The code has been moved to: https://gitlab.inria.fr/tangram/pyellcv
This repository regroups tools to manipulate ellipses and ellipsoids in the context of camera pose estimation. Most of the code is in python, but some parts were written in C++ for efficiency purposes.
This library is used in combination with 3D-aware predicted ellipses for object-based visual localization in 3D-Aware-Ellipses-for-Visual-Localization
The library can be build with the following commands:
python -m pip install 'git+https://gitlab.inria.fr/tangram/pyellcv.git'
# (add --user if you don't have permission)
# Or, to install it from a local clone:
git clone --recursive https://gitlab.inria.fr/tangram/pyellcv.git
python -m pip install -e ./pyellcv
import cv2
import numpy as np
from ellcv.types import Ellipsoid
from ellcv.utils import generate_random_scene, generate_random_camera, \
generate_K, bbox_from_ellipse
from ellcv.visu import draw_ellipse, draw_bbox
# Create a scene of ellipsoids
N = 4
scene = generate_random_scene(N, axes_range=[0.3, 1.5], position_range=[-3.0, 3.0])
# Define the camera
W, H = 640, 480
o, p = generate_random_camera(dist_range=[10.0, 15.0], target_range=[-0.5, 0.5])
K = generate_K(500, W/2, H/2)
P = K @ np.hstack((o.T, -o.T@p.reshape((3, 1))))
# Project and display
img = np.zeros((H, W, 3), dtype=np.uint8)
for ell in scene:
ellipse = ell.project(P)
bbox = bbox_from_ellipse(ellipse)
draw_bbox(img, bbox, color=(255, 0, 0))
draw_ellipse(img, ellipse, color=(0, 255, 0))
cv2.imshow("viz", img)
cv2.waitKey()- The code for p3p originally comes from RPG Monocular Pose Estimator.
- The code for ellipses Intersection-over-Union computations comes from EEOver.