load(pthfile) alexnet.load_state_dict(model_data) # 使用load_state_dict方法加载到alexnet模型中 print(alexnet) 代码中,pretrained=False是不加载参数,也就是说这个model中的参数是初始化的而不是训练好的。所以需要将下载好的参数.pth文件配置到模型中。 运行结果: AlexNet( (features): Sequential( (0):...
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xtuner convert pth_to_hf 命令用于进行模型格式转换。...文件 pth_file=`ls -t ...pth_to_hf ...pth_file=`ls -t . 11710 实用教程详解:模型部署,用DNN模块部署YOLOv5目标检测(附源代码) 三、DNN模块部署Yolov5 用opencv的dnn模块做yolov5目标检测的程序,包含两个步骤:1)、把pytorch的训练模型pth文件...
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${TENSORFLOW_DIR}/tensorflow/contrib/makefile/downloads/nsync/public ${TENSORFLOW_DIR}/tensorflow/contrib/makefile/downloads/absl ${TENSORFLOW_DIR}/tensorflow/contrib/makefile/gen/lib ${TENSORFLOW_DIR}/tensorflow/contrib/makefile/gen/protobuf-host/lib ...
So after we download the vgg16-397923af.pth file into "checkpoints" folder , and we dont need to make the "python misc/convert_caffe_pretrain.py"in our shell , and we should directly to the "python train.py train --env='fasterrcnn-caffe' --plot-every=100 --caffe-pretrain“ !
为了下载文件 "https://download.pytorch.org/models/vgg16-397923af.pth" 并保存到 "C:" 目录下,我们可以使用Python的requests库来实现。以下是详细的步骤和代码: 安装requests库: 如果你还没有安装requests库,可以使用以下命令进行安装: bash pip install requests 编写Python脚本下载文件: 使用requests库发送HTTP...
@File : DemoGetData.py @Software: PyCharm """ from torch.utils.data import Dataset class MyDLoadData(Dataset): def __init__(self): self.file = open('../databases/test.txt').readlines() def __getitem__(self, item): return self.file[item] ...
for file in files: dest_path = os.path.join(resolved_path, file) if os.path.exists(dest_path): print(f"Skip file download, it already exists: {file}") continue url = f"https://agi.gpt4.org/llama/LLaMA/{model}/{file}" response = requests.get(url, stream=True) with open(dest_...
#tensorboard# from torch.utils.tensorboard import SummaryWriter from PIL import Image import numpy as np writer=SummaryWriter("logs")#把数据写入logs文件夹内 image_path="./ant/308196310_1db5ffa01b.jpg" img=Image.open(image_path)#此时img类型为JpegImageFile img_array=np.array(img)#将img转化为...