Fi=6ddlmZddlmZmZmZmZ erJeddusJddlZejdddsJddl Z ddl Z da iZ d a dd ed ed dfd Zdded ed dfdZddZddZddZddZddZddZddZer eeeeeedZyiZy#eeef$rdZYMwxYw))Path)LOGGERSETTINGS TESTS_RUNNINGchecksdvcTNdvclivez2.11.0)verboseFpathprefixreturnc\tr|j}tjd|x}rM|d}tjdd|j }t ||z j|j}tjtjj|||yy)a`Log images at specified path with an optional prefix using DVCLive. This function logs images found at the given path to DVCLive, organizing them by batch to enable slider functionality in the UI. It processes image filenames to extract batch information and restructures the path accordingly. Args: path (Path): Path to the image file to be logged. prefix (str, optional): Optional prefix to add to the image name when logging. Examples: >>> from pathlib import Path >>> _log_images(Path("runs/train/exp/val_batch0_pred.jpg"), prefix="validation") z _batch(\d+)_batchN) livenameresearchsubstemr with_suffixsuffix log_imageosr join)r r rmninew_stems a/var/www/pod-logistic/pod-ai/venv/lib/python3.12/site-packages/ultralytics/utils/callbacks/dvc.py _log_imagesr s yy .$/ /1 /1Bvvnh BHNR'44T[[AD rww||FD148 plotsc|jD]8\}}|d}tj||k7s$t|||t|<:y)aLog plot images for training progress if they have not been previously processed. Args: plots (dict): Dictionary containing plot information with timestamps. prefix (str, optional): Optional prefix to add to the logged image paths. timestampN)items_processed_plotsgetr )r"r rparamsr$s r _log_plotsr)8sO / f;'    % 2 f %%. T " /r!cg}g}|jj}t|jj }|jj dk(r|dgz }t |jjtD]H\}}t |D]5\}}|j||g|z|j||g|z7Jtjd||ddy)aLog confusion matrix for a validator using DVCLive. This function processes the confusion matrix from a validator object and logs it to DVCLive by converting the matrix into lists of target and prediction labels. Args: validator (BaseValidator): The validator object containing the confusion matrix and class names. Must have attributes confusion_matrix.matrix, confusion_matrix.task, and names. detect backgroundconfusion_matrixzcf.jsonT)r normalizedN) r-matrixlistnamesvaluestask enumerateTastypeintextendrlog_sklearn_plot) validatortargetspredsr/r1tipredpinums r_log_confusion_matrixrAFsG E  ' ' . .F '') *E!!&&(2 ,fhhooc23,D  ,GB NNE"I;, - LL%)s* + ,,  ,gu9Y]^r!c tjddatjdy#t $r"}tj d|Yd}~yd}~wwxYw)zLInitialize DVCLive logger for training metadata during pre-training routine.T) save_dvc_exp cache_imagesz[DVCLive is detected and auto logging is enabled (run 'yolo settings dvc=False' to disable).zGDVCLive installed but not initialized correctly, not logging this run. N)r Liverrinfo Exceptionwarning)traineres ron_pretrain_routine_startrK_sPf||DA qr f`ab`cdeefs,/ AAAc0t|jdy)zPLog plots related to the training process at the end of the pretraining routine.trainN)r)r"rIs ron_pretrain_routine_endrOisw}}g&r!cPtr tj|jyy)z9Log the training parameters if DVCLive logging is active.N)r log_paramsargsrNs ron_train_startrSns   % r!cday)zZSet the global variable _training_epoch value to True at the start of each training epoch.TN)_training_epochrNs ron_train_epoch_startrVts Or!ctrtri|j|jd|j|j }|j D]\}}tj|||jdk(r>> # Inside a custom training loop >>> from ultralytics.utils.callbacks.dvc import on_train_end >>> on_train_end(trainer) # Log final metrics and artifacts rMrXFrZr\Tmodel)copytypeN)rr]r^r_r`r%rar)r"r:rAbestexists log_artifactend)rIrerfrgs r on_train_endrqs r11'--1PrT[TcTcrgngqgqr (..0 7MFE OOFEO 6 7 7==%(7$$**E2g//0 <<     gllG  D   r!)rKrOrSrVrhrq))r N)pathlibrultralytics.utilsrrrrr check_versionrrrr&rU ImportErrorAssertionError TypeErrorstrr dictr)rArKrOrSrVrhrq callbacksr!rr}s EE  E?d "" " 6   8T BB B   DO 9d9C996 /d /C / /_2f' &   BP&?#:( 4,$    C ^Y/Gs6B BB