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论文阅读-Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language
涤旧而生新: 兄弟太强了，最近也在研究这方面的东西！
使用pycharm+opencv进行视频抽帧(可以用来扩充数据集）+ labelimg的使用（数据标准）
苏几下: 最后是这个：COMET INFO : To upload this offline experiment , run : comet upload D :\yolov5-7.0\. cometml - runs \d9031c2bc8b846f986e5fe1124690158.zip
使用pycharm+opencv进行视频抽帧(可以用来扩充数据集）+ labelimg的使用（数据标准）
苏几下: train : weights =yolov5s. pt , cfg =, data = data \ bvn . yaml , hyp = data \ hyps \ hyp . scratch - low . yaml , epochs =100, batch _ size =16, imgsz =640, rect = False , resume = False , nosave = False , noval = False , noautoanchor = False , noplots = False , evolve = None , bucket =, cache = None , image _ weights = False , device =, multi _ scale = False , single _ cls = False , optimizer = SGD , sync _ bn = False , workers =8, pro ject = runs \ train , name = exp , exist _ ok = False , quad = False , cos _ lr = False , label _ smoothing =0.0, patience =100, freeze =[0], save _ period =-1, seed =0, local _ rank =-1, entity = None , upload _ datas et = False , bbox _ interval =-1, artifact _ alias = latest github : skipping check ( not a git repository ), for updates see https://github.com/ultralytics/yolov5 YOLOv52022-11-22 Python -3.12.7 torch -2.4.1+cu124 CUDA :0( NVIDIA GeForce RTX 4060 Laptop GPU ,8188MiB) hyperparameters :1r0=0.01,1rf=0.01, momentum =0.937, weight _ decay =0.0005, warmup _ epochs =3.0, warmup _ momentum =0.8, warmup _ bias _ lr =0.1, box =0.05, cls =0.5, cls _ pw =1.0, obj =1.0, obj _ pw =1.0, iou _ t =0.2, anchor _ t =4.0, fl _ gamma =0.0, hsv _ h =0.015, hsv _ s =0.7, hsv _ v =0.4, degrees =0.0, translate =0.1, scale =0.5, shear =0.0, perspective =0.0, flipud =0.0, fliplr =0.5, mosaic =1.0, mixup =0.0, copy _ paste =0.0ClearML: run ' pip install clearml ' to automatically track , visualize and remotely train YOLOv5 in ClearML TensorBoard : Start with ' tensorboard -- logdir runs \ train ', view at http://localhost:6006/ COMET WARNING : Comet credentials have not been set . Comet will default to offline logging . Please set your credentials to enable online logging . COMET WARNING : To get all data logged automatically , import comet _ ml before the following modules : tensorboard , tensorflow , keras , torch . COMET INFO : Using ' D :\yolov5-7.0\\. cometml - runs ' path as offline directory . Pass ' offline directory ' parameter into constructor or set the ' COMET _ OFFLINE DIRECTORY ' environment va riable to manually choose where to store offline experiment archives . COMET WARNING : Native output logging mode is not available , falling back to basic output logging Traceback ( most recent call last ): File " d :yolov5-7.0\ train . py ", line 633, in < module > main ( opt ) File " d :\yolov5-7.0\ train . py ", line 527, in main train ( opt . hyp , opt , device , callbacks ) File " d :\yolov5-7.0\ train . py ", line 95, in train loggers = Loggers ( save _ dir , weights , opt , hyp , LOGGER )# loggers instance ΑΛΑΑΑΑΛΛΛΑΛΑΛΑΑΛΑΑΛΑΑΑΑΛΑΛΛΑΑΛΛΑΑΛΑΛΛΛΑΑΛΛΛΑ File " d :\yolov5-7.0\ utils \ loggers _ init _- py ", line 132, in _ init _ self . comet _ logger = CometLogger ( self . opt , self . hyp ) ΑΛΑΑΛΑΛΛΑΛΛΛΑΛΛΛΛΛΑΑΛΛΑΛΛΛΛΛΛΛΑ File " d :\yolov5-7.0\ utils \ loggers \ comet _ init _. py ", line 97, in _ init __ self . data _ dict = self . check _ dataset ( self . opt . data ) Aww File " d :\yolov5-7.0\ utils \ loggers \ comet __ init _. py ", line 232, in check _ dataset data _ config = yaml . safe _ load ( f ) AAww File " C :\ Users \ Lenono \. conda \ envs \yolov5\ Lib \ site - packages yaml _ init _. py ", line 125, in safe _ load return load ( stream , SafeLoader ) ΑΛΛΛΛΛΑΛΛΛΑΛΛΛΛΛΑΑΛΛΑΛΛΑ File " C :\ Users \ Lenono \. conda \ envs \yolov5\ Lib \ site - packages \ yaml __ init _. py ", line 79, in load loader = Loader ( stream ) AAAAAAAAAAAAA File " C :\ Users \ Lenono \. conda \ envs \yolov5\ Lib \ site - packages \ yaml \ loader . py ", line 34, in _ init _ Reader ._ init _( self , stream ) File " C :\ Users \ Lenono \. conda \ envs \yolov5\ Lib \ site - packages yaml \ reader . py ", line 85, in _ init _ self . determine _ encoding () File " C :\ Users \ Lenono \. conda \ envs \yolov5\ Lib \ site - packages \ yaml \ reader . py ", line 124, in determine _ encoding data = self . stream . read ( size ) ΑΛΑΑΑΑΑΑΑΑΑΑΛΛΛΑΛΛΛΛΛΑ UnicodeDecodeError :' gbk ' codec can ' t decode byte 0x80 in position 233: illegal multibyte sequence COMET INFO : The process of logging environment details ( conda environment , git patch ) is underway . Please be patient as this may take some time . COMET INFO : Couldn '
使用pycharm+opencv进行视频抽帧(可以用来扩充数据集）+ labelimg的使用（数据标准）
苏几下: 我又弄了一次，然后有照片了，但是运行train.py的时候一直不行
使用pycharm+opencv进行视频抽帧(可以用来扩充数据集）+ labelimg的使用（数据标准）
Che_Che_: 你可以试试文中提到的，自己手动创建一个images文件夹，再运行一次，看看文件夹里面有没有

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力扣-使用双指针的方法的题们（持续更新中。。。

指针初始化指向首尾，首尾指针之和>Target,(说明里面大的那个数和其他的数只会更大），所以移动大数的指针；同理首尾指针之和<Target,(说明里面小的那个数和其他的数只会更小），所以移动小数的指针。1）假设固定左右指针，因为是短板问题，长版的指针如果往中间移动，水的高度不会变，宽度变小，容积一定变小，所以不能移动长的指针；不同于正向思考将零移动到末尾，反向思考，将所以非零数交换移动到最后一个非零指针指向的位置，双指针，一个指针遍历数组，一个指针指向最后一个非零位置。

原创 2025-07-15 22:46:18 · 365 阅读 · 0 评论