示例$(async () => {//绘画const canvas = document.getElementsByClassName('cvs')[0];canvas.addEventListener('mousemove', (e) => {if (e.buttons === 1) {const ctx = canvas.getContext('2d');ctx.fillStyle

示例import $ from 'jquery';import * as tf from '@tensorflow/tfjs';import * as tfvis from '@tensorflow/tfjs-vis';import { getInputs, img2x, file2img } from './utils.js';$(async () => {const { inputs,

t1.jsconst tf = require('@tensorflow/tfjs-node-gpu');const getData = require('./data');const TRAIN_PATH = './垃圾分类/垃圾分类/train';const OUT_PUT = 'output';const MOBILENET_URL = 'http://127.0.0.1:8080/data

示例1window.onload = async () => {const xs = [1, 2, 3, 4];const ys = [1, 3, 5, 7];tfvis.render.scatterplot({ name: "线性回归" },{ values: xs.map((x, i) => ({ x, y: ys[i] })) },{ xAxisDomain: [0, 5], y

示例$(async () => {$('#sf').on('submit', function () {console.log($('#sf #x').val(), $('#sf #y').val());if (window.predict) {window.predict({ x: $('#sf #x').val(), y: $('#sf #y').val() });} else {ale

图标识别import $ from 'jquery';import * as tf from '@tensorflow/tfjs';import { img2x, file2img } from './utils.js';const MODEL_PATH = 'http://127.0.0.1:8080';const BRAND_CLASSES = ['android', 'apple', 'wi

示例$(async () => {//绘画const canvas = document.getElementsByClassName('cvs')[0];canvas.addEventListener('mousemove', (e) => {if (e.buttons === 1) {const ctx = canvas.getContext('2d');ctx.fillStyle

实现RAG将pdf文档内容添加到向量数据库进行向量检索时，表格等数据无法识别，可以先用多模态模型对数据进行提取，然后再添加到向量数据中。这样做查询时用文本向量模型就够了。对pdf中所有页面进行截图，手动指定了一张图片，对这个图片中数据进行了提取。

【代码】基于nodejs中@lang/graph框架实现workflow。

#include<iostream>#include<vector>#include<algorithm>#include<functional>#include<string>using namespace std;void test01() {vector<int> v1;for (int i = 1; i <= 1