Ejemplo n.º 1
0
def test_running():
    plant_number = 1
    voxels_size = 16
    bin_images = phm_data.bin_images(plant_number=plant_number)
    calibrations = phm_data.calibrations(plant_number=plant_number)
    voxel_grid = phm_data.voxel_grid(plant_number=plant_number,
                                     voxels_size=voxels_size)

    graph = phm_seg.graph_from_voxel_grid(voxel_grid)
    voxel_skeleton = phm_seg.skeletonize(voxel_grid, graph)

    image_projection = list()
    for angle in [0, 120, 270]:
        projection = calibrations["side"].get_projection(angle)
        image_projection.append((bin_images["side"][angle], projection))

    voxel_skeleton_reduced = phm_seg.segment_reduction(voxel_skeleton,
                                                       image_projection,
                                                       required_visible=1,
                                                       nb_min_pixel=100)
Ejemplo n.º 2
0
def test_running():

    bin_images = phm_data.bin_images(plant_1_dir)
    calibrations = phm_data.calibrations(plant_1_dir)
    voxel_grid = phm_data.voxel_grid(data_dir, 1, 32)

    # Load images binarize

    graph = phm_seg.graph_from_voxel_grid(voxel_grid)

    voxel_skeleton = phm_seg.skeletonize(voxel_grid, graph)

    image_projection = list()
    for angle in [0, 120, 270]:
        projection = calibrations["side"].get_projection(angle)
        image_projection.append((bin_images["side"][angle], projection))

    voxel_skeleton = phm_seg.segment_reduction(
        voxel_skeleton, image_projection,
        required_visible=1,
        nb_min_pixel=100)
Ejemplo n.º 3
0
def test_reconstruction_3d_1():

    # Load images binarize
    bin_images = phm_data.bin_images(plant_1_dir)
    calibrations = phm_data.calibrations(plant_1_dir)

    image_views = list()
    for id_camera in bin_images:
        for angle in bin_images[id_camera]:
            projection = calibrations[id_camera].get_projection(angle)
            iv = phm_obj.ImageView(bin_images[id_camera][angle],
                                   projection,
                                   inclusive=False,
                                   image_ref=None)
            image_views.append(iv)

    voxels_size = 64
    error_tolerance = 0
    vg = phm_mvr.reconstruction_3d(image_views,
                                   voxels_size=voxels_size,
                                   error_tolerance=error_tolerance)

    assert len(vg.voxels_position) > 0
Ejemplo n.º 4
0
#!/usr/bin/env python

import sys
import pickle
import openalea.phenomenal.data as phm_data
import json
import pandas

output_files = {
    'bin_images': '/home/ubuntu/multiviewReconstruction/bin_images.pkl',
    'calibrations': '/home/ubuntu/multiviewReconstruction/calibrations.pkl'
}

plant_number = 2  # Available : 1, 2, 3, 4 or 5
bin_images = phm_data.bin_images(plant_number=plant_number)
calibrations = phm_data.calibrations(plant_number=plant_number)

with open(output_files['bin_images'], 'w') as fd:
    pickle.dump(bin_images, fd)
with open(output_files['calibrations'], 'w') as fd:
    pickle.dump(calibrations, fd)

print('{}\n{}\n{}'.format(plant_number, output_files['bin_images'],
                          output_files['calibrations']))