o 2hK@sddlZddlZddlmZddlmZddlmZddlm Z zddl m Z Wn e y3dZ YnwddZed         dd dZdS)N)backend)ops) keras_export)BaseImagePreprocessingLayercCs8tt|dkr tdt||}|d|df}|S)ayExtracts a batch of images for plotting. Args: images: The 4D tensor or NumPy array of images. num_images: The number of images to extract. batch_size: The original batch size of the images. Returns: A 4D tensor or NumPy array containing the extracted images. Raises: ValueError: If `images` is not a 4D tensor/array. zO`plot_images_gallery()` requires you to batch your `np.array` samples together.N.)lenrshape ValueErrormin)images num_images batch_size num_samplessamplere/var/www/html/chatgem/venv/lib/python3.10/site-packages/keras/src/visualization/plot_image_gallery.py_extract_image_batchs rz&keras.visualization.plot_image_galleryrT<c Cstdurtd|dur| rtd|dus|dur"|dur"td| dur(| n|du} | p1t} tt|dkrBt|dnd}|pOtt t |}|pZtt ||}||}t |||}| dkrot |d }tj||||||fd d d d dd\}}|jdddt|tjrt|jdkr|dkrdnd}t||}| dur|j| ddtj||dd}t|}| dkr| dddd}|durt|}|durt|}t|D]v}t|D]o}|||}t|tjr|||fn|}|||d|jddd|dg}|dur/|t|kr/|d|||d|durI|t|krI|d|||d|rV|jd |dd qq|durmtj!|dd | | d!t"dS| rzt#t"dSdS)"aDisplays a gallery of images with optional labels and predictions. Args: images: A 4D tensor or NumPy array of images. Shape should be `(batch_size, height, width, channels)`. y_true: A 1D tensor or NumPy array of true labels (class indices). Defaults to `None`. y_pred: A 1D tensor or NumPy array of predicted labels (class indices). Defaults to `None`. label_map: A dictionary mapping class indices to class names. Required if `y_true` or `y_pred` are provided. Defaults to `None`. value_range: A tuple specifying the value range of the images (e.g., `(0, 255)` or `(0, 1)`). Defaults to `(0, 255)`. rows: The number of rows in the gallery. If `None`, it's calculated based on the number of images and `cols`. Defaults to `None`. cols: The number of columns in the gallery. If `None`, it's calculated based on the number of images and `rows`. Defaults to `None`. scale: A float controlling the size of the displayed images. The images are scaled by this factor. Defaults to `2`. path: The path to save the generated gallery image. If `None`, the image is displayed using `plt.show()`. Defaults to `None`. show: Whether to display the image using `plt.show()`. If `True`, the image is displayed. If `False`, the image is not displayed. Ignored if `path` is not `None`. Defaults to `True` if `path` is `None`, `False` otherwise. transparent: A boolean, whether to save the figure with a transparent background. Defaults to `True`. dpi: The DPI (dots per inch) for saving the figure. Defaults to 60. legend_handles: A list of matplotlib `Patch` objects to use as legend handles. Defaults to `None`. data_format: The image data format `"channels_last"` or `"channels_first"`. Defaults to the Keras backend data format. Raises: ValueError: If both `path` and `show` are set to non-`None` values, if `images` is not a 4D tensor or array, or if `y_true` or `y_pred` are provided without a `label_map`. ImportError: if matplotlib is not installed. NzuThe `plot_image_gallery` function requires the `matplotlib` package. Please install it with `pip install matplotlib`.zEplot_gallery() expects either `path` to be set, or `show` to be true.zJIf `y_true` or `y_pred` are provided, a `label_map` must also be provided.rrchannels_first)rrrFtightTrowcol)nrowsncolsfigsizeframeonlayoutsqueezesharexsharey)wspacehspacez lower center)handleslocr)r original_range target_rangerruint8)xyoffzLabel: UnknownzPred: z )fontsize)fname pad_inches bbox_inches transparentdpi)$plt ImportErrorr rimage_data_formatrrrintmathceilsqrtr transposesubplotssubplots_adjust isinstancenpndarray expand_dimslegendr_transform_value_rangeconvert_to_numpyrangeimshowastypemarginsaxisappendget set_titlejoinsavefigcloseshow)r y_truey_pred label_maprowscols value_rangescalepathrTr6r7legend_handles data_formatr r figaxes expand_axisrrindex current_axis title_partsrrrplot_image_gallery,s9  $               re) NNNNNrrNNTrNN)r<numpyrC keras.srcrrkeras.src.api_exportrQkeras.src.layers.preprocessing.image_preprocessing.base_image_preprocessing_layerrmatplotlib.pyplotpyplotr8r9rrerrrrs6