Chapter 2 introduces the MNIST data, describing its structure, data characteristics, and label meanings. Understanding these will help you write appropriate programs to analyze and identify the MNIST data set. This section will use the same data set to complete the task of classifying it. 3.1.1 Acquisition of data images and description of labels The […]
Tag: mnist
BadNets: Model backdoor attack code (Pytorch) based on data poisoning, taking MNIST as an example
Load data set # Load MNIST training set and test set transform = transforms.Compose([ transforms.ToTensor(), ]) train_loader = datasets.MNIST(root=’data’, transform=transform, train=True, download=True) test_loader = datasets.MNIST(root=’data’, transform=transform, train=False) # Visualization sample size 28×28 plt.imshow(train_loader.data[0].numpy()) plt.show() Implant 5,000 poisoned samples in the training set # Implant 5000 poisoned samples into the training set for i in range(5000): […]
Touge-Using PyTorch to train convolutional neural networks on the MNIST dataset
Level 1: Use PyTorch to build a network model import argparse import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from torchvision import datasets, transforms from torch.optim.lr_scheduler import StepLR class Net(nn.Module): def __init__(self): super(Net, self).__init__() self.conv1 = nn.Conv2d(1, 10, kernel_size=5) self.conv2 = nn.Conv2d(10, 20, kernel_size=5) self.fc1 = nn.Linear(320, 50) self.fc2 […]
Implement mnist handwritten digit recognition
>- ** This article is the learning record blog in [365-day deep learning training camp](https://mp.weixin.qq.com/s/Nb93582M_5usednAKp_Jtw)** >- ** Original author: [Classmate K | Tutoring, project customization](https://mtyjkh.blog.csdn.net/)** >- ** Article source: [Student K’s study circle](https://www.yuque.com/mingtian-fkmxf/zxwb45)** 1. Preparation 1. Set CPU If the device supports GPU, use GPU, otherwise use CPU import torch import torch.nn as nn import […]
Python Mnist handwritten multi-digit recognition based on paddleocr2.7.0
Directory of series articles Chapter 1 Python Mnist handwritten multi-digit recognition based on paddleocr2.7.0 Article directory Table of Contents of Series Articles Preface 1. Install PaddleOCR 2. Configuration environment 3. Create a handwritten digit data set 1. Splicing data sets Splicing the data set from 0-99: 2.Data display 4. Training model 1. Download the pre-trained […]
Example 1: FashionMNIST in action
Introduction: Different from MINST, MINST is some numbers, used for digital recognition, while FashionMNIST includes hats, skirts, etc., which are about all types of clothing. Compared with the MNIST data set, it is more complex, but the image is still [28,28]. The article begins. Give the complete code and then explain it. 1. Complete code […]
Taking MNIST handwritten digit recognition as an example to customize gradient descent (MindSpore framework)
1. Principle introduction The formula that defines gradient descent is as follows: Where w represents the parameter value to be updated, t represents the number of iteration rounds, learning_rate represents the learning rate, and J(w) represents the objective function. Assume that in the t-th iteration, w is located at the position pointed by the red […]
Solving FileNotFoundError: [Errno 2] No such file or directory: ./data\mnist\train-images-idx3-ubyte
Table of Contents Solving FileNotFoundError: [Errno 2] No such file or directory: ./data\mnist\train-images-idx3-ubyte 1. Check the file path 2. Make sure the file exists 3. Check file permissions 4. Make sure the dataset is downloaded 5. Check file paths in code Practical application scenarios Sample code Solving FileNotFoundError: [Errno 2] No such file or directory: […]
Solving PermissionError: [Errno 13] Permission denied: ./data\mnist\train-images-idx3-ubyte
Table of Contents Problem Description wrong reason solution 1. Check file and directory permissions 2. Change the user or group to which the file belongs 3. Run the program with administrator privileges 4. Change file path 5. Use the os module to set file permissions in conclusion Data set composition Dataset content Dataset purpose Data […]
mnist handwritten digit recognition—–the focus here is on understanding the preprocessing of images
import tensorflow as tf from tensorflow.keras import datasets,models,layers # Import data (train_images,train_labels),(test_images,test_labels) = datasets.mnist.load_data() type(train_images) numpy.ndarray train_images.shape (60000, 28, 28) # Data normalization processing, normalize the pixel value to the range from 0 to 1. train_images, test_images = train_images /255, test_images/255 train_images.shape,test_images.shape,train_labels.shape,test_labels.shape ((60000, 28, 28), (10000, 28, 28), (60000,), (10000,)) # Image visualization import matplotlib.pyplot […]