Define Bounding Box By Camera Locations

[Dragline]

I would like to define a bounding box based on the locations of where photos were taken. It would also be nice to add a buffer around the perimeter defined by the cameras. Does anyone have any idea how to approach this?

[Alexey Pasumansky]

Hello Dragline,

Please try the following script:

Code: [Select]

import PhotoScan, statistics
BUFFER = 10 #percent

def cross(a, b):
result = PhotoScan.Vector([a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z, a.x*b.y - a.y *b.x])
return result.normalized()

chunk = PhotoScan.app.document.chunk
new_region = PhotoScan.Region()
xcoord = PhotoScan.Vector([10E10, -10E10])
ycoord = PhotoScan.Vector([10E10, -10E10])
avg = [[],[]]
T = chunk.transform.matrix
s = chunk.transform.matrix.scale()
crs = chunk.crs
z = PhotoScan.Vector([0,0])

for camera in chunk.cameras:
if camera.transform:
coord = crs.project(T.mulp(camera.center))
xcoord[0] = min(coord.x, xcoord[0])
xcoord[1] = max(coord.x, xcoord[1])
ycoord[0] = min(coord.y, ycoord[0])
ycoord[1] = max(coord.y, ycoord[1])
z[0] += coord.z
z[1] += 1
avg[0].append(coord.x)
avg[1].append(coord.y)
z = z[0] / z[1]
avg = PhotoScan.Vector([statistics.median(avg[0]), statistics.median(avg[1]), z])

corners = [PhotoScan.Vector([xcoord[0], ycoord[0], z]),
PhotoScan.Vector([xcoord[0], ycoord[1], z]),
PhotoScan.Vector([xcoord[1], ycoord[1], z]),
PhotoScan.Vector([xcoord[1], ycoord[0], z])]
corners = [T.inv().mulp(crs.unproject(x)) for x in list(corners)]

side1 = corners[0] - corners[1]
side2 = corners[0] - corners[-1]
side1g = T.mulp(corners[0]) - T.mulp(corners[1])
side2g = T.mulp(corners[0]) - T.mulp(corners[-1])
side3g = T.mulp(corners[0]) - T.mulp(PhotoScan.Vector([corners[0].x, corners[0].y, 0]))
new_size = ((100 + BUFFER) / 100) * PhotoScan.Vector([side2g.norm()/s, side1g.norm()/s, 3*side3g.norm() / s]) ##

xcoord, ycoord, z = T.inv().mulp(crs.unproject(PhotoScan.Vector([sum(xcoord)/2., sum(ycoord)/2., z - 2 * side3g.z]))) #
new_center = PhotoScan.Vector([xcoord, ycoord, z]) #by 4 corners

horizontal = side2
vertical = side1
normal = cross(vertical, horizontal)
horizontal = -cross(vertical, normal)
vertical = vertical.normalized()

R = PhotoScan.Matrix ([horizontal, vertical, -normal])
new_region.rot = R.t()

new_region.center = new_center
new_region.size = new_size
chunk.region = new_region
It should work for georeferenced chunk with some aligned cameras. The buffer extension (in percent) can be modified via the corresponding variable in the second line of the script.

[Dragline]

Perfect! It works just as expected. Thanks for taking the time to put that together.

[Dragline]

I made one minor modification that may be be helpful to others. On this line "z[0] += coord.z" I changed it to "z[0] += coord.z-1000" This ensures that the ground will be within the bounding box during reconstruction.

[Alexey Pasumansky]

Hello Dragline,

In principle, the ground level can be estimated by checking the coordinates of the tie points (if they are present in the project), for example, checking every 100th to speed up the procedure and then taking the median value to filter the outliers.

[Dragline]

Alexey,

I think that would probably be a better way to do this. However my programming skills are no where near that level. I'm just a humble engineer.

[pastouf]

Hi All,
I try to test this script but i dont understand how to apply this?

In fact, i want to define bounding box with 4 markers or 4 gps.
I have 20,000 photos and to save computing time and export only the area where I want to work on the point cloud. I would like to define a smallest possible calculation area for me and thus export a las file corresponding to my work area, but not the entire area.
I can work on lighter files and focus on my work area.

thank you in advance