API - Visualization ================================ TensorFlow provides `TensorBoard `_ to visualize the model, activations etc. Here we provide more functions for data visualization. .. automodule:: tensorlayer.visualize .. autosummary:: read_image read_images save_image save_images draw_boxes_and_labels_to_image draw_mpii_pose_to_image draw_weights CNN2d frame images2d tsne_embedding Save and read images ---------------------- Read one image ^^^^^^^^^^^^^^^^^ .. autofunction:: read_image Read multiple images ^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: read_images Save one image ^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: save_image Save multiple images ^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: save_images Save image for object detection ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: draw_boxes_and_labels_to_image Save image for pose estimation (MPII) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: draw_mpii_pose_to_image Visualize model parameters ------------------------------ Visualize CNN 2d filter ^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: CNN2d Visualize weights ^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: draw_weights Visualize images ----------------- Image by matplotlib ^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: frame Images by matplotlib ^^^^^^^^^^^^^^^^^^^^^ .. autofunction:: images2d Visualize embeddings -------------------- .. autofunction:: tsne_embedding