a Sic@sNdZddlZddlmZddlmZddlmZejZd ddZ d d d Z dS) aHImage summaries and TensorFlow operations to create them. An image summary stores the width, height, and PNG-encoded data for zero or more images in a rank-1 string array: `[w, h, png0, png1, ...]`. NOTE: This module is in beta, and its API is subject to change, but the data that it stores to disk will be supported forever. N)metadata) summary_v2)encoderc Cs8ddlmm}|dur|}tj||d}|||||d|||j | |g|d|}|j |j j ||jdd} |j|d} |j|j| dd d |j| d d d gd d } |j| | gdd} |jjd| ||dWdWdS1s 0YWdn1s*0YdS)aCreate a legacy image summary op for use in a TensorFlow graph. Arguments: name: A unique name for the generated summary node. images: A `Tensor` representing pixel data with shape `[k, h, w, c]`, where `k` is the number of images, `h` and `w` are the height and width of the images, and `c` is the number of channels, which should be 1, 3, or 4. Any of the dimensions may be statically unknown (i.e., `None`). max_outputs: Optional `int` or rank-0 integer `Tensor`. At most this many images will be emitted at each step. When more than `max_outputs` many images are provided, the first `max_outputs` many images will be used and the rest silently discarded. display_name: Optional name for this summary in TensorBoard, as a constant `str`. Defaults to `name`. description: Optional long-form description for this summary, as a constant `str`. Markdown is supported. Defaults to empty. collections: Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[Graph Keys.SUMMARIES]`. Returns: A TensorFlow summary op. rN display_name descriptionZencode_each_image)dtypename)inputwidth)r height dimensions)axis image_summary)r tensor collectionssummary_metadata)tensorflow.compat.v1compatv1rcreate_summary_metadata name_scopecontrol_dependencies assert_rank assert_typeuint8assert_non_negativemap_fnimage encode_pngstringshapestack as_stringconcatsummarytensor_summary) r images max_outputsrrrtfrlimited_imagesencoded_images image_shaperrr1]/var/www/html/django/DPS/env/lib/python3.9/site-packages/tensorboard/plugins/image/summary.pyop$sB!    r3cCsddlmm}t|tj}|jdkr>td|j f|d|}dd|D}|j d|j d}} t |t | g|} |j | |j d } |dur|}t j||d } |j| } |}|jjd || | d |S) a\Create a legacy image summary protobuf. This behaves as if you were to create an `op` with the same arguments (wrapped with constant tensors where appropriate) and then execute that summary op in a TensorFlow session. Arguments: name: A unique name for the generated summary, including any desired name scopes. images: An `np.array` representing pixel data with shape `[k, h, w, c]`, where `k` is the number of images, `w` and `h` are the width and height of the images, and `c` is the number of channels, which should be 1, 3, or 4. max_outputs: Optional `int`. At most this many images will be emitted. If more than this many images are provided, the first `max_outputs` many images will be used and the rest silently discarded. display_name: Optional name for this summary in TensorBoard, as a `str`. Defaults to `name`. description: Optional long-form description for this summary, as a `str`. Markdown is supported. Defaults to empty. Returns: A `tf.Summary` protobuf object. rNr zShape %r must have rank 4cSsg|]}t|qSr1)rr#).0r"r1r1r2 zpb..r r)r rz%s/image_summary)tagrr)rrrnparrayastyperndim ValueErrorr%strmake_tensor_protor$rrSummaryMetadata FromStringSerializeToStringSummaryvalueadd)r r+r,rrr-r.r/rrcontentrrtf_summary_metadatar)r1r1r2pbks0  rG)rNNN)rNN) __doc__numpyr8tensorboard.plugins.imagerrtensorboard.utilrr"r3rGr1r1r1r2s     G