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smpl2supersmpl.py

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+import os
+import numpy as np
+
+import numpy as np
+import pickle as pkl
+from scipy import sparse
+
+from time import time
+import plotly.graph_objects as go
+
+from custom_utils.supersmpl_io import writeOBJ, readOBJ
+
+
+def makeGraph(F):
+    G = {}
+    for f in F:
+        N = len(f)
+        for i,v in enumerate(f):
+            if not v in G: G[v] = {}
+            G[v][f[(i+1) % N]] = 1
+    return G
+
+def extrapolateMissings(M, G):
+    for i in range(6890, M.shape[0]):
+        if np.isnan(M[i]).all():
+            M[i] = neighAvg(M, G, i)
+        elif np.isnan(M[i]).any():
+            print("HOW?")
+            print(M[i])
+    if np.isnan(M).any(): extrapolateMissings(M, G)
+
+def neighAvg(M, G, i):
+    neigh = set(G[i].keys())
+    avg = 0
+    count = 0
+    for n in neigh:
+        if not np.isnan(M[n]).any():
+            avg += M[n]
+            count += 1
+    if count: return avg / count
+    return np.nan
+
+
+def convert(smpl, G):
+    supersmpl = np.empty((27578, 3), np.float32)
+    supersmpl[:] = np.nan
+    supersmpl[:6890] = smpl
+    extrapolateMissings(supersmpl, G)
+    return supersmpl
+
+
+if __name__ == '__main__':
+
+    g = 'f'
+    # Read Super topology
+    V, F, Vt, Ft = readOBJ('super_' + g + '_avg.obj')
+    G = makeGraph(F)
+
+    folder = '/home/workspace/data/dataset/cape/cape_release'
+    test = np.load(os.path.join('/home/workspace/data/dataset/cape_zips/03383/shortlong_ATUsquat/shortlong_ATUsquat.000105.npz'))
+    faces = np.load(os.path.join(folder, 'misc/smpl_tris.npy'))
+    min_body = np.load(os.path.join(folder, 'minimal_body_shape/03383/03383_minimal.npy')) 
+    offsets_cano = test['v_cano'] - min_body
+
+    supersmpl = convert(test['v_posed'], G)
+
+    x = supersmpl
+    fig = go.Figure(data=[
+            go.Mesh3d(
+                # 8 vertices of a cube
+                x=x[:,0],
+                y=x[:,1],
+                z=x[:,2],
+                # i, j and k give the vertices of triangles
+                i = faces[:,0],
+                j = faces[:,1],
+                k = faces[:,2]
+            ),
+        ])
+
+    fig.update_layout(scene_aspectmode='manual',
+                    scene_aspectratio=dict(x=1, y=1, z=1))
+    fig.update_layout(
+        scene = dict(
+            xaxis = dict(nticks=4, range=[-1,1],),
+                        yaxis = dict(nticks=4, range=[-1,1],),
+                        zaxis = dict(nticks=4, range=[-1,1],),)
+                        )
+
+    fig.show()
+
+    print()