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1. Introduction to datasets: UCF101 is a motion recognition dataset for real action videos collected on YouTube and provides 13320 videos from 101 action categories. Official website: https://www.crcv.ucf.edu/research/data-sets/ucf101/ Dataset name: UCF-101 (2012)Total Videos: 13,320 VideosTotal duration: 27 hoursVideo source: YouTube col ...

Data loading in pytoch In deep learning, the amount of data is usually very large. With such a large amount of data, it is impossible to carry out forward calculation and back propagation in the model at one time. Often, we will randomly disrupt the order of the whole data, process the data into batch es one by one, and preprocess the data at ...

PyTorch multi card distributed training DistributedDataParallel catalogue PyTorch multi card distributed training DistributedDataParallel 1.DP mode and DP mode (1) Single process multi GPU training mode: DP mode (2) Multi process multi GPU training mode: DDP mode 2. Pytoch distributed training method 3. Python base trainer (PBT) distribu ...

abstract This example extracts some data from the plant seedling data set as the data set. The data set has 12 categories. It demonstrates how to use the mobile netv3 image classification model of pytorch version to realize the classification task. Through this article, you can learn: 1. How to download from torchvision Models call mobil ...

Summary This is a series of pytorch notes that follow station b. There are a lot of classified articles about renet model image recognition on the internet, but the image part is usually just a link to it. Or read a well-known article and prepared the dataset from scratch. One dataset preparation The dataset consists of 102 categories of flo ...

Early Stopping Brief Introduction When we train deep learning neural networks, we usually hope to obtain the best generalization performance. However, all standard deep learning neural network structures such as MLP are easy to over fit: when the error rate of the network in the training set is getting lower and lower, in fact, at a certa ...

Multilayer perceptron Both linear regression and softmax regression are single-layer neural networks. However, deep learning mainly focuses on multi-layer models. Taking multilayer perceptron (MLP) as an example, the concept of multilayer neural network is introduced. Hidden layer Multilayer perceptron introduces one or more hidden layer ...

Introduction to Mobilenet Traditional neural network has large memory demand and large amount of computation. Cannot run on mobile and embedded devices. Mobilenet focuses on lightweight CNN networks in mobile terminals or embedded devices (the accuracy is reduced by 0.9% compared with VGG16, but the model parameters are only VGG1/32) 1, ...

Variable Tensor is a perfect component in PyTorch, but building neural network is far from enough. We need tensor that can build calculation graph, which is variable. Variable is the encapsulation of tensor. The operation is the same as that of tensor, but each Variabel has three attributes, and the tensor itself in variable data, correspo ...

Author: baiyucraft BLog: baiyucraft's Home Original text: Hands on learning and deep learning 1, Differential and derivative    I believe everyone knows the concept. Draw a picture according to the book: import numpy as np from matplotlib import pyplot as plt def set_figsize(figsize=(3.5, 2.5)): """set up matplotlib The ...