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catalogue Tool function cv::alignPtr() cv::alignSize() cv::allocate() cv::deallocate() cv::fastAtan2() cv::cubeRoot() cv::CV_Assert() & cv::CV_DbgAsser() cv::error() cv::CV_Error() & cv::CV_Error_() cv::fastFree() cv::fastMalloc() cv::format() cv::getCPUTickCount() cv::getNumThreads() cv::getOptimalDFTSize() cv::getTh ...

Ruiluo medical reference resources: Using paddlehub to realize video face changing - Propeller AI Studio - artificial intelligence learning and training community Change your face, Cang * Kong becomes Zhao * Ying, single welfare (understand all), get on the bus quickly. Just kidding, it's purely for technical learning and communication. 1. ...

Content introduction This paper introduces cluster analysis with a simple example of Python using Keans for cluster analysis. Cluster analysis or clustering is the task of grouping a group of objects, Make objects in the same group (called clusters) more similar (in a sense) to objects in other groups (clusters) It is the main task of exp ...

Module 1Modules can be regarded as a collection of functions.A stack of functions can be placed inside a py file, so a py file can be regarded as a module.If the file name of this py file is {module Py, and the module name is "module".1. Four forms of modulesIn Python, there are four types of modules:Custom module: if you write a py f ...

Rimeng Society AI AI:Keras PyTorch MXNet TensorFlow PaddlePaddle deep learning real combat (irregular update) Encoder Decoder framework + Attention mechanism Pytoch: Transformer(Encoder Decoder decoder, multi head attention mechanism, multi head self attention mechanism, mask tensor, feedforward full connection layer, normalization layer, ...

Linear algebra and code implementation (I) vector background The Linear Algebra I studied in university is a little forgotten now, and I am not proficient in the code implementation; This column mainly reviews the basis of linear algebra and implements the code part; 1. Some basic concepts Essence: the basic expression of a group of numbers ...

catalogue 1, Basic theory 1. Thought 2. Principle 2, Process Step induction 1. Convert the original image to binary image 2. Open operation denoising 3. Determine the background area (expansion) (get the background / maximum pass area) 4. Determine foreground area (distance transformation) (separation) (get seed / foreground) 5. U ...

%matplotlib inline import numpy as np import pandas as pd from scipy import stats, integrate from warnings import filterwarnings filterwarnings('ignore') import matplotlib as mpl import matplotlib.pyplot as plt import seaborn as sns sns.set(color_codes=True) np.random.seed(sum(map(ord, "distributions"))) Univariate distribution Grayscal ...

As data scientists or machine learning practitioners, integrating interpretability into machine learning models can help decision makers and other stakeholders have more visibility and understand the interpretation of model output decisions.In this article, I will introduce two models, life and shake, which can help understand the decision-maki ...

preface The pioneering work of the VIT model is to use a pure transformer structure, as shown in the title of the paper: AN IMAGE IS WORTH 16X16 WORDS, which embeds the pictures into a series of sequence s, and realizes the effect comparable to the SOTA model in CNN through multiple encoder structures and head s. Image classification t ...