Programmer Think

The code for processing data samples may become chaotic and difficult to maintain; We ideally want our Dataset code to be separated from our model training code for better readability and modularity. PyTorch provides two data primitives: torch utils. data. DataLoader and torch utils. data. Datasets, which allow you to use preloaded datasets ...

[source code analysis] PyTorch distributed elastic training (4) - Rendezvous architecture and logic 0x00 summary In the previous article, we have learned the basic modules of PyTorch distribution and introduced several official examples. Next, we will introduce the flexibility training of PyTorch. This is the fourth article to see the str ...

1. Installing anaconda3 1.1 download anaconda3 Directly in Official website Slow down, recommended Tsinghua mirror (you can also change the source of Pip to domestic, and pip install will be much faster) In the latest date, select an Anaconda3 installation package corresponding to your system version, x86_64 means compatible with 32-bi ...

Pytorch autoencoder (self coding, unsupervised learning) 1, Compression and decompression There is a neural network. What it is doing is receiving a picture, then coding it, and finally restoring it from the coded picture Assuming that the neural network is like this, corresponding to the picture just above, we can see that the picture is ...

catalogue preface step 1. Download yolov5 source code and tensorrtx source code, and download yolov5s Pt to wts modelstep 2. Install cuDNN, TensorRT and verify that TensorRT is installed successfullystep 3. https://github.com/wang-xinyu Use vs to run through the C + + code of yolov5.0 in githubstep 4. Running your own training modelsumm ...

preface The article is linked to: Detailed analysis of YOLO-V3-SPP This paper mainly explains the processing of YoloV3-SPP in the verification reasoning stage, which is divided into the following points: Preprocessing dataProcessing of validationReasoning NMS processingdrawbox for visualization of reasoning results For the calculation of map ...

Neural networks consist of layers / modules that perform operations on data. torch.nn Namespace provides all the building blocks needed to build your own neural network. Each module in PyTorch is nn.Module Subclass of. Neural network is a module itself, which is composed of other modules (layers). This nested structure allows easy construct ...

I Introduction to ResNet algorithm Residual neural network (ResNet) was proposed by he Kaiming of Microsoft Research Institute. ResNet won the championship in ILSVRC in 2015. Through experiments, ResNet has continuously improved the accuracy of the model with the deepening of the network layer, Reach the maximum (accuracy saturation), and the ...

1. Project source (1) Thesis title The reproduced paper: Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks , the original author implemented the algorithm using Matlab. (2) Achieve goals The task of this time is based on the pytoch implementation of this paper, which is reproduced using Baidu paste past ...

1. Cosine similarity from PIL import Image from numpy import average, linalg, dot def get_thumbnail(image, size=(30, 30), greyscale=False): image = image.resize(size, Image.ANTIALIAS) if greyscale: image = image.convert('L') return image def image_similarity_vectors_via_numpy(image1, image2): image1 = get_thumbnail( ...