o W h@sXddlZddlZddlmZddlmZddlmZddlm Z m Z GdddeZ dS)N)Image) BasePredictor)Results) DEFAULT_CFGopscs8eZdZdZeddffdd ZddZddZZS) ClassificationPredictora A class extending the BasePredictor class for prediction based on a classification model. This predictor handles the specific requirements of classification models, including preprocessing images and postprocessing predictions to generate classification results. Attributes: args (dict): Configuration arguments for the predictor. _legacy_transform_name (str): Name of the legacy transform class for backward compatibility. Methods: preprocess: Convert input images to model-compatible format. postprocess: Process model predictions into Results objects. Notes: - Torchvision classification models can also be passed to the 'model' argument, i.e. model='resnet18'. Examples: >>> from ultralytics.utils import ASSETS >>> from ultralytics.models.yolo.classify import ClassificationPredictor >>> args = dict(model="yolo11n-cls.pt", source=ASSETS) >>> predictor = ClassificationPredictor(overrides=args) >>> predictor.predict_cli() Ncs"t|||d|j_d|_dS)a Initialize the ClassificationPredictor with the specified configuration and set task to 'classify'. This constructor initializes a ClassificationPredictor instance, which extends BasePredictor for classification tasks. It ensures the task is set to 'classify' regardless of input configuration. Args: cfg (dict): Default configuration dictionary containing prediction settings. Defaults to DEFAULT_CFG. overrides (dict, optional): Configuration overrides that take precedence over cfg. _callbacks (list, optional): List of callback functions to be executed during prediction. classifyz&ultralytics.yolo.data.augment.ToTensorN)super__init__argstask_legacy_transform_name)selfcfg overrides _callbacks __class__\/var/www/vscode/kcb/lib/python3.10/site-packages/ultralytics/models/yolo/classify/predict.pyr &s  z ClassificationPredictor.__init__cst|tjs2tfddjjD}|r$tjfdd|Ddd}ntjfdd|Ddd}t|tjr:|nt|jj }jj rL| S| S)zVConvert input images to model-compatible tensor format with appropriate normalization.c3s|] }jt|vVqdS)N)r str).0 transformrrr 9s z5ClassificationPredictor.preprocess..csg|]}|qSr) transformsrimrrr =sz6ClassificationPredictor.preprocess..r)dimc s&g|]}tt|tjqSr)rr fromarraycv2cvtColor COLOR_BGR2RGBrrrrr@s&) isinstancetorchTensoranyrstack from_numpytomodeldevicefp16halffloat)rimgis_legacy_transformrrr preprocess6s  $z"ClassificationPredictor.preprocesscsNt|ts t|}t|ttfr|dn|}fddt||jdDS)a Process predictions to return Results objects with classification probabilities. Args: preds (torch.Tensor): Raw predictions from the model. img (torch.Tensor): Input images after preprocessing. orig_imgs (List[np.ndarray] | torch.Tensor): Original images before preprocessing. Returns: (List[Results]): List of Results objects containing classification results for each image. rcs&g|]\}}}t||jj|dqS))pathnamesprobs)rr+r4)rpredorig_imgimg_pathrrrrUsz7ClassificationPredictor.postprocess..)r$listrconvert_torch2numpy_batchtuplezipbatch)rpredsr0 orig_imgsrrr postprocessEs  z#ClassificationPredictor.postprocess) __name__ __module__ __qualname____doc__rr r2r@ __classcell__rrrrr s r) r!r%PILrultralytics.engine.predictorrultralytics.engine.resultsrultralytics.utilsrrrrrrrs