o 2h@sddlZddlmZddlmZddlmZddlmZzddl Z Wn e y-dZ Ynwed    dd d Z d dZ dS)N)backend)ops) keras_export)convert_formatz'keras.visualization.draw_bounding_boxesrr?c ! CsVtdurtd|p i}|p|}|pt}t|} t| dkr(td| t|t s9t d|dt |d|vsAd|vrHtd ||d krQd } d } nd } d } | | } | | } | }t ||d| | }t|d}t|d}t|d}d|vrt|d}nd}g}|jd}t|D]}||}||}||}t|jdD]p}||d\}}}}||d}|d krqt|t|t|t|f\}}}}t|}t|||f||f||||vr||}|dur|||}|d|d}t||||\}} tj|||| ftj|||dq||qtj|ddS)a! Draws bounding boxes on images. This function draws bounding boxes on a batch of images. It supports different bounding box formats and can optionally display class labels and confidences. Args: images: A batch of images as a 4D tensor or NumPy array. Shape should be `(batch_size, height, width, channels)`. bounding_boxes: A dictionary containing bounding box data. Should have the following keys: - `boxes`: A tensor or array of shape `(batch_size, num_boxes, 4)` containing the bounding box coordinates in the specified format. - `labels`: A tensor or array of shape `(batch_size, num_boxes)` containing the class labels for each bounding box. - `confidences` (Optional): A tensor or array of shape `(batch_size, num_boxes)` containing the confidence scores for each bounding box. bounding_box_format: A string specifying the format of the bounding boxes. Refer [keras-io](TODO) class_mapping: A dictionary mapping class IDs (integers) to class labels (strings). Used to display class labels next to the bounding boxes. Defaults to None (no labels displayed). color: A tuple or list representing the RGB color of the bounding boxes. For example, `(255, 0, 0)` for red. Defaults to `(128, 128, 128)`. line_thickness: An integer specifying the thickness of the bounding box lines. Defaults to `2`. text_thickness: An integer specifying the thickness of the text labels. Defaults to `1`. font_scale: A float specifying the scale of the font used for text labels. Defaults to `1.0`. data_format: A string, either `"channels_last"` or `"channels_first"`, specifying the order of dimensions in the input images. Defaults to the `image_data_format` value found in your Keras config file at `~/.keras/keras.json`. If you never set it, then it will be "channels_last". Returns: A NumPy array of the annotated images with the bounding boxes drawn. The array will have the same shape as the input `images`. Raises: ValueError: If `images` is not a 4D tensor/array, if `bounding_boxes` is not a dictionary, or if `bounding_boxes` does not contain `"boxes"` and `"labels"` keys. TypeError: If `bounding_boxes` is not a dictionary. ImportError: If `cv2` (OpenCV) is not installed. Nz|The `draw_bounding_boxes` function requires the `cv2` package (OpenCV). Please install it with `pip install opencv-python`.z;`images` must be batched 4D tensor. Received: images.shape=z<`bounding_boxes` should be a dict. Received: bounding_boxes=z of type boxeslabelsza`bounding_boxes` should be a dict containing 'boxes' and 'labels' keys. Received: bounding_boxes= channels_lastxyxyuint8 confidencesrint32z | z.2f)imgtextorgfontFace fontScalecolor thickness)axis)cv2 ImportErrorrimage_data_formatrshapelen ValueError isinstancedict TypeErrortypecopyrconvert_to_numpyastyperangeint rectangle_find_text_locationputTextFONT_HERSHEY_SIMPLEXappendnpstack)!imagesbounding_boxesbounding_box_format class_mappingrline_thicknesstext_thickness font_scale data_format images_shapeh_axisw_axisheightwidthr r rresult batch_sizei_image_box_classbox_ix1y1x2y2clabelconffont_x1font_y1rQf/var/www/html/chatgem/venv/lib/python3.10/site-packages/keras/src/visualization/draw_bounding_boxes.pydraw_bounding_boxess=       $    rScCsTt|d}|d}|d|dkr||dfS|}d}|||d|||fS)N rr)r,)xyr:r font_heighttarget_y line_offset static_offsetrQrQrRr.s  r.)Nrrr r N) numpyr2 keras.srcrrkeras.src.api_exportrLkeras.src.layers.preprocessing.image_preprocessing.bounding_boxes.convertersrrrrSr.rQrQrQrRs(