Multi-view reconstruction and Meshing#

0. Import#

[1]:

%matplotlib inline

import cv2

import openalea.phenomenal.data as phm_data
import openalea.phenomenal.display as phm_display
import openalea.phenomenal.object as phm_obj
import openalea.phenomenal.multi_view_reconstruction as phm_mvr
import openalea.phenomenal.mesh as phm_mesh
import openalea.phenomenal.display.notebook as phm_display_notebook
from openalea.phenotyping_data.fetch import fetch_all_data

1. Prerequisites#

1.1 Load data#

[2]:

plant_number = 2  # Available : 1, 2, 3, 4 or 5
data_dir = fetch_all_data(f"plant_{plant_number}")

Downloading file 'plant_2/bin/side/0.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/0.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/120.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/120.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/150.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/150.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/180.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/180.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/210.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/210.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/240.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/240.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/270.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/270.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/30.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/30.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/300.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/300.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/330.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/330.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/60.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/60.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/side/90.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/side/90.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/bin/top/0.png' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/bin/top/0.png' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/calibration/calibration_camera_side.json' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/calibration/calibration_camera_side.json' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/calibration/calibration_camera_top.json' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/calibration/calibration_camera_top.json' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/voxels/16.npz' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/voxels/16.npz' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/voxels/2.npz' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/voxels/2.npz' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/voxels/4.npz' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/voxels/4.npz' to '/home/docs/.cache/phenotyping_data'.
Downloading file 'plant_2/voxels/8.npz' from 'https://raw.githubusercontent.com/openalea/phenotyping_data/main/data/plant_2/voxels/8.npz' to '/home/docs/.cache/phenotyping_data'.

[3]:

bin_images = phm_data.bin_images(data_dir)
calibrations = phm_data.calibrations(data_dir)

phm_display.show_images(
    list(bin_images["side"].values()) + list(bin_images["top"].values())
)

../_images/examples_Multi-view_reconstruction_and_Meshing_4_0.png

2. Multi-view reconstruction#

2.1 Associate images and projection function#

[4]:

def routine_select_ref_angle(bin_side_images):
    max_len = 0
    max_angle = None

    for angle in bin_side_images:
        x_pos, y_pos, x_len, y_len = cv2.boundingRect(
            cv2.findNonZero(bin_side_images[angle])
        )

        if x_len > max_len:
            max_len = x_len
            max_angle = angle

    return max_angle

[5]:

refs_angle_list = [routine_select_ref_angle(bin_images["side"])]
print(refs_angle_list)

image_views = list()
for id_camera in bin_images:
    for angle in bin_images[id_camera]:
        projection = calibrations[id_camera].get_projection(angle)

        image_ref = None
        if id_camera == "side" and angle in refs_angle_list:
            image_ref = bin_images[id_camera][angle]

        inclusive = False
        if id_camera == "top":
            inclusive = True

        image_views.append(
            phm_obj.ImageView(
                bin_images[id_camera][angle],
                projection,
                inclusive=inclusive,
                image_ref=image_ref,
            )
        )

[30]

2.2 Do multi-view reconstruction#

[6]:

voxels_size = 16  # mm
error_tolerance = 0
voxel_grid = phm_mvr.reconstruction_3d(
    image_views, voxels_size=voxels_size, error_tolerance=error_tolerance
)

2.4 Save / Load voxel grid#

[7]:

voxel_grid.write(f"plant_{plant_number}_size_{voxels_size}.npz")

[8]:

voxel_grid = phm_obj.VoxelGrid.read(f"plant_{plant_number}_size_{voxels_size}.npz")

2.5 Viewing#

[9]:

phm_display_notebook.show_voxel_grid(voxel_grid, size=1)

3.Meshing#

[10]:

vertices, faces = phm_mesh.meshing(
    voxel_grid.to_image_3d(), reduction=0.90, smoothing_iteration=5, verbose=True
)

print("Number of vertices : {nb_vertices}".format(nb_vertices=len(vertices)))
print("Number of faces : {nb_faces}".format(nb_faces=len(faces)))

================================================================================
Marching cubes :
        Iso value :0.5

        There are 10089 points.
        There are 20042 polygons.
================================================================================
================================================================================
Smoothing :
        Feature angle :120.0
        Number of iteration :5
        Pass band : 0.01

================================================================================
================================================================================
Decimation :
        Reduction (percentage) :0.9

        Before decimation
        -----------------
        There are 10089 points.
        There are 20042 polygons.

        After decimation
        -----------------
        There are 0.9 points.
        There are 10089 polygons.
================================================================================
Number of vertices : 1019
Number of faces : 2004

Viewing#

[11]:

phm_display_notebook.show_mesh(vertices, faces)