progress save

data/cloth3d_io.py

@@ -233,22 +233,46 @@ def read_posed_garment_frame(folder, id, garment, frame, map, mask=None, shape=N
         verts[mask, :] = verts[mask, :] - np.squeeze(shape_offsets)[mask, :]
 
     if deorient:
-        R = scipy.spatial.transform.Rotation.from_euler(pose[:3])
+        R = scipy.spatial.transform.Rotation.from_euler(pose[:3]).inv()
         # R = scipy.spatial.transform.Rotation.from_euler([0,0,-zrot])
         verts = R.apply(verts)
 
     return verts
 
 
+# can i cache map?
+def read_posed_garment(folder, id, garment, map=None, mask=None, shape=None, shapedirs=None, poses=None, unshape=False, deorient=False):
+    pc16_path = os.path.join(folder, id, garment + '.pc16')
+    verts = readPC2(pc16_path, True)
+
+    if map is None:
+        map = sio.loadmat(os.path.join(folder, id, garment + '_map.mat'))['map'].reshape((-1))
+    verts = verts[:, map, :]
+
+    if unshape:
+        shape_offsets = np.tensordot(shape, shapedirs, axes=[[1], [2]])
+        verts[:, mask, :] = verts[:, mask, :] - np.squeeze(shape_offsets)[None, mask, :]
+
+    if deorient:
+        for i in range(verts.shape[0]):
+            R = scipy.spatial.transform.Rotation.from_euler(poses[:3, i]).inv()
+            # R = scipy.spatial.transform.Rotation.from_euler([0,0,-zrot])
+            verts[i] = R.apply(verts[i])
+
+    return verts
+
+
 def read_garment_mask(folder, id, garment):
     raw_mask = sio.loadmat(os.path.join(folder, id, garment + '_mask.mat'))['mask'].reshape((-1))
     mask = raw_mask > 0
     return mask
 
 
-def read_garment_template(folder, id, garment, mask):
+def read_garment_template(folder, id, garment, mask=None):
     offsets_static = sio.loadmat(os.path.join(folder, id, garment + '_offsets_static.mat'))['label'][:,:3]
     body_static = sio.loadmat(os.path.join(folder, id, 'info_body.mat'))['B']
+    if mask is None:
+        mask = read_garment_mask(folder, id, garment)
     verts_static = (body_static + offsets_static) * mask[:, np.newaxis]
     return verts_static
 
@@ -258,12 +282,25 @@ def read_posed_body_frame(folder, id, frame, pose=None, deorient=False):
     verts = readPC2Frame(pc16_path, frame, True)
 
     if deorient:
-        R = scipy.spatial.transform.Rotation.from_euler(pose[:3])
+        R = scipy.spatial.transform.Rotation.from_euler(pose[:3]).inv()
         # R = scipy.spatial.transform.Rotation.from_euler([0,0,-zrot])
         verts = R.apply(verts)
         
     return verts
 
+
+def read_posed_body(folder, id, poses=None, deorient=False):
+    pc16_path = os.path.join(folder, id, 'Body_posed.pc16')
+    verts = readPC2(pc16_path, True)
+
+    if deorient:
+        for i in range(verts.shape[0]):
+            R = scipy.spatial.transform.Rotation.from_euler(poses[:3, i]).inv()
+            # R = scipy.spatial.transform.Rotation.from_euler([0,0,-zrot])
+            verts[i] = R.apply(verts[i])
+        
+    return verts
+
 # import os
 # import sys
 # import numpy as np

data/convert_to_uv.py

@@ -0,0 +1,486 @@
+import os
+import sys
+import glob
+import tqdm
+import math
+import time
+import random
+import shutil
+import collections
+import argparse
+import pickle
+import numpy as np
+import scipy as sp
+import trimesh as tm
+import cmapy as cm
+import scipy.io as sio
+import scipy.interpolate as spi
+import matplotlib.pyplot as plt
+import scipy.stats as stat
+import cv2
+import plotly.express as ex
+import plotly.graph_objects as go
+
+sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/..')
+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
+
+
+os.environ["CUDA_VISIBLE_DEVICES"] = "6"
+
+def convert_to_uv(res, m2uv, uv_map, verts, neighbours=10, mask=None, method='rbf', garment_uv_mask=None):
+    verts_uv = np.zeros((res * 2, res, 3))
+    uv_values = np.zeros((uv_map.shape[0], 3))
+    uv_values[m2uv[:, 0]] = verts
+    uv_values[m2uv[:, 1]] += verts
+    uv_values = uv_values[uv_map_mask, :] #   add garment mask
+    uv_values /= uv_counter[:, np.newaxis]
+    return_garment_uv_mask = False
+
+    if mask is not None:
+        garment_mask = np.zeros((uv_map.shape[0]), dtype=bool)
+        garment_mask[m2uv[:, 0]] = mask
+        garment_mask[m2uv[:, 1]] += mask
+        garment_mask = garment_mask[uv_map_mask] #   add garment mask
+    else:
+        garment_mask = np.sum(uv_values, axis=-1) != 0
+
+    # test
+    verts_uv[uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1], :] = uv_values
+    # verts_uv_save = verts_uv.copy()
+
+    # garment_mask = np.sum(uv_values, axis=-1) != 0
+    unique_uv_values = uv_values[garment_mask, :]
+    uv_map_discreet_unique_unique = uv_map_discreet_unique[garment_mask, :]
+    rbf_dest_current = rbf_dest
+
+    if garment_uv_mask is None and mask is not None:
+        garment_uv_mask = np.zeros((res * 2, res))
+        garment_uv_mask[uv_map_discreet_unique_unique[:, 0], uv_map_discreet_unique_unique[:, 1]] = 255
+        garment_uv_mask = cv2.morphologyEx(garment_uv_mask, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_RECT, (4 * 2 + 1, 4 * 2 + 1), (4, 4)), iterations=4)
+        garment_uv_mask_border = garment_uv_mask.astype(bool)
+        garment_uv_mask = cv2.dilate(garment_uv_mask, cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=2).astype(bool)
+        garment_uv_mask_border = ~garment_uv_mask_border & garment_uv_mask
+        garment_uv_mask = garment_uv_mask * uv_mask[:,:,0]
+        rbf_dest_current = rbf_dest * garment_uv_mask
+        return_garment_uv_mask = True
+
+
+    rbf_dest_current = np.nonzero(rbf_dest_current)
+    rbf_dest_current = np.array(rbf_dest_current).T
+
+    # uv_verts_uniq = np.array(np.nonzero(np.sum(verts_uv, axis=-1))).T
+    if method == 'rbf':
+        interpolator =  spi.RBFInterpolator(y=uv_map_discreet_unique_unique, d=unique_uv_values, neighbors=neighbours, kernel='linear')
+    elif method == 'nearest':
+        interpolator =  spi.NearestNDInterpolator(x=uv_map_discreet_unique_unique, y=unique_uv_values)
+    else:
+        raise NotImplementedError
+
+    final = interpolator(rbf_dest_current)
+
+    result = np.zeros((res * 2, res, 3))
+
+    # not sure, shouldn't be needed
+    # rbf_dest[:, [0,1]] = rbf_dest[:, [1, 0]]
+
+    result[rbf_dest_current[:, 0], rbf_dest_current[:, 1], :] = final
+    result[uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1], :] = uv_values
+    if garment_uv_mask is not None:
+        result = result * garment_uv_mask[:,:,np.newaxis]
+
+    if return_garment_uv_mask:
+        return result, garment_uv_mask, garment_uv_mask_border
+    else:
+        return result 
+
+
+def convert_to_uv_batch(res, m2uv, uv_map, verts, neighbours=15, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=None, id=None):
+    batch = len(verts)
+
+    assert method == 'rbf'
+
+    assert mask is not None
+    garment_mask = np.zeros((uv_map.shape[0]), dtype=bool)
+    garment_mask[m2uv[:, 0]] = mask
+    garment_mask[m2uv[:, 1]] += mask
+    garment_mask = garment_mask[uv_map_mask] #   add garment mask
+
+    rbf_dest_current = rbf_dest
+
+    # add back mesh vertices that are not part of the garment
+    uv_map_discreet_unique_unique_inv = uv_map_discreet_unique[np.invert(garment_mask), :]
+    rbf_dest_fill = np.zeros((res * 2, res), dtype=bool)
+    rbf_dest_fill[uv_map_discreet_unique_unique_inv[:, 0], uv_map_discreet_unique_unique_inv[:, 1]] = True
+
+    assert not (garment_uv_mask is None and mask is not None)
+    assert garment_uv_mask is not None
+    rbf_dest_current = (rbf_dest + rbf_dest_fill) * garment_uv_mask + garment_uv_mask_border
+
+    rbf_dest_current = np.nonzero(rbf_dest_current)
+    rbf_dest_current = np.array(rbf_dest_current).T
+
+    for i in range(batch):
+        print('processing frame: ' + str(i))
+
+        uv_values = np.zeros((uv_map.shape[0], 3))
+        uv_values[m2uv[:, 0]] = verts[i]
+        uv_values[m2uv[:, 1]] += verts[i]
+        uv_values = uv_values[uv_map_mask, :]
+        uv_values /= uv_counter[:, np.newaxis]
+
+        unique_uv_values = uv_values[garment_mask, :]
+        uv_map_discreet_unique_unique = uv_map_discreet_unique[garment_mask, :]
+
+        interpolator =  spi.RBFInterpolator(y=uv_map_discreet_unique_unique, d=unique_uv_values[:,:], neighbors=neighbours, kernel='linear')
+        result = np.zeros((res * 2, res, 3), np.float32)
+        result[rbf_dest_current[:, 0], rbf_dest_current[:, 1], :] = interpolator(rbf_dest_current)
+        result[uv_map_discreet_unique_unique[:, 0], uv_map_discreet_unique_unique[:, 1], :] = unique_uv_values[:,:]
+
+        if garment_uv_mask is not None:
+            result *= garment_uv_mask[:,:,np.newaxis]
+            
+        np.savez_compressed(os.path.join(folder, 'uv_posed_no_orient', id + '_' + str(i) + '.npz'), uv_posed_no_orient=result)
+
+
+def convert_to_uv_batch_label(res, m2uv, uv_map, values, neighbours=15, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=None):
+    batch = values.shape[0]
+    values = (values + 1) * mask
+    values_uv = np.zeros((batch, res * 2, res))
+    missing = np.zeros((res * 2, res))
+    uv_values = np.zeros((batch, uv_map.shape[0]))
+    uv_values[:, m2uv[:, 0]] = values
+    uv_values[:, m2uv[:, 1]] = values
+    uv_values = uv_values[:, uv_map_mask]
+    return_garment_uv_mask = False
+
+    if mask is not None:
+        garment_mask = np.zeros((uv_map.shape[0]), dtype=bool)
+        garment_mask[m2uv[:, 0]] = mask
+        garment_mask[m2uv[:, 1]] += mask
+        garment_mask = garment_mask[uv_map_mask] #   add garment mask
+    else:
+        raise Exception
+
+
+    # test 
+    values_uv[:, uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1]] = uv_values
+    missing[uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1]] = (uv_values[0,:] == 0)
+    
+    unique_uv_values = uv_values[:, garment_mask]
+    uv_map_discreet_unique_unique = uv_map_discreet_unique[garment_mask, :]
+    # rbf_dest_current = rbf_dest.astype(bool) + garment_uv_mask_border * uv_mask[:,:,0]
+
+    if garment_uv_mask is None and mask is not None:
+        garment_uv_mask = np.zeros((res * 2, res))
+        garment_uv_mask[uv_map_discreet_unique_unique[:, 0], uv_map_discreet_unique_unique[:, 1]] = 255
+        garment_uv_mask = cv2.morphologyEx(garment_uv_mask, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=4)
+        garment_uv_mask = cv2.dilate(garment_uv_mask, cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=2).astype(bool)
+        return_garment_uv_mask = True
+
+    rbf_dest_current = rbf_dest * garment_uv_mask + missing * garment_uv_mask
+    rbf_dest_current = np.nonzero(rbf_dest_current)
+    rbf_dest_current = np.array(rbf_dest_current).T
+
+    # uv_verts_uniq = np.array(np.nonzero(np.sum(verts_uv, axis=-1))).T
+    final = []
+    for i in range(batch):
+        print('processing frame: ' + str(i))
+        interpolator =  spi.NearestNDInterpolator(x=uv_map_discreet_unique_unique, y=unique_uv_values[i,:])
+        final.append(interpolator(rbf_dest_current))
+    final = np.asarray(final)
+
+    result = np.zeros((batch, res * 2, res))
+    result[:, uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1]] = uv_values
+    result[:, rbf_dest_current[:, 0], rbf_dest_current[:, 1]] = final
+    if garment_uv_mask is not None:
+        result = result * garment_uv_mask[np.newaxis,:,:]
+
+    if return_garment_uv_mask:
+        return result, garment_uv_mask
+    else:
+        return result 
+
+
+def m2uv_array(m2uv):
+    result = np.zeros((14475, 2), dtype=np.int32)
+    for k, v in m2uv.items():
+        if len(v) == 2:
+            result[k] = list(v)
+        elif len(v) == 1:
+            x = v.pop()
+            result[k] = [x, x]
+        else:
+            assert False
+
+    return result
+
+
+def uv_to_mesh(uv, m2uv):
+    res = uv.shape[0]
+    mesh = np.zeros((14475, 3))
+    uv_pixels = uv_map_discreet[m2uv]
+    # counter = np.ones((14475))
+    # counter[m2uv[:, 0] == m2uv[:, 1]] = 2
+    mesh = np.mean(uv[uv_pixels[:, :, 0], uv_pixels[:, :, 1], :], axis=1) # / counter[:, np.newaxis]
+    return mesh
+    pass
+
+
+def verify_reconstruction(orig, reconstructed):
+    error = np.sqrt(np.sum((orig - reconstructed) ** 2, axis=-1))
+    colors = np.array([cm.color('jet', 1 - i) for i in error])
+    error_sum = np.sum(error)
+
+
+    verts_uv = np.zeros((uv_res * 2, uv_res, 3))
+    uv_values = np.zeros((uv_map.shape[0], 3))
+    uv_values[m2uv[:, 0]] = colors
+    uv_values[m2uv[:, 1]] += colors
+    uv_counter = np.zeros((uv_map.shape[0]))
+    uv_counter[m2uv[:, 0]] = 1
+    uv_counter[m2uv[:, 1]] += 1
+    uv_values /= uv_counter[:, np.newaxis]
+    verts_uv[uv_map_discreet[:, 0], uv_map_discreet[:, 1], :] = uv_values
+    fig = plt.figure(figsize=(15, 15))
+    ax = fig.add_subplot(111)
+    ax.scatter(uv_map[:, 0], uv_map[:, 1], s=5, c=uv_values/255)
+    plt.show()
+
+
+
+    fig = plt.figure(figsize=(15, 15))
+    ax = fig.add_subplot(121, projection='3d')
+    x = orig
+    ax.set_xlim3d(-1, 1)
+    ax.set_ylim3d(-1, 1)
+    ax.set_zlim3d(-1, 1)
+    ax.set_xlabel("X")
+    ax.set_ylabel("Y")
+    ax.set_zlabel("Z")
+    ax.scatter(x[:, 0], x[:, 1], x[:, 2], s=5)
+
+    ax = fig.add_subplot(122, projection='3d')
+    x = reconstructed#[error > 0.1, :]
+    ax.set_xlim3d(-1, 1)
+    ax.set_ylim3d(-1, 1)
+    ax.set_zlim3d(-1, 1)
+    ax.set_xlabel("X")
+    ax.set_ylabel("Y")
+    ax.set_zlabel("Z")
+    ax.scatter(x[:, 0], x[:, 1], x[:, 2], s=5, c=colors/255) #[error > 0.1, :]
+
+    plt.show()
+
+    pass
+
+# https://stackoverflow.com/questions/38187286/find-unique-pairs-in-list-of-pairs
+def unique_pairs(a):
+    a.sort(axis=1)
+    b = np.ascontiguousarray(a).view(
+        np.dtype((np.void, a.dtype.itemsize * a.shape[1]))
+    )
+    _, inv, ct = np.unique(b, return_inverse=True, return_counts=True)
+    return ct[inv] == 1
+
+
+def unique_uv_map_mask(uv_map_discreet):
+    mask = np.zeros((uv_map_discreet.shape[0]), dtype=bool)
+    temp = np.zeros((uv_res * 2, uv_res))
+    for p in uv_map_discreet:
+        temp[p[0], p[1]] += 1
+    # temp = temp == 1
+    for i, p in enumerate(uv_map_discreet):
+        if temp[p[0], p[1]] == 1:
+            mask[i] = True
+        elif temp[p[0], p[1]] == 2:
+            mask[i] = True
+            temp[p[0], p[1]] = 0
+    return mask
+
+
+def test(verts, faces, values):
+    uv_values = np.zeros((uv_map.shape[0], 3))
+    uv_values[m2uv[:, 0]] = values
+    uv_values[m2uv[:, 1]] += values
+    uv_counter = np.zeros((uv_map.shape[0]))
+    uv_counter[m2uv[:, 0]] = 1
+    uv_counter[m2uv[:, 1]] += 1
+    uv_values /= uv_counter[:, np.newaxis]
+    x = uv_values
+    verts = np.concatenate((verts, np.zeros((15068, 1))), axis=-1)
+    im = ((x - x.min()) / (x.max() - x.min())) * 255
+    tm.Trimesh(verts, faces, vertex_colors=im.astype(np.int32)).show()
+
+
+def get_shapedirs():
+    to_keep = sio.loadmat(os.path.join('custom_utils/keep_remove.mat'))['keep'].reshape(-1)
+    shapedirs = []
+    with open(os.path.join('custom_utils/super_model_f.pkl'), 'rb') as f:
+        female = pickle.load(f, encoding="latin1")
+        shapedirs.append(female['shapedirs'][to_keep, :])
+    with open(os.path.join('custom_utils/super_model_m.pkl'), 'rb') as f:
+        male = pickle.load(f, encoding="latin1")
+        shapedirs.append(male['shapedirs'][to_keep, :])
+    return shapedirs
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-f", "--folder", help = "end of range", default='/home/workspace/data/dataset/test_skirt_ready_2')
+    parser.add_argument("-s", "--start", help = "start of range", default=0)
+    parser.add_argument("-e", "--end", help = "end of range", default=30000)
+    parser.add_argument("-n", "--name", help = "end of range", default='lhunor')
+    parser.add_argument("-sk", "--skirt", help = "end of range", default=1)
+    args = parser.parse_args()
+
+    # smpl = SMPL('FeatureLines/superSMPL')
+
+    folder = args.folder 
+
+    print("skirt" if args.skirt == 1 else "not skirt")
+
+    F = np.load("custom_utils/smpl_faces" + ("_skirt" if args.skirt == 1 else "") + ".npy")
+    uv_map = np.load('custom_utils/stretched_uv_map_' + ("skirt" if args.skirt == 1 else "3") + '.npy')
+    m2uv = np.load('custom_utils/m2uv' + ("_skirt" if args.skirt == 1 else "") + '.npy', allow_pickle=True).item()
+    m2uv = m2uv_array(m2uv)
+    uv_mask = np.load('custom_utils/mask_256x512' + ("_skirt" if args.skirt == 1 else "") + '.npy')
+    curvature_label_type = '6_25 '
+
+    uv_res = 256
+    uv_mask = (cv2.resize(uv_mask * 255.0, (uv_res, uv_res * 2)) / 255).astype(bool)[:, :, np.newaxis]
+    # uv_mask_dilate = cv2.erode(uv_mask.astype(np.float32), cv2.getStructuringElement(cv2.MORPH_CROSS, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=1).astype(bool)[:, :, np.newaxis]
+    # uv_mask_border = uv_mask * np.invert(uv_mask_dilate)
+    uv_mask = cv2.dilate(uv_mask.astype(np.float32), cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=2).astype(bool)[:, :, np.newaxis]
+
+    uv_map_discreet = np.floor(uv_map * uv_res).astype(np.int32)
+    uv_map_mask = unique_uv_map_mask(uv_map_discreet)
+
+    uv_counter = np.zeros((uv_map.shape[0]))
+    uv_counter[m2uv[:, 0]] = 1
+    uv_counter[m2uv[:, 1]] += 1
+    uv_counter = uv_counter[uv_map_mask]
+
+    uv_map_discreet_unique = uv_map_discreet[uv_map_mask, :]
+
+    rbf_dest = np.ones((uv_res * 2, uv_res))
+    rbf_dest[uv_map_discreet_unique[:, 0], uv_map_discreet_unique[:, 1]] = 0
+    rbf_dest[np.invert(uv_mask[:,:,0])] = 0
+
+    is_skirt = True if args.skirt == 1 else False
+    skirt_modifier = '_skirt' if is_skirt else ''
+
+    folder = args.folder
+    frames_file = 'frames_all.txt'
+
+    frames = []
+    with open(os.path.join(folder, frames_file), 'r') as f:
+        lines = f.readlines()
+        lines = [line.strip() for line in lines]
+    frames = lines#[int(args.start):int(args.end)]
+    ids = [frame.split('_')[0] for frame in frames]
+
+    print(f'params: -f {args.folder} -s {args.start} -e {args.end} -n {args.name} -skirt {args.skirt}')
+
+    # ids = os.listdir(os.path.join(local_folder, 'pose_shape'))
+    # ids = [id.split('_')[0] for id in ids]
+    ids = sorted(list(set(ids)))[int(args.start):int(args.end)]
+
+    shapedirs = get_shapedirs()
+
+    use_no_orient = True
+    data_to_convert = ['mesh_posed']
+
+    for id in tqdm.tqdm(ids):
+
+        info = loadInfo(os.path.join(folder, id, 'info.mat'))
+        garments = info['outfit']
+        assert info['poses'].shape[1] <= 300
+
+        mask = read_garment_mask(folder, id, garment)
+        verts_static = read_garment_template(folder, id, garment, mask)
+        body = read_posed_body(folder, id, info['poses'], use_no_orient)
+        gt = read_posed_garment(folder, id, garment, mask=mask, shape=info['shape'])
+        # gt = readPC2(os.path.join(folder, id, garment + '_registered.pc16'),  True)['V']
+        curvature = np.stack([np.load(os.path.join(folder, f'mesh_curvature_{neighbourhood}_2',  f'{id}_{i}.npz'))['mesh_curvature'] for i in range(frames_len)])
+        # mesh_unposed = [np.load(os.path.join(folder, id, 'mesh_unposed',  id + '_' + str(i) + '.npz')) for i in range(gt.shape[0])]
+        # mesh_unposed = np.stack([mesh_unposed[i]['mesh_unposed'] for i in range(gt.shape[0])])
+        # mesh_unposed_no_shape = [np.load(os.path.join(folder, id, 'mesh_unposed_no_shape',  id + '_' + str(i) + '.npz')) for i in range(gt.shape[0])]
+        # mesh_unposed_no_shape = np.stack([mesh_unposed_no_shape[i]['mesh_unposed_no_shape'] for i in range(gt.shape[0])])
+        # body_no_orient = [np.load(os.path.join(folder, id, 'mesh_posed_body_no_orient',  id + '_' + str(i) + '.npz')) for i in range(gt.shape[0])]
+        # body_no_orient = np.stack([body_no_orient[i]['mesh_posed_body_no_orient'] for i in range(gt.shape[0])])
+        # mesh_unposed_no_shape_one_hot = [np.load(os.path.join(local_folder, 'mesh_unposed_no_shape_one_hot',  id + '_' + str(i) + '.npz')) for i in range(frames)]
+        # mesh_unposed_no_shape_one_hot = [mesh_unposed_no_shape_one_hot[i]['mesh_unposed_no_shape'] for i in range(frames)]
+        # mesh_posed_no_orient = [np.load(os.path.join(local_folder, 'mesh_posed_no_orient',  id + '_' + str(i) + '.npz')) for i in range(frames)]
+        # mesh_posed_no_orient = [mesh_posed_no_orient[i]['mesh_posed_no_orient'] for i in range(frames)]
+
+
+        # verts_dynamic = gt
+
+        # TODO: check if have to mask out non garment vertices or not? are they the same vertices erpeated many times? if remove, have to interpolate from almost nothing?
+
+        # test(data.f.Vt, data.f.Ft, verts)
+        # test(uv_map, data.f.Ft, verts)
+
+        start = time.perf_counter()
+
+
+
+        uv_verts_static, garment_uv_mask, garment_uv_mask_border = convert_to_uv(uv_res, m2uv, uv_map, verts_static, neighbours=3, mask=mask, method='rbf', garment_uv_mask=None)
+        uv_verts_static = uv_verts_static.astype(np.float32)
+        # uv_body_static = convert_to_uv(uv_res, m2uv, uv_map, body_static, neighbours=3, mask=None, method='rbf', garment_uv_mask=None).astype(np.float32)
+        # uv_body = convert_to_uv_batch(uv_res, m2uv, uv_map, body[:, :, :], neighbours=3, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
+        # uv_posed_body_no_orient = convert_to_uv_batch(uv_res, m2uv, uv_map, body_no_orient[:, :, :], neighbours=3, mask=None, method='rbf', garment_uv_mask=None, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
+        # uv_gt = convert_to_uv_batch(uv_res, m2uv, uv_map, gt[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
+        uv_curvature = convert_to_uv_batch_label(uv_res, m2uv, uv_map, curvature[:, :], neighbours=3, mask=mask, method='nearest', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
+        # uv_unposed = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_unposed[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
+        # uv_unposed_no_shape = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_unposed_no_shape[:, :, :], neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border).astype(np.float32)
+        # uv_unposed_no_shape_one_hot = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_unposed_no_shape_one_hot, neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border, id=id)
+        # uv_posed_no_orient = convert_to_uv_batch(uv_res, m2uv, uv_map, mesh_posed_no_orient, neighbours=3, mask=mask, method='rbf', garment_uv_mask=garment_uv_mask, garment_uv_mask_border=garment_uv_mask_border, id=id)
+        # uv_shaped_body = convert_to_uv(uv_res, m2uv, uv_map, shaped_body, neighbours=3, mask=None, method='rbf', garment_uv_mask=None).astype(np.float32)
+        print(time.perf_counter() - start)
+
+        # start = time.perf_counter()
+        # np.save(os.path.join(folder, id, garment + '_offsets_static_uv.npy'), uv_verts_static)
+        # np.save(os.path.join(folder, id, 'body_static_uv.npy'), uv_body_static)
+        # np.save(os.path.join(folder, id, 'mask_uv.npy'), garment_uv_mask)
+
+        # os.makedirs(os.path.join(folder, id, 'body_posed_uv'), exist_ok=True)
+        # for i in range(uv_body.shape[0]):
+        #     np.savez_compressed(os.path.join(folder, id, 'body_posed_uv', garment + '_' + str(i) + '.npz'), uv_body=uv_body[i, :, :, :])
+        
+        # os.makedirs(os.path.join(folder, id, 'uv_posed_body_no_orient'), exist_ok=True)
+        # for i in range(uv_posed_body_no_orient.shape[0]):
+        #     np.savez_compressed(os.path.join(folder, id, 'uv_posed_body_no_orient', garment + '_' + str(i) + '.npz'), uv_posed_body_no_orient=uv_posed_body_no_orient[i, :, :, :])
+
+        # os.makedirs(os.path.join(folder, id, 'gt_uv'), exist_ok=True)
+        # for i in range(uv_gt.shape[0]):
+        #     np.savez_compressed(os.path.join(folder, id, 'gt_uv', garment + '_' + str(i) + '.npz'), uv_gt=uv_gt[i, :, :, :])
+
+        os.makedirs(os.path.join(folder, f'uv_curvature_{neighbourhood}_2'), exist_ok=True)
+        for i in range(uv_curvature.shape[0]):
+            np.savez_compressed(os.path.join(folder, f'uv_curvature_{neighbourhood}_2', id + '_' + str(i) + '.npz'), curvature_uv=uv_curvature[i, :, :])
+
+        # os.makedirs(os.path.join(folder, id, 'uv_unposed'), exist_ok=True)
+        # for i in range(uv_unposed.shape[0]):
+        #     np.savez_compressed(os.path.join(folder, id, 'uv_unposed', garment + '_' + str(i) + '.npz'), uv_unposed=uv_unposed[i, :, :, :])
+
+        # os.makedirs(os.path.join(folder, id, 'uv_unposed_no_shape'), exist_ok=True)
+        # for i in range(uv_unposed_no_shape.shape[0]):
+        #     np.savez_compressed(os.path.join(folder, id, 'uv_unposed_no_shape', garment + '_' + str(i) + '.npz'), uv_unposed_no_shape=uv_unposed_no_shape[i, :, :, :])
+
+        # os.makedirs(os.path.join(folder, id, 'uv_unposed_no_shape_one_hot'), exist_ok=True)
+        # for i in range(uv_unposed_no_shape_one_hot.shape[0]):
+        #     np.savez_compressed(os.path.join(folder, id, 'uv_unposed_no_shape_one_hot', garment + '_' + str(i) + '.npz'), uv_unposed_no_shape=uv_unposed_no_shape_one_hot[i, :, :, :])
+
+        # os.makedirs(os.path.join(folder, id, 'uv_shaped_body'), exist_ok=True)
+        # np.savez_compressed(os.path.join(folder, id, 'uv_shaped_body.npz'), uv_shaped_body=uv_shaped_body)
+
+        # print(time.perf_counter() - start)
+        
+        # mesh = uv_to_mesh(uv_verts_static, m2uv)
+        # verify_reconstruction(verts_static * mask[:, np.newaxis], mesh * mask[:, np.newaxis])
+
+        # mesh = uv_to_mesh(uv_body[0,:,:], m2uv)
+        # verify_reconstruction(body[0,:,:] * mask[:, np.newaxis], mesh * mask[:, np.newaxis])
+
+        pass
+

data/dataset.py

@@ -215,10 +215,9 @@ class DatasetFactory():
             if 'mesh_posed' in signature.keys():
                 if use_no_orient:
                     item['mesh_posed'] = read_posed_garment_frame(folder, id, garment, frame, map, mask=None, shape=None, shapedirs=None, pose=None, unshape=False, deorient=False)
-            if 'mesh_unposed' in signature.keys():
-                mesh_unposed_no_shape = np.load(os.path.join(folder, 'mesh_unposed_no_shape', id + separator + frame_nr + '.npz')); mesh_unposed_no_shape = mesh_unposed_no_shape['mesh_unposed_no_shape']
-                item['mesh_unposed'] = mesh_unposed_no_shape
-
+            # if 'mesh_unposed' in signature.keys():
+            #     mesh_unposed_no_shape = np.load(os.path.join(folder, 'mesh_unposed_no_shape', id + separator + frame_nr + '.npz')); mesh_unposed_no_shape = mesh_unposed_no_shape['mesh_unposed_no_shape']
+            #     item['mesh_unposed'] = mesh_unposed_no_shape
 
             if 'mesh_curvature' in signature.keys():
                 mesh_curvature = np.load(os.path.join(folder, 'mesh_curvature', id + separator + frame_nr + '.npz')); mesh_curvature = mesh_curvature['mesh_curvature']