首先我们下载CIFAR-100 python version,下载完之后解压,在cifar-100-Python下会出现:meta,test和train三个文件,他们都是python用cPickle封装的pickled对象 def unpickle(file): import cPickle fo = open(file,'rb') dict = cPickle.load(fo) fo.close() ret
经历:自学python,现在混迹于paddle社区,希望和大家一起从基础走起,一起学习Paddle csdn地址:https://blog.csdn.net/weixin_45623093/article/list/3 我在AI Studio上获得至尊等级,点亮10个徽章,来互关呀~https://aistudio.baidu.com/aistudio/personalcenter/thirdview/284366 传说中的飞桨社区最菜代码人,让我们一...
Cache file /home/aistudio/.cache/paddle/dataset/cifar/cifar-100-python.tar.gz not found, downloading https://dataset.bj.bcebos.com/cifar/cifar-100-python.tar.gz Begin to download Download finished ② 模型选择和开发 ##2.1 模型开发 In [3] network = paddle.vision.models.resnet101(num_class...
# 导入相关库 import paddle import numpy as np import io import os from PIL import Image import paddle import numpy as np import paddle.nn as nn import matplotlib.pyplot as plt paddle.__version__ /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/matplotlib/__init__.py:...
/device gpu /device cpu Software Environment: -- MindSpore version (source or binary): -- Python version (e.g., Python 3.7.5): -- OS platform and distribution (e.g., Linux Ubuntu 16.04): -- GCC/Compiler version (if compiled from source): ...
if sys.version_info[0] == 2: import cPickle as pickle else: import pickle class CIFAR10(data.Dataset): base_folder = 'cifar-10-batches-py' url = "http://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz" filename = "cifar-10-python.tar.gz" tgz_mdf = 'c58f30108f718f92721af...
python download-and-convert-cifar-100.pyrm: cannot remove ‘download-and-convert-cifar-100.py’: No such file or directory Getting the download script... wget: /root/anaconda2/lib/libcrypto.so.1.0.0: no version information available (required by wget) wget: /root/anaconda2/lib/libssl.so...
「CIFAR-10 python version」、「CIFAR-100 python version」からダウンロードして、適当な場所に解凍する input_cifar.py import cPickle import numpy as np import os def unpickle(file): fo = open(file, 'rb') dict = cPickle.load(fo) ...
Paddle2.0高层API加载Resnet101预训练模型实现Cifar100图像识别,增强验证集模拟随机测试集,泛化能力好,准确率高达82%,增加EPOCH或加入模型融合还可再高一线。 Nemo 5枚 AI Studio 经典版 2.0.2 Python3 初级计算机视觉深度学习数据分析分类 2022-03-04 22:00:00 版本内容 Fork记录 评论(0) 运行一下 1 2022-...
import os import random import paddle import numpy as np import warnings warnings.filterwarnings("ignore") paddle.__version__ '2.0.0' In [3] # 设置随机种子 seed = 42 def seed_everything(seed): random.seed(seed) os.environ['PYTHONHASHSEED'] = str(seed) np.random.seed(seed) paddle.se...