From 3c2c851ba5519f30cfe8f282f383a332d666d445 Mon Sep 17 00:00:00 2001
From: Hunor Laczko <luni741@gmail.com>
Date: Fri, 6 Jan 2023 11:27:13 +0000
Subject: [PATCH] only read info.mat once

---
 cloth3d/read.py | 20 ++++++++------------
 data/dataset.py | 12 ++++++------
 2 files changed, 14 insertions(+), 18 deletions(-)

diff --git a/cloth3d/read.py b/cloth3d/read.py
index 3806ff6..702f5fa 100644
--- a/cloth3d/read.py
+++ b/cloth3d/read.py
@@ -57,16 +57,14 @@ class DataReader:
     - V: human mesh vertices
     - F: mesh faces
     """
-    def read_human(self, sample, frame, absolute=True):
-        # Read sample data
-        info = self.read_info(sample)
+    def read_human(self, sample, frame, trans, zrot):
         # SMPL parameters
         gender, pose, shape, trans = self.read_smpl_params(sample, frame)
         # Compute SMPL
-        V, J = self.smpl[gender].set_params(pose=pose, beta=shape, trans=trans if absolute else None)
+        V, J = self.smpl[gender].set_params(pose=pose, beta=shape, trans=trans)
         V -= J[0:1]
         # Apply rotation on z-axis
-        zRot = zRotMatrix(info['zrot'])
+        zRot = zRotMatrix(zrot)
         return zRot.dot(V.T).T, self.smpl[gender].faces, zRot.dot(trans.T).T[None,:], zRot.dot((J -  J[0:1] + trans[None,:]).T).T[None,:], zRot.dot((J -  J[0:1]).T).T[None,:]
     
     """ Garment data """
@@ -76,21 +74,19 @@ class DataReader:
     - sample: name of the sample
     - garment: type of garment (e.g.: 'Tshirt', 'Jumpsuit', ...)
     - frame: frame number
-    - absolute: True for absolute vertex locations, False for locations relative to SMPL root joint	
+    - TODO: absolute: True for absolute vertex locations, False for locations relative to SMPL root joint	
     Outputs:
     - V: 3D vertex locations for the specified sample, garment and frame
     """
-    def read_garment_vertices(self, sample, garment, frame, absolute=True):
+    def read_garment_vertices(self, sample, garment, frame, trans, zrot):
         # Read garment vertices (relative to root joint)
         pc16_path = os.path.join(self.SRC, sample, garment + '_registered.pc16')
         V = readPC2Frame(pc16_path, frame, True)
         # Read sample data
-        info = self.read_info(sample)
-        if absolute:
+        if trans is not None:
             # Transform to absolute
-            V += info['trans'][:,frame][None]
-        # Apply rotation on z-axis
-        zRot = zRotMatrix(info['zrot'])
+            V += trans[None]
+        zRot = zRotMatrix(zrot)
         return zRot.dot(V.T).T
 
     """
diff --git a/data/dataset.py b/data/dataset.py
index 9d59411..0c3fe84 100644
--- a/data/dataset.py
+++ b/data/dataset.py
@@ -43,22 +43,22 @@ class Dataset(Dataset):
     def __getitem__(self, idx):
         frame : Frame = self.frames[idx]
         path = os.path.join(self.folder, frame.id)
+        info = self.reader.read_info(frame.id)
         # mesh_posed = readPC2Frame(os.path.join(path, frame.garment + '_registered.pc16'), frame.frame_nr, True)
-        mesh_posed = self.reader.read_garment_vertices(frame.id, frame.garment, frame.frame_nr)
-        mesh_posed_no_trans = self.reader.read_garment_vertices(frame.id, frame.garment, frame.frame_nr, absolute=False)
+        mesh_posed = self.reader.read_garment_vertices(frame.id, frame.garment, frame.frame_nr, info['trans'][:,frame.frame_nr], info['zrot'])
+        # mesh_posed_no_trans = self.reader.read_garment_vertices(frame.id, frame.garment, frame.frame_nr, absolute=False)
 
         mesh_mask = np.load(os.path.join(path, frame.garment + '_mask.npy'))
         # TODO: what's the difference between masking and reading .obj file
         faces = mask_faces(self.body_faces, mesh_mask)
         # faces = quads2tris(self.reader.read_garment_topology(frame.id, frame.garment))
         # body = readPC2Frame(os.path.join(path, 'Body_posed.pc16'), frame.frame_nr, True)
-        body, body_faces, root_joint, joints, joints_no_trans = self.reader.read_human(frame.id, frame.frame_nr)
-        body_no_trans, _, _, _, _ = self.reader.read_human(frame.id, frame.frame_nr, absolute=False)
+        body, body_faces, root_joint, joints, joints_no_trans = self.reader.read_human(frame.id, frame.frame_nr, info['trans'][:,frame.frame_nr], info['zrot'])
+        # body_no_trans, _, _, _, _ = self.reader.read_human(frame.id, frame.frame_nr, absolute=False)
         body_faces = quads2tris(body_faces)
 
-        info = self.reader.read_info(frame.id)
         combined = torch.Tensor(np.concatenate((body, mesh_posed[mesh_mask, :]))).to('cuda')
-        combined_no_trans = torch.Tensor(np.concatenate((body_no_trans, mesh_posed_no_trans[mesh_mask, :]))).to('cuda')
+        # combined_no_trans = torch.Tensor(np.concatenate((body_no_trans, mesh_posed_no_trans[mesh_mask, :]))).to('cuda')
         combined_faces = torch.Tensor(np.concatenate((body_faces, faces + body.shape[0]))).to('cuda')
 
         idx_frame = 35500