o Ďi@sdZddlZddlZddlZddlZddlmZddlmZddl m Z m Z m Z e dZ ddZee d dd d ZdddZdS)z AutoAnchor utils N)tqdm) TryExcept)LOGGERTQDM_BAR_FORMATcolorstrz AutoAnchor: cCs|jddd}|d|d}|jd|jd}|r=||kr?ttd|j d|jdd<dSdSdS)NrzReversing anchor order) anchorsprodmeanviewstridesignrinfoPREFIXflip)madadsrS/home/jeff/fluffinator/venv/lib/python3.10/site-packages/yolov5/utils/autoanchor.pycheck_anchor_ordersrERROR@cst|dr |jjdn|jd}||j|jjddd}tjjdd|jddfd }t t d d t |||j Dfd d }|j|jjddd}|j|} || dd\} } dt| dd| dd} | dkrt| ddSt| d|jd} t|| |ddd} || d}|| krt j | |jjd|j} | |j|jdd<t||j|_td} ntd} t| dS)NmodulerTkeepdims?g?r)sizecS(g|]\}}|ddddf|qSNr.0slrrr #(z!check_anchors..csvdddf|d}t|d|dd}|dd}|dkd}|dk}||fSNrr)torchminmaxfloatsumr )krxbestaatbprthrwhrrmetric%s zcheck_anchors..metricr, .2fz anchors/target, .3fz Best Possible Recall (BPR). g\(\?u-Current anchors are a good fit to dataset ✅uBAnchors are a poor fit to dataset ⚠️, attempting to improve...F)nimg_sizer9genverbose)deviceuKDone ✅ (optional: update model *.yaml to use these anchors in the future)uXDone ⚠️ (original anchors better than new anchors, proceeding with original anchors))hasattrrmodelshapesr/nprandomuniformshaper-tensor concatenateziplabelsr0r torrDr clonecpurrrnumel kmean_anchorstype_asview_asr)datasetrFr9imgszrrGscaler;r rr7r6r'nanew_bprrr8r check_anchorss. *   r\./data/coco128.yaml r?Tc sddlm}tj}dddfdd}d+fd d } t|trSt|d d  } t| } Wd n1s?wYddl m } | | dddd}|j |j j ddd} t ddt| |jDdkd}|rttd|dtddkdtjz4ttddtdtksJd}||ddd|}t|ksJWn!tyttdt|dd}Ynwd d!fD\| |d"d#}|||jd$d%f\} }}}tt |t!d&}|D]Y}t"|}|dk#rA|||kt|j$||d%d'd}|dk#s"|&|j%dd(}||}|| krl||&} }td)| d*|_'|rl| ||q| |tjS),aI Creates kmeans-evolved anchors from training dataset Arguments: dataset: path to data.yaml, or a loaded dataset n: number of anchors img_size: image size used for training thr: anchor-label wh ratio threshold hyperparameter hyp['anchor_t'] used for training, default=4.0 gen: generations to evolve anchors using genetic algorithm verbose: print all results Return: k: kmeans evolved anchors Usage: from yolov5.utils.autoanchor import *; _ = kmean_anchors() r)kmeansrcSsD|dddf|d}t|d|dd}||ddfSr+)r-r.r/)r2r:r3r4rrrr;Yszkmean_anchors..metriccs.tj|tjd\}}||kS)Ndtype)r-rLfloat32r0r )r2_r5)r;r9r:rranchor_fitness_sz%kmean_anchors..anchor_fitnessTcs|t|d}|\}}|k|k}}tddd|dd|ddtdd d |d d |d d ||kd d}|D]}|dt|dt|df7}qV|rtt|dd|S)Nrzthr=r=z: .4fz best possible recall, z anchors past thr zn=z , img_size=z , metric_all=r>/z-mean/best, past_thr=z-mean: z%i,%i, r) rHargsortr r0r rroundrr)r2rCr4r5r7r6r')rAr;r@r9wh0rr print_resultscs*&"z$kmean_anchors..print_resultsignore)errorsN)LoadImagesAndLabelstrain)augmentrectrcSr!r"rr%rrrr)xr*z!kmean_anchors..g@u.WARNING ⚠️ Extremely small objects found: z of z labels are <3 pixels in sizeg@zRunning kmeans for z anchors on z points...)iteru>WARNING ⚠️ switching strategies from kmeans to random initr,css |] }tj|tjdVqdS)r`N)r-rLrb)r&r4rrr sz kmean_anchors..F)rCrg?) bar_formatg333333?)r.z3Evolving anchors with Genetic Algorithm: fitness = re)T)(scipy.cluster.vqr_rHrI isinstancestropenyaml safe_loadyolov5.utils.dataloadersrnrGr/rMrNrOanyr1rrrlenastyperbstd ExceptionwarningsortrandreshaperKrrangeronesallrandnclipcopydesc)rWr@rAr9rBrCr_nprrdrkf data_dictrnrGir'r2shmppbarrcvkgfgr)rAr;r@r9r:rjrrTCs\        $  0  rT)rr)r]r^rrr?T)__doc__rInumpyrHr-rzr yolov5.utilsryolov5.utils.generalrrrrrr\rTrrrrs   %