openalea.phenomenal.multi_view_reconstruction.multi_view_reconstruction#

Functions

`check_each`(image_views[, check])	Return a check dict for all keys in image_views according to check
`filter_voxels`(voxels, image_views[, ...])	Filter voxels, keeping the one photo_consistent with all minus error_tolerance images in image_views
`find_best_angle`(bin_side_images)
`get_bounding_box_voxel_projected`(...)	Compute the bounding box value according the radius, angle and calibration parameters of point_3d projection
`get_integrale_image`(img)
`get_voxels_corners`(voxels_position, voxels_size)	According to the voxels position and their size, return a numpy array containing for each input voxels the position of the 8 corners.
`image_error`(img_ref, img_src[, precision])	Return false position and true negative result from the comparison on two binaries images
`integral_image`(input_array)
`integral_image_hits`(boxes, image_int, width, ...)	boxes: (N, 4) array → [x_min, y_min, x_max, y_max] (float or int) returns: boolean array (N,) → True if any pixel inside box > 0
`multi_tolerant_reconstruction`(image_views[, ...])
`project_voxel_centers_on_image`(...[, value, ...])	Create a image with same shape that shape_image and project each voxel on image and write positive value (255) on it.
`project_voxels_position_on_image`(...)	Create an image with same shape that shape_image and project each voxel on image and write positive value (255) on it.
`reconstruction_3d`(image_views[, ...])	Construct a list of voxel represented object with positive value on binary image in images of images_projections.
`reconstruction_error`(voxels_grid, image_views)	Compute the reconstruction error (false positive and true negative) of the 3d reconstruction from the image view.
`reconstruction_grid`([center, grid_size, ...])	Setup a reconstruction grid :param center: coordinates of the center of the grid :param grid_size: outer edge length of the grid :param voxel_size: edge length of voxels composing the grid
`split_voxels_in_eight`(voxels)	Split each voxel in 8 en return the numpy.array position
`tolerant_reconstruction`(image_views[, ...])
`voxels_is_visible_in_image`(voxels_position, ...)	Return a numpy array containing True if the voxel are

Classes

Voxels(position, size)