Click on the above“Beginner Learning Vision” to selectStar or “Pin” Heavyweight content delivered first-hand Originally published by | Machine Learning AI Algorithm Engineer The link to the VOC dataset used is provided in the article, the pre-trained model has been uploaded to GitHub, and I used Colab Pro for the environment, everyone can download the … Read more
Click the above “Beginner’s Guide to Vision” and choose to add a Star or “Top” Essential content delivered promptly Introduction This article summarizes important points to consider when implementing checkpoint resume training with PyTorch, along with detailed code explanations. Recently, while trying to train a classification problem using CIFAR10, I found that the dataset is … Read more
Click on the above “Beginner’s Guide to Vision” to choose to add “Star” or “Pin“ Important content delivered promptly Author: Alxander@Zhihu (authorized) Source: https://zhuanlan.zhihu.com/p/448284000 Editor: Jishi Platform Jishi Guide During the training process in deep learning, due to random initialization and the randomness of sample reading, repeated experimental results may differ, with some variations being … Read more
Click the "Xiao Bai Learns Vision" above, select to "star" or "top" Heavy content delivered immediately Author丨Civ@Zhihu (Authorized) Source丨https://www.zhihu.com/question/66532235/answer/2782357337 Editor丨Jishi Platform Jishi Guide This article uses the C++ inference framework ncnn as an example to introduce the general deployment process. The approach is similar for other C++ inference frameworks; the only learning cost is the … Read more
Kaggle Competition Tips Author:William Falcon, Source: AI Park Introduction Some small details can indeed improve speed. Over the past 10 months, during my work with PyTorch Lightning, the team and I have encountered many styles of structuring PyTorch code, and we have identified some key places where people inadvertently introduce bottlenecks. We are very careful … Read more
Using data augmentation techniques can increase the diversity of images in the dataset, thereby improving the performance and generalization ability of the model. The main image augmentation techniques include: Resizing Grayscale Transformation Normalization Random Rotation Center Cropping Random Cropping Gaussian Blur Brightness and Contrast Adjustment Horizontal Flip Vertical Flip Gaussian Noise Random Blocks Central Region … Read more
Click on "Xiaobai Learns Vision" above, select to add "Star" or "Top" Heavyweight content delivered first License Plate Recognition Overview License plate recognition based on deep learning, where the vehicle detection network directly uses YOLO for detection. Then, a network is used to detect and recognize the license plate number. The license plate detection network … Read more
Click on "Xiaobai Studies Vision" above, select to add "Star" or "Top" Heavy content, delivered first time For academic sharing only, does not represent the position of this public account. Contact for deletion if infringing. Reprinted from:Source | Jishi Platform Author | Jack Stark@Zhihu The best resource for PyTorch is the official documentation. This article … Read more
This article is approximately 1800 words long and is recommended to be read in 5 minutes. This article will deeply introduce the 7 core functions of the torch.utils.data module in PyTorch, which can help you better manage and manipulate data. In machine learning and deep learning projects, data processing is a crucial part. PyTorch, as … Read more
This article was compiled by a PhD student from Harbin Institute of Technology over the course of six months, consisting of a total of fourteen chapters. It starts with the basics of creating tensors and gradually deepens, covering almost all commonly used functions! [From Beginner to Pro in PyTorch, AI Deep Learning Neural Network Learning … Read more