API - Preprocessing¶
Data preprocessing, more Tensor functions about image, signal processing can be found in TensorFlow API
distorted_images ([images, height, width]) |
Distort images for generating more training data. |
crop_central_whiten_images ([images, height, …]) |
Crop the central of image, and normailize it for test data. |
Images¶
For training data¶
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tensorlayer.preprocess.
distorted_images
(images=None, height=24, width=24)[source]¶ Distort images for generating more training data.
Parameters: - images : 4D Tensor
The tensor or placeholder of images
- height : int
The height for random crop.
- width : int
The width for random crop.
Returns: - result : tuple of Tensor
(Tensor for distorted images, Tensor for while loop index)
Notes
The first image in ‘distorted_images’ should be removed.
References
tensorflow.models.image.cifar10.cifar10_input
Examples
>>> X_train, y_train, X_test, y_test = tl.files.load_cifar10_dataset(shape=(-1, 32, 32, 3), plotable=False) >>> sess = tf.InteractiveSession() >>> batch_size = 128 >>> x = tf.placeholder(tf.float32, shape=[batch_size, 32, 32, 3]) >>> distorted_images_op = tl.preprocess.distorted_images(images=x, height=24, width=24) >>> sess.run(tf.initialize_all_variables()) >>> feed_dict={x: X_train[0:batch_size,:,:,:]} >>> distorted_images, idx = sess.run(distorted_images_op, feed_dict=feed_dict) >>> tl.visualize.images2d(X_train[0:9,:,:,:], second=2, saveable=False, name='cifar10', dtype=np.uint8, fig_idx=20212) >>> tl.visualize.images2d(distorted_images[1:10,:,:,:], second=10, saveable=False, name='distorted_images', dtype=None, fig_idx=23012)
For testing data¶
-
tensorlayer.preprocess.
crop_central_whiten_images
(images=None, height=24, width=24)[source]¶ Crop the central of image, and normailize it for test data.
They are cropped to central of height * width pixels.
Whiten (Normalize) the images.
Parameters: - images : 4D Tensor
The tensor or placeholder of images
- height : int
The height for central crop.
- width: int
The width for central crop.
Returns: - result : tuple Tensor
(Tensor for distorted images, Tensor for while loop index)
Notes
The first image in ‘central_images’ should be removed.
Examples
>>> X_train, y_train, X_test, y_test = tl.files.load_cifar10_dataset(shape=(-1, 32, 32, 3), plotable=False) >>> sess = tf.InteractiveSession() >>> batch_size = 128 >>> x = tf.placeholder(tf.float32, shape=[batch_size, 32, 32, 3]) >>> central_images_op = tl.preprocess.crop_central_whiten_images(images=x, height=24, width=24) >>> sess.run(tf.initialize_all_variables()) >>> feed_dict={x: X_train[0:batch_size,:,:,:]} >>> central_images, idx = sess.run(central_images_op, feed_dict=feed_dict) >>> tl.visualize.images2d(X_train[0:9,:,:,:], second=2, saveable=False, name='cifar10', dtype=np.uint8, fig_idx=20212) >>> tl.visualize.images2d(central_images[1:10,:,:,:], second=10, saveable=False, name='central_images', dtype=None, fig_idx=23012)