invetigate registration errors
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@@ -107,7 +107,7 @@ class UV2MeshLabel():
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return self.uv_to_mesh(uv)
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def _maskFaces(V, F, mask):
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def _maskFaces(V, F, mask, return_unfixed=False):
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V_mask = mask
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F_mask = np.take(V_mask, F.reshape(-1), axis=0)
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F_mask = F_mask.reshape((-1, 3)).sum(axis=1) == 3
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@@ -117,6 +117,9 @@ def _maskFaces(V, F, mask):
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F_new = np.take(V_ind, F[F_mask, :].reshape(-1), axis=0).reshape((-1, 3))
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V_new = V[V_mask, :]
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if return_unfixed:
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return V_new, F_new, F[F_mask, :]
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else:
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return V_new, F_new
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+4
-1
@@ -260,9 +260,12 @@ def read_posed_garment(folder, id, garment, map=None, mask=None, shape=None, sha
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return verts
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def read_garment_mask(folder, id, garment):
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def read_garment_mask(folder, id, garment, return_raw=False):
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raw_mask = sio.loadmat(os.path.join(folder, id, garment + '_mask.mat'))['mask'].reshape((-1))
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if not return_raw:
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mask = raw_mask > 0
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else:
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mask = raw_mask
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return mask
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+81
-5
@@ -3,6 +3,7 @@ import sys
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import random
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import numpy as np
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import plotly.graph_objects as go
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from pymeshfix import MeshFix
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sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/..')
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from data.cloth3d_io import read_garment_mask, read_garment_template, read_posed_garment_frame, loadInfo, read_posed_body_frame, read_posed_body, read_posed_garment, read_curvatures, read_curvature_frame, writeOBJ
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@@ -51,7 +52,7 @@ def build_lookup_table(repeated):
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lookup[repeated[i][j]] = [repeated[i][k] for k in range(len(repeated[i]))] # if k != j
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return lookup
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def mask_faces(all_faces, mask, repeated, verts):
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def mask_faces(all_faces, mask, raw_mask, repeated, verts):
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# if any of the vertices of a face is masked, mask the face
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lookup = build_lookup_table(repeated)
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faces = []
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@@ -79,6 +80,30 @@ def mask_faces(all_faces, mask, repeated, verts):
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if mask[v1[i]] and mask[v2[j]] and mask[v3[k]]:
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# if the euclidean distance between any two of the vertices of the face is less than 0.05 then append the face
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# if np.linalg.norm(verts[v1[i]] - verts[v2[j]]) < 0.05 and np.linalg.norm(verts[v1[i]] - verts[v3[k]]) < 0.05 and np.linalg.norm(verts[v2[j]] - verts[v3[k]]) < 0.05:
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#only add the face if this face originally existed among the faces of the garment
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# if not np.any([np.array([v1[i], v2[j], v3[k]], dtype=np.int32) == face for face in all_faces]):
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# continue
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# if all vertices of the face have a value of 2 in the raw mask then don't add the face
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# if np.all(raw_mask[[v1[i], v2[j], v3[k]]] == 2):
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# continue
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# skip face if it's area is more than 0.001 and at least one of the vertices has value of 2 in the raw mask
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# if np.linalg.norm(np.cross(verts[v1[i]] - verts[v2[j]], verts[v1[i]] - verts[v3[k]])) > 0.001 and np.any(raw_mask[[v1[i], v2[j], v3[k]]] == 2):
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# continue
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# if np.linalg.norm(np.cross(verts[v1[i]] - verts[v2[j]], verts[v1[i]] - verts[v3[k]])) > 0.001:
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# continue
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# if any edge of the face is longer than 0.1 and both vertices of the edge have a value of 2 in the raw mask then skip the face
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# if np.linalg.norm(verts[v1[i]] - verts[v2[j]]) > 0.05 and (raw_mask[v1[i]] == 2 or raw_mask[v2[j]] == 2):
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# continue
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# if np.linalg.norm(verts[v1[i]] - verts[v3[k]]) > 0.05 and (raw_mask[v1[i]] == 2 or raw_mask[v3[k]] == 2):
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# continue
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# if np.linalg.norm(verts[v2[j]] - verts[v3[k]]) > 0.05 and (raw_mask[v2[j]] == 2 or raw_mask[v3[k]] == 2):
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# continue
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faces.append(np.array([v1[i], v2[j], v3[k]], dtype=np.int32))
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assert np.all(verts[face] == verts[faces[-1]])
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found_replacement = True
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@@ -100,22 +125,38 @@ def check(folder, frame):
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id, frame_nr, garment = frame.split()
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frame_nr = int(frame_nr)
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info = loadInfo(os.path.join(folder, id, 'info.mat'))
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mask = read_garment_mask(folder, id, garment)
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raw_mask = read_garment_mask(folder, id, garment, return_raw=True)
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mask = raw_mask > 0
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mesh_posed = read_posed_garment_frame(folder, id, garment, frame_nr, mask=mask, shape=info['shape'], pose=info['poses'][:,frame_nr], deorient=use_no_orient, unshape=no_shape)
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v = mesh_posed[mask,:]
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is_skirt = (garment == 'Dress' or garment == 'Skirt')
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skirt_mod = '_skirt' if is_skirt else ''
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F = np.load(f'custom_utils/smpl_faces{skirt_mod}.npy').astype(np.int32)
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_, faces = _maskFaces(np.zeros((14475,3)), F, mask)
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_, faces, unfixed = _maskFaces(np.zeros((14475,3)), F, mask, True)
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meshfix = MeshFix(v, faces)
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holes = meshfix.extract_holes()
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# plot(v, faces)
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unq, idx, count = np.unique(mesh_posed, axis=0, return_counts=True, return_index=True)
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repeated_groups = unq[count > 1]
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new_border = []
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for border in np.array(holes.points):
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# find the index of the vertex in the original mesh
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ind = np.argwhere(np.all(mesh_posed == border, axis=1))
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new_border.extend(ind.ravel())
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raw_mask[new_border] = 2
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mask_2 = np.zeros((14475), dtype=bool)
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mask_2_raw = np.zeros((14475), dtype=np.uint8)
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mask_2[idx] = True
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mask_2_raw = mask_2.astype(np.uint8)
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mask_3 = np.zeros((14475), dtype=bool)
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mask_3[mask_2] = raw_mask[mask_2] == 2
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mask_2_raw[mask_3] = 2
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v_2 = mesh_posed[mask_2,:]
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_, faces_2 = _maskFaces(np.zeros((14475,3)), F, mask_2)
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# plot(v_2, faces_2)
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@@ -127,11 +168,46 @@ def check(folder, frame):
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repeated_idx = np.argwhere(np.all(mesh_posed == repeated_group, axis=1))
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repeated.append(repeated_idx.ravel())
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faces_3 = mask_faces(F, mask_2, repeated, mesh_posed)
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writeOBJ('temp/investigate_3.obj', v_2, faces_3)
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# # if a vertex from v_2 is not part of v then set the corresponding value in mask_0 to 0
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# mask_0 = np.zeros((v_2.shape[0]), dtype=bool)
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# for i, _v in enumerate(v_2):
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# if not np.any([np.all(_v == _w) for _w in v]):
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# mask_0[i] = True
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# mask_0_0 = np.zeros((14475), dtype=bool)
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# mask_0_0[mask_2] = 1 - mask_0
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# mask_4 = np.logical_not(mask_0)
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faces_3 = mask_faces(F, mask_2, mask_2_raw, repeated, mesh_posed)
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# writeOBJ('temp/investigate_3.obj', v_2, faces_3)
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plot(v_2, faces_3)
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# plot repeated
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r = []
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for rr in repeated:
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r.extend(rr)
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x = mesh_posed
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y = mesh_posed[r,:]
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go.Figure(data = [go.Scatter3d(x=x[:, 0], y=x[:, 1], z=x[:, 2], marker=dict(size=3, line=dict(width=0),), mode='markers'),
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go.Scatter3d(x=y[:, 0], y=y[:, 1], z=y[:, 2], marker=dict(size=5, line=dict(width=0),), mode='markers'),
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]).show()
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# unq, idx, count = np.unique(v, axis=0, return_counts=True, return_index=True)
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# repeated_groups = unq[count > 1]
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# repeated = []
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# for repeated_group in repeated_groups:
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# repeated_idx = np.argwhere(np.all(v == repeated_group, axis=1))
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# repeated.append(repeated_idx.ravel())
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# mask_3 = np.zeros((v.shape[0]), dtype=bool)
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# mask_3[idx] = True
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# faces_4 = mask_faces(faces.astype(np.int64), mask_3, mask_2_raw, repeated, v)
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# plot(v[mask_3,:], faces_4)
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pass
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