From 18a21d4b07c581a8954b08518115fb035c712b28 Mon Sep 17 00:00:00 2001
From: natanielruiz <nataniel777@hotmail.com>
Date: 星期二, 08 八月 2017 07:34:09 +0800
Subject: [PATCH] Added new correct cropping for training and smoothing for video.
---
code/datasets.py | 46 +++++++++++++++++++++++++++++++++++++---------
1 files changed, 37 insertions(+), 9 deletions(-)
diff --git a/code/datasets.py b/code/datasets.py
index 3750e71..06cd433 100644
--- a/code/datasets.py
+++ b/code/datasets.py
@@ -81,9 +81,24 @@
def __getitem__(self, index):
img = Image.open(os.path.join(self.data_dir, self.X_train[index] + self.img_ext))
img = img.convert('RGB')
+ mat_path = os.path.join(self.data_dir, self.y_train[index] + self.annot_ext)
+
+ # Crop the face
+ pt2d = utils.get_pt2d_from_mat(mat_path)
+ x_min = min(pt2d[0,:])
+ y_min = min(pt2d[1,:])
+ x_max = max(pt2d[0,:])
+ y_max = max(pt2d[1,:])
+
+ k = 0.15
+ x_min -= k * abs(x_max - x_min)
+ y_min -= 4 * k * abs(y_max - y_min)
+ x_max += k * abs(x_max - x_min)
+ y_max += 0.4 * k * abs(y_max - y_min)
+ img = img.crop((int(x_min), int(y_min), int(x_max), int(y_max)))
# We get the pose in radians
- pose = utils.get_ypr_from_mat(os.path.join(self.data_dir, self.y_train[index] + self.annot_ext))
+ pose = utils.get_ypr_from_mat(mat_path)
# And convert to degrees.
pitch = pose[0] * 180 / np.pi
yaw = pose[1] * 180 / np.pi
@@ -117,23 +132,36 @@
def __getitem__(self, index):
img = Image.open(os.path.join(self.data_dir, self.X_train[index] + self.img_ext))
img = img.convert('RGB')
+ mat_path = os.path.join(self.data_dir, self.y_train[index] + self.annot_ext)
+
+ # Crop the face
+ pt2d = utils.get_pt2d_from_mat(mat_path)
+ x_min = min(pt2d[0,:])
+ y_min = min(pt2d[1,:])
+ x_max = max(pt2d[0,:])
+ y_max = max(pt2d[1,:])
+
+ k = 0.15
+ x_min -= k * abs(x_max - x_min)
+ y_min -= 4 * k * abs(y_max - y_min)
+ x_max += k * abs(x_max - x_min)
+ y_max += 0.4 * k * abs(y_max - y_min)
+ img = img.crop((int(x_min), int(y_min), int(x_max), int(y_max)))
# We get the pose in radians
- pose = utils.get_ypr_from_mat(os.path.join(self.data_dir, self.y_train[index] + self.annot_ext))
+ pose = utils.get_ypr_from_mat(mat_path)
# And convert to degrees.
- pitch, yaw, roll = pose * 180 / np.pi
+ pitch = pose[0] * 180 / np.pi
+ yaw = pose[1] * 180 / np.pi
+ roll = pose[2] * 180 / np.pi
# Bin values
bins = np.array(range(-99, 102, 3))
- binned_pitch = torch.DoubleTensor(np.digitize(pitch, bins) - 1)
- binned_yaw = torch.DoubleTensor(np.digitize(yaw, bins) - 1)
- binned_roll = torch.DoubleTensor(np.digitize(roll, bins) - 1)
-
- label = binned_yaw, binned_pitch, binned_roll
+ labels = torch.LongTensor(np.digitize([yaw, pitch, roll], bins) - 1)
if self.transform is not None:
img = self.transform(img)
- return img, label, self.X_train[index]
+ return img, labels, self.X_train[index]
def __len__(self):
# 2,000
--
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