def triangle_mesh_equirectangular(shot_id, r, graph):
shot = r['shots'][shot_id]
cam = r['cameras'][shot['camera']]
bearings = []
vertices = []
# Add vertices to ensure that the camera is inside the convex hull of the points
for point in itertools.product([-1, 1], repeat=3): # vertices of a cube
bearing = 0.3 * np.array(point) / np.linalg.norm(point)
bearings.append(bearing)
point = reconstruction.world_coordinates(cam, shot, bearing)
vertices.append(point.tolist())
for track_id, edge in graph[shot_id].items():
if track_id in r['points']:
point = r['points'][track_id]['coordinates']
vertices.append(point)
direction = reconstruction.camera_coordinates(cam, shot, point)
pixel = direction / np.linalg.norm(direction)
bearings.append(pixel.tolist())
tri = scipy.spatial.ConvexHull(bearings)
faces = tri.simplices.tolist()
return vertices, faces
def triangle_mesh_equirectangular(shot_id, r, graph):
shot = r['shots'][shot_id]
cam = r['cameras'][shot['camera']]
bearings = []
vertices = []
# Add vertices to ensure that the camera is inside the convex hull of the points
for point in itertools.product([-1, 1], repeat=3): # vertices of a cube
bearing = 0.3 * np.array(point) / np.linalg.norm(point)
bearings.append(bearing)
point = reconstruction.world_coordinates(cam, shot, bearing)
vertices.append(point.tolist())
for track_id, edge in graph[shot_id].items():
if track_id in r['points']:
point = r['points'][track_id]['coordinates']
vertices.append(point)
direction = reconstruction.camera_coordinates(cam, shot, point)
pixel = direction / np.linalg.norm(direction)
bearings.append(pixel.tolist())
tri = scipy.spatial.ConvexHull(bearings)
faces = tri.simplices.tolist()
return vertices, faces
def triangle_mesh_perspective(shot_id, r, graph):
shot = r['shots'][shot_id]
cam = r['cameras'][shot['camera']]
dx = float(cam['width']) / 2 / max(cam['width'], cam['height'])
dy = float(cam['height']) / 2 / max(cam['width'], cam['height'])
pixels = [[-dx, -dy], [-dx, dy], [dx, dy], [dx, -dy]]
vertices = [None for i in range(4)]
for track_id, edge in graph[shot_id].items():
if track_id in r['points']:
point = r['points'][track_id]
pixel = reconstruction.reproject(cam, shot, point)
if -dx <= pixel[0] <= dx and -dy <= pixel[1] <= dy:
vertices.append(point['coordinates'])
pixels.append(pixel.tolist())
try:
tri = scipy.spatial.Delaunay(pixels)
except Exception as e:
logger.error('Delaunay triangulation failed for input: {}'.format(
` pixels `))
raise e
sums = [0., 0., 0., 0.]
depths = [0., 0., 0., 0.]
for t in tri.simplices:
for i in range(4):
if i in t:
for j in t:
if j >= 4:
depths[i] += reconstruction.camera_coordinates(
cam, shot, vertices[j])[2]
sums[i] += 1
for i in range(4):
if sums[i] > 0:
d = depths[i] / sums[i]
else:
d = 50.0
vertices[i] = reconstruction.back_project(cam, shot, pixels[i],
d).tolist()
faces = tri.simplices.tolist()
return vertices, faces
def triangle_mesh(shot_id, r, graph, data):
'''
Create triangle meshes in a list
'''
if 'shots' not in r or shot_id not in r['shots'] or shot_id not in graph:
return [], []
shot = r['shots'][shot_id]
cam = r['cameras'][shot['camera']]
dx = float(cam['width']) / 2 / max(cam['width'], cam['height'])
dy = float(cam['height']) / 2 / max(cam['width'], cam['height'])
pixels = [[-dx, -dy], [-dx, dy], [dx, dy], [dx, -dy]]
vertices = [None for i in range(4)]
for track_id, edge in graph[shot_id].items():
if track_id in r['points']:
point = r['points'][track_id]
vertices.append(point['coordinates'])
pixel = reconstruction.reproject(cam, shot, point)
pixels.append(pixel.tolist())
tri = scipy.spatial.Delaunay(pixels)
sums = [0., 0., 0., 0.]
depths = [0., 0., 0., 0.]
for t in tri.simplices:
for i in range(4):
if i in t:
for j in t:
if j >= 4:
depths[i] += reconstruction.camera_coordinates(
cam, shot, vertices[j])[2]
sums[i] += 1
for i in range(4):
if sums[i] > 0:
d = depths[i] / sums[i]
else:
d = 50.0
vertices[i] = reconstruction.back_project(cam, shot, pixels[i],
d).tolist()
faces = tri.simplices.tolist()
return vertices, faces
def triangle_mesh_perspective(shot_id, r, graph):
shot = r['shots'][shot_id]
cam = r['cameras'][shot['camera']]
dx = float(cam['width']) / 2 / max(cam['width'], cam['height'])
dy = float(cam['height']) / 2 / max(cam['width'], cam['height'])
pixels = [[-dx, -dy], [-dx, dy], [dx, dy], [dx, -dy]]
vertices = [None for i in range(4)]
for track_id, edge in graph[shot_id].items():
if track_id in r['points']:
point = r['points'][track_id]
pixel = reconstruction.reproject(cam, shot, point)
if -dx <= pixel[0] <= dx and -dy <= pixel[1] <= dy:
vertices.append(point['coordinates'])
pixels.append(pixel.tolist())
try:
tri = scipy.spatial.Delaunay(pixels)
except Exception as e:
logger.error('Delaunay triangulation failed for input: {}'.format(`pixels`))
raise e
sums = [0.,0.,0.,0.]
depths = [0.,0.,0.,0.]
for t in tri.simplices:
for i in range(4):
if i in t:
for j in t:
if j >= 4:
depths[i] += reconstruction.camera_coordinates(cam, shot, vertices[j])[2]
sums[i] += 1
for i in range(4):
if sums[i] > 0:
d = depths[i] / sums[i]
else:
d = 50.0
vertices[i] = reconstruction.back_project(cam, shot, pixels[i], d).tolist()
faces = tri.simplices.tolist()
return vertices, faces
def triangle_mesh(shot_id, r, graph, data):
'''
Create triangle meshes in a list
'''
if 'shots' not in r or shot_id not in r['shots'] or shot_id not in graph:
return [], []
shot = r['shots'][shot_id]
cam = r['cameras'][shot['camera']]
dx = float(cam['width']) / 2 / max(cam['width'], cam['height'])
dy = float(cam['height']) / 2 / max(cam['width'], cam['height'])
pixels = [[-dx, -dy], [-dx, dy], [dx, dy], [dx, -dy]]
vertices = [None for i in range(4)]
for track_id, edge in graph[shot_id].items():
if track_id in r['points']:
point = r['points'][track_id]
vertices.append(point['coordinates'])
pixel = reconstruction.reproject(cam, shot, point)
pixels.append(pixel.tolist())
tri = scipy.spatial.Delaunay(pixels)
sums = [0.,0.,0.,0.]
depths = [0.,0.,0.,0.]
for t in tri.simplices:
for i in range(4):
if i in t:
for j in t:
if j >= 4:
depths[i] += reconstruction.camera_coordinates(cam, shot, vertices[j])[2]
sums[i] += 1
for i in range(4):
if sums[i] > 0:
d = depths[i] / sums[i]
else:
d = 50.0
vertices[i] = reconstruction.back_project(cam, shot, pixels[i], d).tolist()
faces = tri.simplices.tolist()
return vertices, faces
