U Hc@sldZddlZddlZddlZddlZddlmZddlmZm Z m Z e dZ ddZ dd d Z dddZdS)z AutoAnchor utils N)tqdm)LOGGERcolorstremojisz AutoAnchor: cCsp|jdd}|d|d}|jd|jd}||krlttd|jd|jdd<dS)NrzReversing anchor order) anchorsprodviewstridesignrinfoPREFIXflip)madadsrF/var/www/html/VideoAnalyticsDashboard/src/./yolov5/utils/autoanchor.pycheck_anchor_orders r@c s t|dr|jjdn|jd}||j|jjddd}tjjdd|jddfd }t t d d t |||j Dfd d }|j|j|jjddd}||dd\} } dt| dd| dd} | dkrtt| dntt| d|jd} zt|| |ddd}Wn8tk rx} zttd| W5d} ~ XYnX||d}|| krt j ||jjd|j}||j|j|jjddd|jdd<t|ttdnttddS)NmodulerTkeepdims?g?r)sizecSs(g|] \}}|ddddf|qSNr.0slrrr !sz!check_anchors..csvdddf|d}t|d|dd}|dd}|dkd}|dk}||fSNrr)torchminmaxfloatsummean)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_sizer5genverbosezERROR: )devicezSNew anchors saved to model. Update model *.yaml to use these anchors in the future.zKOriginal anchors better than new anchors. Proceeding with original anchors.) hasattrrmodelshapesr*nprandomuniformshaper(tensor concatenateziplabelsr+rcloner tor@r cpur rr rnumel kmean_anchors Exceptiontype_asview_asr)datasetrBr5imgszrrCscaler7rr3r2r#naeZnew_bprrr4r check_anchorss. *$ &  4rY./data/coco128.yaml r;Tc sddlm}tj}dddfdd}d+fd d } t|trt|d d } t| } W5QRXdd l m } | | dddd}|j |j j ddd} t ddt| |jDdkd}|rttd|dtddkdttddtdd}||ddd|}t|krttdt|ddt|dd}tjtjd tjtjd | |d!d"}|||jd#d$f\} }}}tt |td%d&}|D]}t!|}|dk"rT|||kt|j#||d$d'd}q|%|j$dd(}||}|| kr||%} }td)| d*|_&|r| ||q| |S),aB Creates kmeans-evolved anchors from training dataset Arguments: dataset: path to data.yaml, or a loaded dataset n: number of anchors img_size: image size used for training thr: anchor-label wh ratio threshold hyperparameter hyp['anchor_t'] used for training, default=4.0 gen: generations to evolve anchors using genetic algorithm verbose: print all results Return: k: kmeans evolved anchors Usage: from utils.autoanchor import *; _ = kmean_anchors() r)kmeansrcSsD|dddf|d}t|d|dd}||ddfSr&)r(r)r*)r.r6r/r0rrrr7Wszkmean_anchors..metriccs.tj|tjd\}}||kS)Ndtype)r(rHfloat32r+r-)r._r1)r7r5r6rranchor_fitness]sz%kmean_anchors..anchor_fitnessTcs|t|d}|\}}|k|k}}tddd|dd|ddtdd d |d d |d d ||kd d}t|D](\}}|dt|dt|df7}q|rt |dd|S)Nrzthr=r9z: .4fz best possible recall, z anchors past thr zn=z , img_size=z , metric_all=r:/z-mean/best, past_thr=z-mean: z%i,%i, r) rDargsortrr+r-r enumerateroundrr )r.r?r0r1r3r2r#i)r=r7r<r5wh0rr print_resultsas&`"z$kmean_anchors..print_resultsignore)errors)LoadImagesAndLabelstrain)augmentrectrcSs(g|] \}}|ddddf|qSrrr!rrrr%vsz!kmean_anchors..g@z(WARNING: Extremely small objects found. z of z labels are < 3 pixels in size.g@zRunning kmeans for z anchors on z points...)iterz/WARNING: scipy.cluster.vq.kmeans returned only z requested pointsr'r]F)r?rg?z(Evolving anchors with Genetic Algorithm:)descg333333?)r)z3Evolving anchors with Genetic Algorithm: fitness = rb)T)'Zscipy.cluster.vqr\rDrE isinstancestropenyaml safe_loadutils.datasetsrmrCr*rIrJrKanyr,rr r lenstdwarningsortrandreshaper(rHr_rGrrangeonesallrandnclipcopyrs)rTr<r=r5r>r?r\Znprrarjf data_dictrmrCrhr#r.shmppbarr`vkgfgr)r=r7r<r5r6rirrPAsP          4 rP)rr)rZr[rrr;T)__doc__rEnumpyrDr(rwr utils.generalrrrr rrYrPrrrrs  %