| |
| |
|
|
| import cv2 |
| import numpy as np |
| import chumpy as ch |
|
|
| from lib.geometry import visible_boundary_edge_verts |
| from vendor.smplify.robustifiers import GMOf |
|
|
|
|
| def plucker(rays): |
| p = rays[:, 0] |
| n = rays[:, 1] - rays[:, 0] |
| n /= np.linalg.norm(n, axis=1).reshape(-1, 1) |
| m = np.cross(p, n, axisa=1, axisb=1) |
|
|
| return n, m |
|
|
|
|
| def distance_function(rays, verts): |
| n, m = plucker(rays) |
| return ch.cross(verts, n, axisa=1, axisb=1) - m |
|
|
|
|
| def unpose_and_select_rays(rays, Vi, smpl, rn_b, rn_m): |
| v_ids = visible_boundary_edge_verts(rn_b, rn_m) |
| verts = smpl.r[v_ids] |
|
|
| n, m = plucker(rays) |
| dist = np.linalg.norm(np.cross(verts.reshape(-1, 1, 3), n, axisa=2, axisb=1) - m, axis=2) |
|
|
| ray_matches = np.argmin(dist, axis=0) |
| vert_matches = np.argmin(dist, axis=1) |
|
|
| rays_u_r = np.zeros_like(rays) |
|
|
| M = Vi[:, :, v_ids] |
| T = smpl.v_posevariation[v_ids].r |
|
|
| tmp0 = M[:, :, ray_matches] * np.hstack((rays[:, 0], np.ones((rays.shape[0], 1)))).T.reshape(1, 4, -1) |
| tmp1 = M[:, :, ray_matches] * np.hstack((rays[:, 1], np.ones((rays.shape[0], 1)))).T.reshape(1, 4, -1) |
|
|
| rays_u_r[:, 0] = np.sum(tmp0, axis=1).T[:, :3] - T[ray_matches] |
| rays_u_r[:, 1] = np.sum(tmp1, axis=1).T[:, :3] - T[ray_matches] |
|
|
| rays_u_v = np.zeros_like(rays[vert_matches]) |
|
|
| tmp0 = M * np.hstack((rays[vert_matches, 0], np.ones((verts.shape[0], 1)))).T.reshape(1, 4, -1) |
| tmp1 = M * np.hstack((rays[vert_matches, 1], np.ones((verts.shape[0], 1)))).T.reshape(1, 4, -1) |
|
|
| rays_u_v[:, 0] = np.sum(tmp0, axis=1).T[:, :3] - T |
| rays_u_v[:, 1] = np.sum(tmp1, axis=1).T[:, :3] - T |
|
|
| valid_rays = dist[np.vstack((ray_matches, range(dist.shape[1]))).tolist()] < 0.12 |
| valid_verts = dist[np.vstack((range(dist.shape[0]), vert_matches)).tolist()] < 0.03 |
|
|
| ray_matches = ray_matches[valid_rays] |
|
|
| return np.concatenate((v_ids[ray_matches], v_ids[valid_verts])), \ |
| np.concatenate((rays_u_r[valid_rays], rays_u_v[valid_verts])) |
|
|
|
|
| def rays_from_points(points, camera): |
| points = np.hstack((points, np.ones((points.shape[0], 1)))) |
| points3d = camera.unproject_points(points) |
|
|
| c0 = -camera.t.r |
|
|
| return np.hstack((np.repeat(c0.reshape(1, 1, 3), points3d.shape[0], axis=0), points3d.reshape(-1, 1, 3))) |
|
|
|
|
| def rays_from_silh(mask, camera): |
|
|
| if cv2.__version__[0] == '2': |
| contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) |
| else: |
| _, contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) |
|
|
| silh = np.zeros_like(mask) |
|
|
| for con in contours: |
| cv2.drawContours(silh, [con], 0, 1, 1) |
|
|
| points = np.vstack(np.where(silh == 1)[::-1]).astype(np.float32).T |
| rays = rays_from_points(points, camera) |
|
|
| return rays |
|
|
|
|
| def ray_objective(f, sigma, base_smpl, camera, vis_rn_b, vis_rn_m): |
| base_smpl.pose[:] = f.pose |
| camera.t[:] = f.trans |
|
|
| f.v_ids, f.rays_u = unpose_and_select_rays(f.rays, f.Vi, base_smpl, vis_rn_b, vis_rn_m) |
| f.verts = base_smpl.v_shaped_personal[f.v_ids] |
| f.dist = distance_function(f.rays_u, f.verts) |
|
|
| return GMOf(f.dist, sigma) |
|
|
