o e@sRddlmZmZmZddlZddlZddlmZddl m Z m Z GdddZ dS))ListOptionalUnionN) Detections)Color ColorPalettec @seZdZdZededddfdeeefde ded e d e d e f d d Z  dde j dedeeedede j f ddZdS) BoxAnnotatora A class for drawing bounding boxes on an image using detections provided. Attributes: color (Union[Color, ColorPalette]): The color to draw the bounding box, can be a single color or a color palette thickness (int): The thickness of the bounding box lines, default is 2 text_color (Color): The color of the text on the bounding box, default is white text_scale (float): The scale of the text on the bounding box, default is 0.5 text_thickness (int): The thickness of the text on the bounding box, default is 1 text_padding (int): The padding around the text on the bounding box, default is 5 g? color thickness text_color text_scaletext_thickness text_paddingcCs(||_||_||_||_||_||_dS)N)r r rrrr)selfr r rrrrrM/var/www/myenv/lib/python3.10/site-packages/supervision/detection/annotate.py__init__s   zBoxAnnotator.__init__NFscene detectionslabels skip_labelreturnc Csrtj}tt|D]}|j|t\}}} } |jdur!|j|nd} | dur)| n|} t|j t r7|j | n|j } tj |||f| | f| |jd|rNq |dusZt|t|kr]| n||}tj|||j|jdd\}}||j}||j}|}|d|j|}|d|j|}|}tj |||f||f| tjdtj||||f||j|j|jtjdq |S)a3 Draws bounding boxes on the frame using the detections provided. Args: scene (np.ndarray): The image on which the bounding boxes will be drawn detections (Detections): The detections for which the bounding boxes will be drawn labels (Optional[List[str]]): An optional list of labels corresponding to each detection. If `labels` are not provided, corresponding `class_id` will be used as label. skip_label (bool): Is set to `True`, skips bounding box label annotation. Returns: np.ndarray: The image with the bounding boxes drawn on it Example: ```python >>> import supervision as sv >>> classes = ['person', ...] >>> image = ... >>> detections = sv.Detections(...) >>> box_annotator = sv.BoxAnnotator() >>> labels = [ ... f"{classes[class_id]} {confidence:0.2f}" ... for _, _, confidence, class_id, _ ... in detections ... ] >>> annotated_frame = box_annotator.annotate( ... scene=image.copy(), ... detections=detections, ... labels=labels ... ) ``` N)imgpt1pt2r r )textfontFace fontScaler rr )rrorgrr r r lineType)cv2FONT_HERSHEY_SIMPLEXrangelenxyxyastypeintclass_id isinstancer rby_idx rectangleas_bgrr getTextSizerrrFILLEDputTextras_rgbLINE_AA)rrrrrfontix1y1x2y2r*idxr r text_width text_heighttext_xtext_ytext_background_x1text_background_y1text_background_x2text_background_y2rrrannotate+sn*    zBoxAnnotator.annotate)NF)__name__ __module__ __qualname____doc__rdefaultrblackrr)floatrnpndarrayrrrstrboolrCrrrrr sD   r) typingrrrr#numpyrKsupervision.detection.corersupervision.draw.colorrrrrrrrs