o W h6 @sDddlZddlmZddlmZmZddlmZGdddeZdS)N)Path) BaseSolutionSolutionResults) save_one_boxcs(eZdZdZfddZddZZS) ObjectCroppera A class to manage the cropping of detected objects in a real-time video stream or images. This class extends the BaseSolution class and provides functionality for cropping objects based on detected bounding boxes. The cropped images are saved to a specified directory for further analysis or usage. Attributes: crop_dir (str): Directory where cropped object images are stored. crop_idx (int): Counter for the total number of cropped objects. iou (float): IoU (Intersection over Union) threshold for non-maximum suppression. conf (float): Confidence threshold for filtering detections. Methods: process: Crops detected objects from the input image and saves them to the output directory. Examples: >>> cropper = ObjectCropper() >>> frame = cv2.imread("frame.jpg") >>> processed_results = cropper.process(frame) >>> print(f"Total cropped objects: {cropper.crop_idx}") c stjd i||dd|_tj|jst|j|jdr,|j d|jd|_ |jd|_ |jddurD|jd|_ dSd |_ dS) a3 Initialize the ObjectCropper class for cropping objects from detected bounding boxes. Args: **kwargs (Any): Keyword arguments passed to the parent class and used for configuration. crop_dir (str): Path to the directory for saving cropped object images. crop_dirzcropped-detectionsshowzTshow=True disabled for crop solution, results will be saved in the directory named: riouconfNg?)super__init__getrospathexistsmkdirCFGLOGGERwarningcrop_idxr r )selfkwargs __class__r X/var/www/vscode/kcb/lib/python3.10/site-packages/ultralytics/solutions/object_cropper.pyr !s    (zObjectCropper.__init__cCst|jj||j|j|j|jddd}|jD]}|jd7_t|j |t |j d|jdddqt ||jd S) a5 Crop detected objects from the input image and save them as separate images. Args: im0 (numpy.ndarray): The input image containing detected objects. Returns: (SolutionResults): A SolutionResults object containing the total number of cropped objects and processed image. Examples: >>> cropper = ObjectCropper() >>> frame = cv2.imread("image.jpg") >>> results = cropper.process(frame) >>> print(f"Total cropped objects: {results.total_crop_objects}") device)classesr r rrcrop_z.jpgT)fileBGR)plot_imtotal_crop_objects) modelpredictrr r rboxesrrxyxyrrr)rim0resultsboxr r rprocess6s zObjectCropper.process)__name__ __module__ __qualname____doc__r r+ __classcell__r r rrr s r) rpathlibrultralytics.solutions.solutionsrrultralytics.utils.plottingrrr r r rs