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AI图像生成炼丹术一窥:如何轻松掌握AI绘画工具(上篇)

发布于 2023-04-28

<section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp;&nbsp; &nbsp;</span><img class="rich_pages wxw-img" data-galleryid="" data-ratio="0.6725571725571725" data-s="300,640" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gt1w8qJp0zZSsjAgc61LPS9jEiclJbWzylEEdy9ibNCph2KJuEqEeM6cQ/640?wx_fmt=png" data-type="png" data-w="962" style="text-align: center;letter-spacing: 0.034em;" /></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;letter-spacing: 0.034em;">引言</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">最近经常听说一种奇异的技术,它能够用文字来创造图像,<strong>让人们的想象力得以可视化,这是一种什么技术?</strong></span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="color: rgb(255, 255, 255);background-color: rgb(0, 122, 170);"><strong><span style="font-size: 16px;">AI: </span></strong></span><span style="font-size: 16px;">这种技术是人工智能的一种应用,它利用了深度学习的方法,让机器能够根据人们输入的文字,自动生成与之相符的图像。这种技术不仅能够满足人们的好奇心和创造力,也能够在各个领域发挥作用,比如教育、娱乐、设计、医疗等。</span></section><section style="margin-left: 16px;margin-right: 16px;"><strong><span style="font-size: 16px;letter-spacing: 0.034em;">我想知道,这种技术是怎样实现的,又有哪些不同的方式呢?</span></strong></section><section style="margin-left: 16px;margin-right: 16px;"><span style="color: rgb(255, 255, 255);background-color: rgb(0, 122, 170);"><strong><span style="background-color: rgb(0, 122, 170);font-size: 16px;">AI:</span></strong></span><span style="font-size: 16px;">我将为你介绍两种主要的技术:生成对抗网络(GAN)和扩散模型(Diffusion),它们各自有什么特点和优劣,又有什么历史和前景。同时,本文还将教读者如何使用目前流行的技术工具,轻松掌握AI绘画。我们将把这个过程比作学习炼丹术,而这些工具就是不同等级的炼丹炉。你是否感兴趣呢?如果感兴趣,就请跟我一起走进这个神秘而奇妙的世界吧!</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">&nbsp;&nbsp;</span></section><section style="text-align: center;margin-left: 16px;margin-right: 16px;"><span style="color: rgb(136, 136, 136);font-size: 16px;text-align: center;letter-spacing: 0.034em;">&nbsp;– 以下文字皆为AI,小编配图 –</span></section><section style="text-align: center;margin-left: 16px;margin-right: 16px;"><br /></section><section style="margin-left: 16px;margin-right: 16px;"><br /></section><section style="margin-left: 16px;margin-right: 16px;"><span style="color: rgb(0, 0, 0);font-size: 50px;">01</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 18px;"><strong><span style="color: rgb(0, 0, 0);">模型介绍</span></strong></span></section><section style="margin-left: 16px;margin-right: 16px;"><strong style="letter-spacing: 0.034em;color: rgb(0, 122, 170);"><span style="font-size: 16px;">两种“炼丹炉”的发展历程及优缺点</span></strong></section><section style="margin-left: 16px;margin-right: 16px;"><span style="color: rgb(0, 122, 170);"><strong><span style="font-size: 16px;">1)生成对抗网络</span></strong></span><span style="font-size: 16px;">(GAN)是一种让机器自己创造新的图片的技术,它在2014年由Ian Goodfellow等人发明,引起了很多人的关注。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">GAN的基本想法是让一个机器(生成器)根据给定的一些随机或文字信息,创造出看起来像真的图片,而另一个机器(判别器)则负责检查这些图片是不是真的,从而给出反馈信号来指导生成器不断改进。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">这类似GAN有两个部分:一个是画家,它学会根据一些随机杂点画出似是而非的图片;另一个是鉴赏家,它负责评价这些图片的真实性,并给出反馈信号来指导画家不断提高。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"><span style="color: rgb(0, 122, 170);"><strong>这是一个类似于“画家与鉴赏家”的游戏</strong></span>,通过不断地互相挑战,最终达到一个平衡点,即画家可以画出骗过鉴赏家的图片,而鉴赏家无法分辨真假。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-backh="185" data-backw="278" data-cropselx1="0" data-cropselx2="546" data-cropsely1="0" data-cropsely2="362" data-ratio="0.6273653566229985" data-src="https://mmbiz.qpic.cn/mmbiz_jpg/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gPuzRNSv4iceqOxePsPfVJ2cfFyiaPSs9lUJekYMMjbP1c04LF1UzdeQg/640?wx_fmt=jpeg" data-type="png" data-w="687" style="width: 577px;height: 362px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">&nbsp;</span><span style="color: rgb(0, 122, 170);"><strong><span style="font-size: 16px;letter-spacing: 0.034em;">GAN在创造图片方面有着很多有趣和有用的应用,比如改变图片的风格、提高图片的清晰度、给黑白图片上色、修改图片的内容、根据文字生成图片等。</span></strong></span><span style="font-size: 16px;letter-spacing: 0.034em;"></span></section><section style="margin-left: 16px;margin-right: 16px;"><strong><span style="font-size: 16px;">人脸生成</span></strong><span style="font-size: 16px;">:根据人脸数据集来生成逼真的人脸图像,甚至可以控制人脸的属性,如年龄,性别,发型等。此图中都是不存在的人脸。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-backh="397" data-backw="398" data-cropselx1="0" data-cropselx2="398" data-cropsely1="0" data-cropsely2="397" data-ratio="0.9949494949494949" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gNqw5zWJbCn2eRLVEiaWYt8HtEBPfDSK6Of2c8mGFtvcqexy1rib00h0A/640?wx_fmt=png" data-type="png" data-w="396" style="width: 100%;height: auto;" /></section><section style="margin-left: 16px;margin-right: 16px;"><br /></section><section style="margin-left: 16px;margin-right: 16px;"><strong><span style="font-size: 16px;">风格迁移</span></strong><span style="font-size: 16px;">(styleGAN):将一种风格的图像转换为另一种风格的图像,例如将照片变成油画或素描。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="letter-spacing: 0.034em;font-size: 16px;">&nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f" style="letter-spacing: 0.034em;"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="293" data-ratio="0.5063613231552163" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gib3wNLK1jKrRskJibLgmykBUibyKibzh7ISLx6dUhw7IzPcyXh7hhSrib1w/640?wx_fmt=png" data-type="png" data-w="786" style="letter-spacing: 0.034em;width: 578px;height: 292px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><strong><span style="font-size: 16px;">图像增强</span></strong><span style="font-size: 16px;">:对低分辨率或模糊的图像进行超分辨率或去噪处理,使图像更清晰和细致。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="282" data-ratio="0.4888888888888889" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3g0piaX6M9wP5593ee2vJwNLmabcsachRwTFO1IJ0XgqZHwRpCBbFjyVw/640?wx_fmt=png" data-type="png" data-w="1080" style="width: 578px;height: 283px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><strong><span style="font-size: 16px;">图像编辑</span></strong><span style="font-size: 16px;">:对图像进行局部修改或添加,例如改变背景,添加物体或文字等。</span></section><section style="margin-left: 16px;margin-right: 16px;"><strong><span style="font-size: 16px;">文字到图像</span></strong><span style="font-size: 16px;">:由文字描述生成相应的图像。</span></section><section style="text-align: center;margin-left: 16px;margin-right: 16px;"><img class="rich_pages wxw-img" data-galleryid="" data-ratio="0.9541984732824428" data-s="300,640" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gPaM8MPtLK35CMOYjMG5GL4KHcicWZ4OHklxNGrSWOhoZwGM0AXmpiaYA/640?wx_fmt=png" data-type="png" data-w="786" style="" /></section><section style="margin-left: 16px;margin-right: 16px;"><br /></section><section style="margin-left: 16px;margin-right: 16px;"><strong><span style="font-size: 16px;">图像修复</span></strong><span style="font-size: 16px;">:对缺失或损坏的图像进行修复或填充,例如修复老照片或涂鸦等。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-backh="243" data-backw="490" data-cropselx1="0" data-cropselx2="490" data-cropsely1="0" data-cropsely2="243" data-ratio="0.49504950495049505" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3goIyL0ziarqZUECw3eBLbaCpaO6ibGtYHox6FLVPBWeOWyoiaj58r6FF3A/640?wx_fmt=png" data-type="png" data-w="707" style="width: 100%;height: auto;" /></section><section style="margin-left: 16px;margin-right: 16px;"><strong><span style="font-size: 16px;">动画生成</span></strong><span style="font-size: 16px;">:根据动画数据集来生成动画角色或场景,甚至可以生成动画视频。</span></section><section style="text-align: center;margin-left: 16px;margin-right: 16px;"><img class="rich_pages wxw-img" data-galleryid="" data-ratio="0.7554945054945055" data-s="300,640" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gndAFMicdneWg1UCYdicpST3AVpBAHzH4cHkSARJo6iaBQnSnFckRMU27Q/640?wx_fmt=png" data-type="png" data-w="728" style="" /></section><section style="text-align: center;margin-left: 16px;margin-right: 16px;"><br /></section><section style="margin-left: 16px;margin-right: 16px;"><strong><span style="font-size: 16px;">GAN发展时间线</span></strong></section><section style="text-align: center;margin-left: 16px;margin-right: 16px;"><img class="rich_pages wxw-img" data-cropselx1="0" data-cropselx2="546" data-cropsely1="0" data-cropsely2="373" data-galleryid="" data-ratio="0.6786542923433875" data-s="300,640" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3g1Pb0zeicYOsHQU1xJdSKAxQ8sP13FicicDK3G6TFWibyfZvydkqwe0OIjw/640?wx_fmt=png" data-type="png" data-w="862" style="width: 550px;height: 373px;"></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">然而,GAN也遇到了很多困难和问题,比如生成器学习不到足够的信息、生成器只能创造出一些简单的图片、生成器和判别器难以协调、难以判断什么时候停止学习等。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"><br />为了解决这些问题,很多人提出了很多改进的GAN设计和方法,比如DCGAN、StyleGAN、BigGAN、StackGAN、Pix2pix、Age-cGAN、CycleGAN等,它们在不断迭代,也在各自的路线上发展出不同的细化功能。这些设计在不同的任务和数据上展示了GAN的强大能力和潜力。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"><br /></span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="color: rgb(0, 122, 170);"><strong><span style="font-size: 16px;"><strong style="color: rgb(0, 122, 170);letter-spacing: 0.578px;white-space: normal;"><span style="font-size: 16px;">2</span></strong>)扩散模型</span></strong></span><span style="font-size: 16px;">(Diffusion Model)是一种让机器自己画出新的图片的技术,它在2015年提出,受热力学原理启发,但直到2020年逐渐才引起大量关注。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">扩散模型的主要想法是让一个机器(画家)根据给定的一些随机杂点,逐步去掉杂点,画出看起来像真的图片,它不需要额外训练一个鉴赏家,而是通过一个简单的前向过程和一个逆向过程来实现图像合成。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-backh="195" data-backw="335" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="337" data-ratio="0.5843881856540084" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gdYZeTLvSyyRuEvYBKqd04094UNibBskic6ItELLDF77rQ7tXL3CrFDPw/640?wx_fmt=png" data-type="png" data-w="474" style="width: 578px;height: 338px;"></section><section style="margin-left: 16px;margin-right: 16px;"><br /></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">扩散模型的训练过程,可以用这个例子理解下,将一张猫图逐步加噪声,直到变成一幅完全噪声的图片,过程中记录变化的噪声参数,生成过程就是反向去噪的过程。</span><span style="letter-spacing: 0.034em;font-size: 16px;">&nbsp;&nbsp;</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="letter-spacing: 0.034em;font-size: 16px;">&nbsp;&nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f" style="letter-spacing: 0.034em;"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-croporisrc="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gOPQT67OI1a1YEAfdkvNgahIBXn4gENQNSKaXZw067hqgSpzq2wBxcA/640?wx_fmt=png" data-cropx1="0" data-cropx2="1080" data-cropy1="93.42560553633218" data-cropy2="541.8685121107267" data-ratio="0.41388888888888886" data-src="https://mmbiz.qpic.cn/mmbiz_jpg/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gThiaHdpy3vRmx2oTgWLicpFVQXPf7L1BGg59T0lh4kb0HVicufAJhWQ4g/640?wx_fmt=jpeg" data-type="jpeg" data-w="1080" style="letter-spacing: 0.034em;width: 578px;height: 240px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">Diffusion模型的发展时间线大致如下:</span></section><section style="text-align: center;margin-left: 16px;margin-right: 16px;"><img class="rich_pages wxw-img" data-backh="674" data-backw="349" data-cropselx1="0" data-cropselx2="546" data-cropsely1="0" data-cropsely2="1054" data-galleryid="" data-ratio="0.8530424799081515" data-s="300,640" data-src="https://mmbiz.qpic.cn/mmbiz_jpg/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gajibnodXWRicSo8XEPa6Is0oTXDM8TxJibWYbPcj7DzymkMspic3OvtdMw/640?wx_fmt=jpeg" data-type="jpeg" data-w="871" style="width: 578px;height: 493px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;letter-spacing: 0.034em;">扩</span><span style="font-size: 16px;letter-spacing: 0.034em;">散模</span><span style="font-size: 16px;letter-spacing: 0.034em;">型在画图方面有着很多有趣和有用的应用,比如根据文字画出图片、改变图片的风格、提高图片的清晰度、修改图片的内容等。</span><br /></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">然而,diffusion也遇到了很多困难和问题,比如画家需要很多步骤才能画出图片、画家和鉴赏家难以协调、难以判断什么时候停止去掉杂点等。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">为了解决这些问题,很多人提出了很多改进的diffusion设计和方法,比如稳定版diffusion、去噪版diffusion、基于分数版diffusion等。这些设计在不同的任务和数据上展示了diffusion的强大能力和潜力。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;<br /></span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="color: rgb(0, 122, 170);"><strong><span style="font-size: 16px;">3)两种模型的比较</span></strong></span><span style="font-size: 16px;"></span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-cropselx1="0" data-cropselx2="514" data-cropsely1="0" data-cropsely2="426" data-ratio="0.828125" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3g0p4TgLDxibEzgSYkHMTBeosuCl9QfQShvYRNaoQzhfNEObtGv4FrwIg/640?wx_fmt=png" data-type="png" data-w="512" style="width: 514px;height: 426px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">生成对抗网络和扩散模型各有优缺点——GAN在图像合成方面有着很多有趣和有用的应用,比如根据文字画出图片、改变图片的风格、修改图片的内容等。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">然而,GAN也面临着许多挑战和问题,比如画家和鉴赏家难以协调、训练过程不稳定、生成结果缺乏多样性等。为了解决这些问题,很多人提出了很多改进的GAN设计和方法,比如WGAN、CGAN、StyleGAN等。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">Diffusion在图像生成领域有着广泛的应用和创新,比如根据文字生成图片、改变图片的风格、提高图片的清晰度、修改图片的内容等。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">Diffusion相比GAN往往有更加稳定的训练过程、更加简单的目标函数、更加丰富的数据理论。然而,Diffusion也有一些局限性,比如生成速度较慢、需要很多步骤才能恢复出图片、难以处理高分辨率的图片等。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">为了解决这些问题,很多人提出了很多改进扩散模型的设计和方法,比如stable diffusion、denoising diffusion probabilistic models、score-based generative models等。近来大火的Midjourney据说是融合了GAN和Diffusion的优点,使得生成的图像质量和可控性达到较好的平衡。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;<br /></span></section><section style="letter-spacing: 0.578px;white-space: normal;margin-left: 16px;margin-right: 16px;"><span style="color: rgb(0, 0, 0);font-size: 50px;">02</span></section><section style="letter-spacing: 0.578px;white-space: normal;margin-left: 16px;margin-right: 16px;"><span style="font-size: 18px;"><strong><span style="color: rgb(0, 0, 0);">模型应用</span></strong></span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">那么,“炼丹炉”准备好了,可以开始“炼丹”了。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;letter-spacing: 0.034em;">先看几个其他人的“炼丹”结果,图片下方就是提示语,我们可以由学习他人的案例开始。</span></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-backh="410" data-backw="318" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="745" data-ratio="1.288888888888889" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gliaGXOxaXtzic8lQM0dazjN77BNxTpqiaDGIAXQwickCL6LhBl6hjyvdbA/640?wx_fmt=png" data-type="png" data-w="315" style="width: 578px;height: 745px;" /><span style="letter-spacing: 0.034em;font-size: 16px;">&nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f" style="letter-spacing: 0.034em;"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-backh="394" data-backw="318" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="718" data-ratio="1.2412698412698413" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3glNIwkxxgbJWtJiaSay0ibj4gp2gKSHG2I8DYdsI5sPLz5Eib41vTDjoZg/640?wx_fmt=png" data-type="png" data-w="315" style="letter-spacing: 0.034em;width: 578px;height: 718px;" /><span style="letter-spacing: 0.034em;font-size: 16px;">&nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</span><v:shapetype coordsize="21600,21600" xmlns:o="urn:schemas-microsoft-com:office:office" o:spt="75" path="m@4@5l@4@11@9@11@9@5xe" o:preferrelative="t" filled="f" stroked="f" style="letter-spacing: 0.034em;"><v:formulas><v:f eqn="if lineDrawn pixelLineWidth 0"></v:f><v:f eqn="sum @0 1 0"></v:f><v:f eqn="sum 0 0 @1"></v:f><v:f eqn="prod @2 1 2"></v:f><v:f eqn="prod @3 21600 pixelWidth"></v:f><v:f eqn="prod @3 21600 pixelHeight"></v:f><v:f eqn="sum @0 0 1"></v:f><v:f eqn="prod @6 1 2"></v:f><v:f eqn="prod @7 21600 pixelWidth"></v:f><v:f eqn="sum @8 21600 0"></v:f><v:f eqn="prod @7 21600 pixelHeight"></v:f><v:f eqn="sum @10 21600 0"></v:f></v:formulas><v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"></v:path></v:shapetype><img class="rich_pages wxw-img" data-backh="407" data-backw="318" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="737" data-ratio="1.2753164556962024" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3g2y21HNuUoL16NYNibPicAjnz0VIhfZibnm7lSmvYry1iaiaFlDzprfg3OmA/640?wx_fmt=png" data-type="png" data-w="316" style="letter-spacing: 0.034em;width: 578px;height: 737px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><img class="rich_pages wxw-img" data-backh="486" data-backw="325" data-cropselx1="0" data-cropselx2="325" data-cropsely1="0" data-cropsely2="486" data-ratio="1.4968944099378882" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gX5KOWG4Gy1wP9dBDUSzD6mANeHSSnBgBsElhLGQMkf8XEjS19lv7rQ/640?wx_fmt=png" data-type="png" data-w="322" style="letter-spacing: 0.034em;width: 100%;" /></section><section style="margin-left: 16px;margin-right: 16px;"><img class="rich_pages wxw-img" data-backh="548" data-backw="317" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="999" data-ratio="1.7292993630573248" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3geDKkiaBBO9NzGftNxcERF265nqBwIb05ddxcs0QKs8SwBKiaEunvFibsg/640?wx_fmt=png" data-type="png" data-w="314" style="width: 578px;height: 1000px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><img class="rich_pages wxw-img" data-backh="558" data-backw="328" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="983" data-ratio="1.7015384615384614" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3grsLtWAibSwbgnctl37Gu0RDW9bHtfAvicDR8u6icFS5fRMYnaVibjDRJFQ/640?wx_fmt=png" data-type="png" data-w="325" style="width: 578px;height: 983px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><img class="rich_pages wxw-img" data-backh="548" data-backw="321" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="987" data-ratio="1.7075471698113207" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gdnBofpNNo5zKKHKNpV3Tw2fLcFIfxphZecDJ1GRgL2Y8AeNfrBqiaSA/640?wx_fmt=png" data-type="png" data-w="318" style="width: 578px;height: 987px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><img class="rich_pages wxw-img" data-backh="494" data-backw="316" data-cropselx1="0" data-cropselx2="578" data-cropsely1="0" data-cropsely2="905" data-ratio="1.5654952076677315" data-src="https://mmbiz.qpic.cn/mmbiz_png/AJkYaTAujIxIAGex3RBoLNJDd5NY6Y3gCV31QQ83GKASEbaV0ypoH8pqIT5tr2gDZA45N8ibLEicKLSF83uyYIwg/640?wx_fmt=png" data-type="png" data-w="313" style="width: 578px;height: 905px;" /></section><section style="margin-left: 16px;margin-right: 16px;"><br /></section><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;">下篇会详细说说炼丹过程,先放几个写<span style="font-size: 16px;color: rgb(0, 122, 170);"><strong>提示语的窍门</strong></span>在这里,这是用midjourney生成图像的提示语的一些窍门:</span></section><ul class="list-paddingleft-1" style="list-style-type: disc;margin-left: 16px;margin-right: 16px;"><li><p><strong><span style="font-size: 16px;">尽量使用简单,明确,具体的词语,避免模糊,抽象,复杂的词语。</span></strong></p></li><li><p><strong><span style="font-size: 16px;">尽量使用名词,形容词,颜色,数字等描述图像的特征,避免使用动词,副词,连词等描述图像的动作或关系。</span></strong></p></li><li><p><strong><span style="font-size: 16px;">尽量使用逗号分隔不同的特征,避免使用句号或其他标点符号。</span></strong></p></li><li><p><strong><span style="font-size: 16px;">尽量使用常见的图像主题,避免使用太奇怪或太难画的图像主题。</span></strong><span style="font-size: 16px;"></span></p></li></ul><section style="margin-left: 16px;margin-right: 16px;"><span style="font-size: 16px;"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;<br /></span></section><section data-role="paragraph" style="white-space: normal;box-sizing: border-box;margin-bottom: 0px;"><section style="max-width: 100%;font-family: -apple-system, BlinkMacSystemFont, &quot;Helvetica Neue&quot;, &quot;PingFang SC&quot;, &quot;Hiragino Sans GB&quot;, &quot;Microsoft YaHei UI&quot;, 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