def test_maize():
plant_number = 3
voxels_size = 4
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)
vms = phm_seg.maize_segmentation(voxel_skeleton, graph)
vmsi = phm_seg.maize_analysis(vms)
def test_maize():
voxel_grid = phm_data.random_voxel_grid(voxels_size=32)
graph = phm_seg.graph_from_voxel_grid(voxel_grid)
voxel_skeleton = phm_seg.skeletonize(voxel_grid, graph)
vms = phm_seg.maize_segmentation(voxel_skeleton, graph)
vmsi = phm_seg.maize_analysis(vms)
# Write
filename = 'tmp.json'
vms.write_to_json_gz(filename)
vms = phm_obj.VoxelSegmentation.read_from_json_gz(filename)
os.remove(filename)
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)
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)
def segmentation(row):
bin_images = dc.get_bin_images(row)
calibrations = dc.get_calibrations(row)
refs_angle_list = [_routine_select_ref_angle(bin_images["side"])]
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))
# ### 2.2 Do multi-view reconstruction
voxels_size = 16 # mm
error_tolerance = 0
voxel_grid = phm_mvr.reconstruction_3d(image_views,
voxels_size=voxels_size,
error_tolerance=error_tolerance)
#phm_display_notebook.show_voxel_grid(voxel_grid, size=1)
# ## 4. Skeletonization
#
# ### 4.1 Compute Graph and the skeleton
# Compute the skeleton of the plant voxelgrid
# In[12]:
graph = phm_seg.graph_from_voxel_grid(voxel_grid, connect_all_point=True)
voxel_skeleton = phm_seg.skeletonize(voxel_grid, graph)
# ### 2.3 Clean skeleton (filter small elements)
# In[14]:
# Select images
image_projection = list()
for angle in bin_images["side"]:
projection = calibrations["side"].get_projection(angle)
image_projection.append((bin_images["side"][angle], projection))
voxel_skeleton_denoised = phm_seg.segment_reduction(voxel_skeleton,
image_projection,
required_visible=5,
nb_min_pixel=400)
#phm_display_notebook.show_skeleton(voxel_skeleton_denoised, size=1)
# ## 5. Maize Segmentation
#
# ### 5.1 Process
#
# Voxel skeleton are segmented in several label "stem", "mature_leaf", "growing_leaf" and "unknow"
# In[16]:
vms = phm_seg.maize_segmentation(voxel_skeleton_denoised, graph)
vmsi = phm_seg.maize_analysis(vms)
return vmsi
#!/usr/bin/env python import sys import openalea.phenomenal.display as phm_display import openalea.phenomenal.mesh as phm_mesh import openalea.phenomenal.object as phm_obj import openalea.phenomenal.segmentation as phm_seg from funcs import * voxel_grid = phm_obj.VoxelGrid.read(sys.argv[1]) graph = phm_seg.graph_from_voxel_grid(voxel_grid, connect_all_point=True) voxel_skeleton = phm_seg.skeletonize(voxel_grid, graph)