1#使用torchvision来加载并归一化CIFAR10数据集23importtorch4importtorchvision#保存了一些数据集5importtorchvision.transforms as transforms#进行数据预处理6importtorch.nn as nn7importtorch.nn.functional as F8importtorch.optim as optim910fromtorch.autogradimportVariable111213#定义网络一般继承torch.nn.Module创建新...
source_image_name) src_img = Image.open(path_source_img) full_image_name=prefix+"_train_"+source_image_name print(full_image_name) # save renamed image to the target dir target_image_path=os.path.join(target_image_dir, full_image_name) src_img.save(target_image_path) ...
train_ds = ImageFolder('../input/intel-image-classification/seg_train/seg_train', transform=transform_train)test_ds = ImageFolder('../input/intel-image-classification/seg_test/seg_test', transform=transform_test)pred_ds = ImageFolder('/kaggle/input/intel-image-classification/seg_pred/', transfor...
Then there is this section of the code where I start training the Net. for epoch in range(2): running_loss = 0.0 for i, data in enumerate(wiki_train_dataloader, 0): inputs, labels = data['image'], data['class'] print(inputs.shape) inputs, labels = Variable(input...
( root=r'E:\machine learning\Deep_learning\deep_learning\PyTorch\code\some_models\vgg-demo\VGG16\satelite\Satellite_Image_Classification\val', transform=custom_transform ) classes = val_dataset.classes val_loader = DataLoader(dataset=val_dataset, batch_size=16, shuffle=True) for features, ...
cd PyTorch_image_classifier python tools/data_preprocess.py--data_dir"./data/data.csv"--n_splits5--output_dir"./data/train.csv"--random_state2020 1、修改配置文件,选择需要的模型 以及 模型参数:vim conf/test.yaml 代码语言:javascript
title(f'{title} label: {str(y)}') return True #用torch.utils.make_grid构建一组图片 def make_grid_image(ori_ds, grid_size=4): grid_size = grid_size rnd_inds = np.random.randint(0,len(ori_ds),grid_size) print("image indices:", rnd_inds) x_grid=[ori_ds[i][0] for i in...
open(full_filenames) # 画图显示 draw = ImageDraw.Draw(img) draw.rectangle(((32, 32), (64, 64)), outline='green') plt.subplot(nrows, ncols, i+1) if color_flag is True: plt.imshow(np.array(img)) else: plt.imshow(np.array(img)[:,:,0], cmap='gray') plt.axis('off') ...
pathlib import Path import requests # 设置数据文件夹路径 data_path = Path("data/") image_...
torchrun和torch.distributed.launch的用法基本一致,不过弃用了--use_env命令,直接将local_rank设置在环境变量中,目前最新版本的torchvision是采用torchrun启动方式,具体见 vision/references/classification at main · pytorch/vision。 混合精度训练(采用apex) 混合精度训练(混合FP32和FP16训练)可以适用更大的batch_size...