[list[obja.Face], int]: list the triangles """ polygon, ring = self.project_polar(index) faces = [] # the final list of faces indices = [(local_i, global_i) for local_i, global_i in enumerate(ring)] # remainging vertices node_index = 0 while len(indices) > 2: # Extract indices local_i, global_i = indices[node_index - 1] local_j, global_j = indices[node_index] local_k, global_k = indices[node_index + 1] # Extract verticies prev_vert = polygon[local_i] curr_vert = polygon[local_j] next_vert = polygon[local_k] is_convex = MAPS.is_convex(prev_vert, curr_vert, next_vert) is_ear = True if is_convex: # the triangle needs to be convext to be an ear # Begin with the point next to the triangle test_node_index = (node_index + 2) % len(indices) while indices[test_node_index][0] != local_i and is_ear: test_vert = polygon[indices[test_node_index][0]] is_ear = not MAPS.is_inside(prev_vert, curr_vert, next_vert, test_vert) test_node_index = (test_node_index + 1) % len(indices) else: is_ear = False if is_ear: faces.append(obja.Face(global_i, global_j, global_k)) indices.pop(node_index) # remove the point from the ring node_index = (node_index + 2) % len(indices) - 1 return faces def is_convex(prev_vert: np.ndarray, curr_vert: np.ndarray, next_vert: np.ndarray) -> bool: """ Check if the angle less than pi Args: prev_vert (np.ndarray): first point curr_vert (np.ndarray): middle point next_vert (np.ndarray): last point Returns: bool: angle smaller than pi """ a = prev_vert - curr_vert b = next_vert - curr_vert dot = a[0] * b[0] + a[1] * b[1] det = a[0] * b[1] - a[1] * b[0] angle = np.arctan2(det, dot) if angle < 0.0: angle = 2.0 * np.pi + angle internal_angle = angle return internal_angle >= np.pi def is_inside(a: np.ndarray, b: np.ndarray, c: np.ndarray, p: np.ndarray) -> bool: """ Check if p is in the triangle a b c Args: a (np.ndarray): point one b (np.ndarray): point two c (np.ndarray): point three p (np.ndarray): point to check Returns: bool: if the point to check is in a b c """ # Compute vectors v0 = c - a v1 = b - a v2 = p - a # Compute dot products dot00 = np.dot(v0, v0) dot01 = np.dot(v0, v1) dot02 = np.dot(v0, v2) dot11 = np.dot(v1, v1) dot12 = np.dot(v1, v2) # Compute barycentric coordinates denom = dot00 * dot11 - dot01 * dot01 if abs(denom) < 1e-20: return True invDenom = 1.0 / denom u = (dot11 * dot02 - dot01 * dot12) * invDenom v = (dot00 * dot12 - dot01 * dot02) * invDenom # Check if point is in triangle return (u >= 0) and (v >= 0) and (u + v < 1) def contract(self, output: io.TextIOWrapper) -> None: """ Compress the 3d model Args: output (io.TextIOWrapper): Output file descriptor """ operations = [] # while len(self.vertices) > 64: for i in range(16): selected_vertices = self.select_vertices() # find the set of vertices to remove faces_to_add, faces_to_remove = [], [] while len(selected_vertices) > 0: vertex = selected_vertices.pop(0) # get next vertex print(f" {len(selected_vertices)} ", end='\r') # Extract ring faces _, ring_faces = self.one_ring(vertex) faces_to_remove += ring_faces # Apply retriangulation algorithm faces = self.clip_ear(vertex) faces_to_add += faces # Edit the first faces for i in range(len(faces)): operations.append( ('ef', ring_faces[i], self.faces[ring_faces[i]])) self.faces[ring_faces[i]] = faces[i] # Remove the last faces for i in range(len(faces), len(ring_faces)): operations.append( ('af', ring_faces[i], self.faces[ring_faces[i]])) self.faces[ring_faces[i]] = None # Remove the vertex operations.append(('av', vertex, self.vertices[vertex])) self.vertices[vertex] = None # REgister remaining vertices and faces for i, face in enumerate(self.faces): if face != None: operations.append(('af', i, face)) for i, vertex in enumerate(self.vertices): if type(vertex) != NoneType: operations.append(('av', i, vertex)) # To rebuild the model, run operations in reverse order operations.reverse() # Write the result in output file output_model = obja.Output(output) for (op, index, value) in operations: if op == 'av': output_model.add_vertex(index, value) elif op == 'af': output_model.add_face(index, value) elif op == 'ev': output_model.edit_vertex(index, value) elif op == 'ef': output_model.edit_face(index, value) def main(args): """ Run MAPS model compression Args: args (Namespace): arguments (input and output path) """ model = MAPS() model.parse_file(args.input) with open(args.output, 'w') as output: model.contract(output) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('-i', '--input', type=str, required=True) parser.add_argument('-o', '--output', type=str, required=True) args = parser.parse_args() main(args)