&Vf\dZddlZddlmZddlmZddlmZejZ d dZ d dZ 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 <ddlmcm}||}tj||}||5|||d|||j | |g5|d|}| |j j ||jd} ||} ||| dd || d d gd } || | gd} |jd| ||cdddcdddS#1swxYwYddddS#1swxYwYdS)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 descriptionencode_each_image)dtypename)inputwidth)rheight dimensions)axis image_summary)rtensor collectionssummary_metadata)tensorflow.compat.v1compatv1rcreate_summary_metadata name_scopecontrol_dependencies assert_rank assert_typeuint8assert_non_negativemap_fnimage encode_pngstringshapestack as_stringconcatsummarytensor_summary) rimages max_outputsr r rtfrlimited_imagesencoded_images image_shaperrs ^/var/www/html/software/conda/lib/python3.11/site-packages/tensorboard/plugins/image/summary.pyopr5$snB&%%%%%%%% 7!{ t    b55 NN61 % % NN628 , ,  " "; / /     - H  )$ #   hhVh,, XX [^' :: [^( ;;    J7a@@z(( #- )  /                                         s7AFCE9 F9E= =FE= FFFcddlmcm}tj|tj}|jdkrtd|j d|d|}d|D}|j d|j d} }t|t| g|z} | | |j } ||}tj|| } |j| } |}|jd |z| | |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 z must have rank 4c6g|]}tj|S)rr&).0r%s r4 zpb..s#LLLEg(//LLLrr)r rz%s/image_summary)tagrr)rrrnparrayastyper"ndim ValueErrorr(strmake_tensor_protor'rrSummaryMetadata FromStringSerializeToStringSummaryvalueadd)rr.r/r r r0r1r2rrcontentrrtf_summary_metadatar,s r4pbrLksd6&%%%%%%%% Xf   $ $RX . .F {aj FGGGL[L)NLL^LLLN|A QFU5zz3v;;'.8G  ! !' ! ; ;F 7!{,77**,,jjllG M  %$ Nr;)rNNN)rNN) __doc__numpyr=tensorboard.plugins.imagerrtensorboard.utilrr%r5rLr8r;r4rQs......000000$$$$$$   D D D D N666666r;