name="prediction")
pred_annotation = tf.expand_dims(pred_annotation, axis=3)
with tf.variable_scope("infer_decode"):
decoder_net = cls.unet(softmax_image_segment, keep_prob,
phase_train, 3, flags.num_layers,
flags.debug)
reconstruct_image = decoder_net['segment']
return pred_annotation, image_segment_logits, reconstruct_image
if __name__ == '__main__':
"""
Init network and train.
"""
flags = tf_flags()
net = Wnet_naive(flags)
print("Setting up dataset reader")
train_dataset_reader, validation_dataset_reader, test_dataset_reader = create_BatchDatset(
'./soccer')
if "train" in flags.mode:
net.train_net(train_dataset_reader, validation_dataset_reader)
elif "visualize" in flags.mode:
valid_images, preds = net.visualize_pred(validation_dataset_reader)
elif "test" in flags.mode:
test_images, preds = net.plot_segmentation_on_test(test_dataset_reader)
(datetime.datetime.now(), valid_loss))
# add validation loss to TensorBoard
self.validation_writer.add_summary(summary_sva, itr)
self.saver.save(
self.sess, os.path.join(self.flags.logs_dir, "model.ckpt"),
itr)
return
if __name__ == '__main__':
"""
Init network and train.
"""
flags = tf_flags()
net = Wnet_bright(flags)
if flags.mode == "test":
test_images, preds = net.plot_segmentation_under_test_dir()
else:
print("Setting up dataset reader")
train_dataset_reader, validation_dataset_reader = create_BatchDatset()
if flags.mode == "train":
net.train_net(train_dataset_reader, validation_dataset_reader)
elif flags.mode == "visualize":
valid_images, preds = net.visaulize_pred(validation_dataset_reader)
flags.debug)
reconstruct_ice = decoder_net['segment']
return pred_annotation, image_segment_logits, reconstruct_ice
if __name__ == '__main__':
"""
Init network and train.
"""
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
flags = tf_flags()
net = Wnet_ice(flags)
print("Setting up dataset reader")
train_dataset_reader, validation_dataset_reader, test_dataset_reader = \
create_BatchDatset('./soccer/ice',
image_dir='images',
annotation_dir='segmentations',
ftype='png')
if "train" in flags.mode:
net.train_net(train_dataset_reader, validation_dataset_reader)
elif "visualize" in flags.mode:
valid_images, preds = net.visualize_pred(validation_dataset_reader)
elif "test" in flags.mode:
test_images, preds = net.plot_segmentation_on_test(test_dataset_reader)