开始时调用HAL_UART_Receive_DMA(&huart1, uartDeviceRxBuf, UART_BUF_LEN); 在接收到的相应长度的数据之后DMA会产生一个完成的中断,其回调函数与中断模式相同,虽然两者发生中断地方不一致,但是操作是同一个 voidHAL_UART_RxCpltCallback(UART_HandleTypeDef *uartHandle) {if(uartHandle->Instance == USART1) ...
Modbus的CRC校验实验 表述 Name :"CRC-16/MODBUS"Width :16Poly :8005Init :FFFFRefIn :TrueRefOut :TrueXorOut :0000Check :? 先参考一些厂家给的MODBUS校验程序 const unsigned char auchCRCHi[] = {0x00,0xC1,0x81,0x40,0x01,0xC0,0x80,0x41,0x01,0xC0,0x80,0x41,0x00,0xC1,0x81,0x40,0x0...
百度试题 结果1 题目Cau 2:Cho tam giac vuong ABH vuong H tai co BH =2; AB=3. Hinh chieu cua H len AB la K. Tinh tich vo huong BK BH. D A. 4.4/3 e3/4 (16)/9 相关知识点: 试题来源: 解析 DChọn DTa có: 反馈 收藏 ...
', function(index) { - layer.close(index); - fly.json('/api/jieda-delete/', { - id: li.data('id') - }, function(res) { - if(res.status === 0) { - var count = dom.jiedaCount.text() | 0; - dom.jiedaCount.html(--count); - li.remove(); - //如果删除了最佳答案...
web_set_max_html_param_len("500000"); lr_think_time(atoi(lr_eval_string("{randomthink}"))); // lr_start_transaction("Homepage"); web_url("flex-internal_2", "URL=https://globalcenter.seawave.com/GlobalCenter/flex-internal?action=history_html_secure", ...
from torchvision.models import vgg16 device = "cuda" if torch.cuda.is_available() else "cpu" print("Using {} device".format(device)) # 加载预训练模型,并且对模型进行微调 model = vgg16(pretrained = True).to(device) # 加载预训练的vgg16模型 for param in model.parameters(): param.requires...
torchvisionimporttorch.nn.functionalasFfromtorchvisionimporttransforms,datasetsfromsklearn.model_selectionimportKFoldfromtorch.optim.lr_schedulerimportStepLR,MultiStepLR,LambdaLR,ExponentialLR,CosineAnnealingLR,ReduceLROnPlateauimportos,PIL,pathlib,randomdevice=torch.device("cuda"iftorch.cuda.is_available()else"...
toks = [t[i:i+self.ngram]foriinrange(0,len(t), self.stride)iflen(t[i:i+self.ngram]) == self.ngram]returntoks# 假设不使用实例属性,而是硬编码deftokenize(self, t): t = t.upper() ngram =5stride =2ifngram ==1: toks =list(t)else: ...
p = k //2ifisinstance(k,int)else[x //2forxink]# auto-padreturnp 3.2 Conv 这个函数是整个网络中最基础的组件,由 卷积层 + BN层 + 激活函数组成,具体结构如下 classConv(nn.Module):# Standard convolution with args(ch_in, ch_out, kernel, stride, padding, groups, dilation, activation)defaul...
file_val.write(name)else: file_test.write(name) file_trainval.close() file_train.close() file_val.close() file_test.close() 2、运行voc_label.py 该脚本文件的主要功能是生成训练集/测试集/验证集的数据索引文件train.txt/test.txt/val.txt,并归一化标注信息(labels文件夹下)。