From 9f2fa4a5fa2af40503c05379c9d5318e87581c7b Mon Sep 17 00:00:00 2001
From: natanielruiz <nataniel777@hotmail.com>
Date: 星期五, 08 十二月 2017 02:10:14 +0800
Subject: [PATCH] Removed shape loading which fixes a bug with loading AFLW2000 and 300W-LP for training and testing.

---
 code/datasets.py |   12 ++----------
 1 files changed, 2 insertions(+), 10 deletions(-)

diff --git a/code/datasets.py b/code/datasets.py
index 5f1dfdc..8d05d98 100644
--- a/code/datasets.py
+++ b/code/datasets.py
@@ -96,7 +96,6 @@
         img = Image.open(os.path.join(self.data_dir, self.X_train[index] + self.img_ext))
         img = img.convert(self.image_mode)
         mat_path = os.path.join(self.data_dir, self.y_train[index] + self.annot_ext)
-        shape_path = os.path.join(self.data_dir, self.y_train[index] + '_shape.npy')
 
         # Crop the face loosely
         pt2d = utils.get_pt2d_from_mat(mat_path)
@@ -136,11 +135,8 @@
         bins = np.array(range(-99, 102, 3))
         binned_pose = np.digitize([yaw, pitch, roll], bins) - 1
 
-        # Get shape
-        shape = np.load(shape_path)
-
         # Get target tensors
-        labels = torch.LongTensor(np.concatenate((binned_pose, shape), axis = 0))
+        labels = binned_pose
         cont_labels = torch.FloatTensor([yaw, pitch, roll])
 
         if self.transform is not None:
@@ -171,7 +167,6 @@
         img = Image.open(os.path.join(self.data_dir, self.X_train[index] + self.img_ext))
         img = img.convert(self.image_mode)
         mat_path = os.path.join(self.data_dir, self.y_train[index] + self.annot_ext)
-        shape_path = os.path.join(self.data_dir, self.y_train[index] + '_shape.npy')
 
         # Crop the face loosely
         pt2d = utils.get_pt2d_from_mat(mat_path)
@@ -214,11 +209,8 @@
         bins = np.array(range(-99, 102, 3))
         binned_pose = np.digitize([yaw, pitch, roll], bins) - 1
 
-        # Get shape
-        shape = np.load(shape_path)
-
         # Get target tensors
-        labels = torch.LongTensor(np.concatenate((binned_pose, shape), axis = 0))
+        labels = binned_pose
         cont_labels = torch.FloatTensor([yaw, pitch, roll])
 
         if self.transform is not None:

--
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