def convert_to_example(self, label):
img_path = os.path.join(self.img_dir, label.name)
with tf.gfile.FastGFile(img_path, 'r') as f:
img_data = f.read()
example = tf.train.Example(features=tf.train.Features(feature={
'name':_bytes_feature(label.name),
'xyz_pose':_float_feature(label.pose),
'png16':_bytes_feature(img_data)}))
return example
def convert_to_example(self, label):
img_path = os.path.join(self.img_dir, label.name)
with tf.gfile.FastGFile(img_path, 'r') as f:
img_data = f.read()
self._decode_png(img_data)
if self.subset == 'testing':
example = tf.train.Example(features=tf.train.Features(feature={
'name':_bytes_feature(label.name),
'xyz_pose':_float_feature(label.pose),
'bbx':_float_feature(label.bbx),
'png16':_bytes_feature(img_data)}))
else:
example = tf.train.Example(features=tf.train.Features(feature={
'name':_bytes_feature(label.name),
'xyz_pose':_float_feature(label.pose),
'png16':_bytes_feature(img_data)}))
return example