基于p2pcrowdcounting的大豆p2p计数模型

Eval Log Fri Jul 14 10:53:50 2023 Namespace(backbone='vgg16', batch_size=1, checkpoints_dir='checkpointds_dir', clip_max_norm=0.1, data_root='/home/king/Projects/LiuHuaiyang/p2p_plant_counting/p2p_Soybean/soybean_datasets/SOYBEAN/data_root', dataset_file='SOYBEAN', eos_coef=0.05, epochs=200, eval=False, eval_freq=2, frozen_weights=None, gpu_id=0, half=False, line=2, lr=0.0001, lr_drop=1000, lr_fpn=1e-05, num_workers=1, output_dir='output_dir', point_loss_coef=0.0002, resume='', row=2, seed=42, set_cost_class=1, set_cost_point=0.5, start_epoch=0, tensorboard_dir='tensorboard_dir', threshold=0.5, vis_dir='/media/king/DATA/LiuHuaiyang/p2p_plant_counting/p2p_Soybean/vis_p2pnetSoy_testing', weight_decay=0.0001)mae:97017.74242424243, mse:103794.91865000235, time:108.60173106193542, best mae:97017.74242424243metric/mae@0: 97017.74242424243metric/mse@0: 103794.91865000235loss/loss@0: 0.10297484024767838loss/loss_ce@0: 0.10211981854416312[ep 0][lr 0.0001000][24.29s]loss/loss@1: 0.08284864179967415loss/loss_ce@1: 0.08227750274633604[ep 1][lr 0.0001000][23.53s]mae:122.93181818181819, mse:132.69568169082947, time:80.5579125881195, best mae:122.93181818181819metric/mae@1: 122.93181818181819metric/mse@1: 132.69568169082947loss/loss@2: 0.07435253626918273loss/loss_ce@2: 0.07396524308604144[ep 2][lr 0.0001000][22.99s]loss/loss@3: 0.07886109360685897loss/loss_ce@3: 0.07845561102860504[ep 3][lr 0.0001000][24.04s]mae:122.93181818181819, mse:132.69568169082947, time:80.51736307144165, best mae:122.93181818181819metric/mae@2: 122.93181818181819metric/mse@2: 132.69568169082947loss/loss@4: 0.07873950401941936loss/loss_ce@4: 0.0784250135784821[ep 4][lr 0.0001000][24.67s]loss/loss@5: 0.0769289743731774loss/loss_ce@5: 0.07659169414361554[ep 5][lr 0.0001000][26.27s]mae:122.93181818181819, mse:132.69568169082947, time:80.38532495498657, best mae:122.93181818181819metric/mae@3: 122.93181818181819metric/mse@3: 132.69568169082947loss/loss@6: 0.07070395803921634loss/loss_ce@6: 0.07042609408335199[ep 6][lr 0.0001000][24.86s]loss/loss@7: 0.07621902717454802loss/loss_ce@7: 0.07593307350688273[ep 7][lr 0.0001000][28.40s]mae:122.93181818181819, mse:132.69568169082947, time:80.58882284164429, best mae:122.93181818181819metric/mae@4: 122.93181818181819metric/mse@4: 132.69568169082947loss/loss@8: 0.07104344621655487loss/loss_ce@8: 0.07080117432725808[ep 8][lr 0.0001000][25.84s]loss/loss@9: 0.0669034445244405loss/loss_ce@9: 0.06662193678378586[ep 9][lr 0.0001000][25.94s]mae:122.93181818181819, mse:132.69568169082947, time:80.34734010696411, best mae:122.93181818181819metric/mae@5: 122.93181818181819metric/mse@5: 132.69568169082947loss/loss@10: 0.07193948228710464loss/loss_ce@10: 0.07164867927453347[ep 10][lr 0.0001000][24.89s]loss/loss@11: 0.06749965641499749loss/loss_ce@11: 0.06725964279076646[ep 11][lr 0.0001000][27.03s]mae:122.93181818181819, mse:132.69568169082947, time:81.16495323181152, best mae:122.93181818181819metric/mae@6: 122.93181818181819metric/mse@6: 132.69568169082947loss/loss@12: 0.06675411032749311loss/loss_ce@12: 0.06657535186599171[ep 12][lr 0.0001000][25.87s]loss/loss@13: 0.06923471481376697loss/loss_ce@13: 0.06905678004795124[ep 13][lr 0.0001000][30.31s]mae:120.06818181818181, mse:128.7491394499043, time:81.31049466133118, best mae:120.06818181818181metric/mae@7: 120.06818181818181metric/mse@7: 128.7491394499043loss/loss@14: 0.06045277210484658loss/loss_ce@14: 0.06027606493305592[ep 14][lr 0.0001000][26.04s]loss/loss@15: 0.05838754725095535loss/loss_ce@15: 0.058209029961347816[ep 15][lr 0.0001000][28.02s]mae:98.81818181818181, mse:103.82079548798292, time:81.22397780418396, best mae:98.81818181818181metric/mae@8: 98.81818181818181metric/mse@8: 103.82079548798292loss/loss@16: 0.061075020611049635loss/loss_ce@16: 0.06091664349364619[ep 16][lr 0.0001000][26.12s]loss/loss@17: 0.06005818891294655loss/loss_ce@17: 0.05986710516588083[ep 17][lr 0.0001000][28.57s]mae:163.6439393939394, mse:258.72506467466405, time:81.48563718795776, best mae:98.81818181818181metric/mae@9: 163.6439393939394metric/mse@9: 258.72506467466405loss/loss@18: 0.05452905434908138loss/loss_ce@18: 0.054314737999072625[ep 18][lr 0.0001000][26.92s]loss/loss@19: 0.055487272876595696loss/loss_ce@19: 0.055321956385991404[ep 19][lr 0.0001000][29.04s]mae:90.10606060606061, mse:145.41523616557828, time:81.28022742271423, best mae:90.10606060606061metric/mae@10: 90.10606060606061metric/mse@10: 145.41523616557828loss/loss@20: 0.04835213218919105loss/loss_ce@20: 0.04818926932704118[ep 20][lr 0.0001000][25.18s]loss/loss@21: 0.05285184740251492loss/loss_ce@21: 0.05269265099472943[ep 21][lr 0.0001000][29.18s]mae:133.0151515151515, mse:229.75998675825065, time:81.80649590492249, best mae:90.10606060606061metric/mae@11: 133.0151515151515metric/mse@11: 229.75998675825065loss/loss@22: 0.05052773506631927loss/loss_ce@22: 0.050377262541876425[ep 22][lr 0.0001000][25.33s]loss/loss@23: 0.05209671417694716loss/loss_ce@23: 0.05195019158372094[ep 23][lr 0.0001000][28.73s]mae:454.0681818181818, mse:628.8237034336413, time:80.97771692276001, best mae:90.10606060606061metric/mae@12: 454.0681818181818metric/mse@12: 628.8237034336413loss/loss@24: 0.049570284717317135loss/loss_ce@24: 0.04942417346561948[ep 24][lr 0.0001000][26.72s]loss/loss@25: 0.050500705187755915loss/loss_ce@25: 0.05035688045124213[ep 25][lr 0.0001000][28.77s]mae:140.5, mse:234.2778071202881, time:80.7343213558197, best mae:90.10606060606061metric/mae@13: 140.5metric/mse@13: 234.2778071202881loss/loss@26: 0.04907771339640021loss/loss_ce@26: 0.04893610352975509[ep 26][lr 0.0001000][25.09s]loss/loss@27: 0.049561653005343584loss/loss_ce@27: 0.049418756098944756[ep 27][lr 0.0001000][26.95s]mae:239.74242424242425, mse:372.44802362615684, time:80.74750566482544, best mae:90.10606060606061metric/mae@14: 239.74242424242425metric/mse@14: 372.44802362615684loss/loss@28: 0.04549991679451768loss/loss_ce@28: 0.045353983395865986[ep 28][lr 0.0001000][26.84s]loss/loss@29: 0.044010398465962636loss/loss_ce@29: 0.043871778203913615[ep 29][lr 0.0001000][28.84s]mae:102.4090909090909, mse:155.38768719989795, time:81.46699714660645, best mae:90.10606060606061metric/mae@15: 102.4090909090909metric/mse@15: 155.38768719989795loss/loss@30: 0.04308289381128455loss/loss_ce@30: 0.04294955588522412[ep 30][lr 0.0001000][26.10s]loss/loss@31: 0.041603724738316875loss/loss_ce@31: 0.04147155532642963[ep 31][lr 0.0001000][29.04s]mae:193.22727272727272, mse:318.2684211146118, time:81.67432856559753, best mae:90.10606060606061metric/mae@16: 193.22727272727272metric/mse@16: 318.2684211146118loss/loss@32: 0.043613545470944946loss/loss_ce@32: 0.043479513931309895[ep 32][lr 0.0001000][26.64s]loss/loss@33: 0.039784110402540554loss/loss_ce@33: 0.039651146779457726[ep 33][lr 0.0001000][28.53s]mae:391.1060606060606, mse:596.3378135577082, time:80.92615389823914, best mae:90.10606060606061metric/mae@17: 391.1060606060606metric/mse@17: 596.3378135577082loss/loss@34: 0.03656810713517997loss/loss_ce@34: 0.03643334529451316[ep 34][lr 0.0001000][25.11s]loss/loss@35: 0.03883200515771196loss/loss_ce@35: 0.03869590549803679[ep 35][lr 0.0001000][28.14s]mae:462.2651515151515, mse:625.1880504974871, time:80.26260614395142, best mae:90.10606060606061metric/mae@18: 462.2651515151515metric/mse@18: 625.1880504974871loss/loss@36: 0.04449980211118975loss/loss_ce@36: 0.044336605720990706[ep 36][lr 0.0001000][25.84s]loss/loss@37: 0.04313872145518424loss/loss_ce@37: 0.04300115066063073[ep 37][lr 0.0001000][29.21s]mae:356.97727272727275, mse:513.53459504013, time:81.1429169178009, best mae:90.10606060606061metric/mae@19: 356.97727272727275metric/mse@19: 513.53459504013loss/loss@38: 0.03434813494187972loss/loss_ce@38: 0.03421078046547279[ep 38][lr 0.0001000][25.26s]loss/loss@39: 0.03834205664073428loss/loss_ce@39: 0.03820635566842698[ep 39][lr 0.0001000][27.99s]mae:353.2121212121212, mse:499.9456788673964, time:80.48815536499023, best mae:90.10606060606061metric/mae@20: 353.2121212121212metric/mse@20: 499.9456788673964loss/loss@40: 0.0