基于 Serverless 架构的头像漫画风处理小程序
简介: 当一个程序员想要个漫画风的头像时...
前言
我一直都想要有一个漫画版的头像,奈何手太笨,用了很多软件 “捏不出来”,所以就在想着,是否可以基于 AI 实现这样一个功能,并部署到 Serverless 架构上让更多人来尝试使用呢?
后端项目
后端项目采用业界鼎鼎有名的动漫风格转化滤镜库 AnimeGAN 的 v2 版本,效果大概如下:
from PIL import Image import io import torch import base64 import bottle import random import json cacheDir = '/tmp/' modelDir = './model/bryandlee_animegan2-pytorch_main' getModel = lambda modelName: torch.hub.load(modelDir, "generator", pretrained=modelName, source='local') models = { 'celeba_distill': getModel('celeba_distill'), 'face_paint_512_v1': getModel('face_paint_512_v1'), 'face_paint_512_v2': getModel('face_paint_512_v2'), 'paprika': getModel('paprika') } randomStr = lambda num=5: "".join(random.sample('abcdefghijklmnopqrstuvwxyz', num)) face2paint = torch.hub.load(modelDir, "face2paint", size=512, source='local') @bottle.route('/images/comic_style', method='POST') def getComicStyle(): result = {} try: postData = json.loads(bottle.request.body.read().decode("utf-8")) style = postData.get("style", 'celeba_distill') image = postData.get("image") localName = randomStr(10) # 图片获取 imagePath = cacheDir + localName with open(imagePath, 'wb') as f: f.write(base64.b64decode(image)) # 内容预测 model = models[style] imgAttr = Image.open(imagePath).convert("RGB") outAttr = face2paint(model, imgAttr) img_buffer = io.BytesIO() outAttr.save(img_buffer, format='JPEG') byte_data = img_buffer.getvalue() img_buffer.close() result["photo"] = 'data:image/jpg;base64, %s' % base64.b64encode(byte_data).decode() except Exception as e: print("ERROR: ", e) result["error"] = True return result app = bottle.default_app() if __name__ == "__main__": bottle.run(host='localhost', port=8099)
整个代码是基于 Serverless 架构进行了部分改良的:
- 实例初始化的时候,进行模型的加载,已经可能的减少频繁的冷启动带来的影响情况;
- 在函数模式下,往往只有/tmp目录是可写的,所以图片会被缓存到/tmp目录下;
- 虽然说函数计算是“无状态”的,但是实际上也有复用的情况,所有数据在存储到tmp的时候进行了随机命名;
- 虽然部分云厂商支持二进制的文件上传,但是大部分的 Serverless 架构对二进制上传支持的并不友好,所以这里依旧采用 Base64 上传的方案;
上面的代码,更多是和 AI 相关的,除此之外,还需要有一个获取模型列表,以及模型路径等相关信息的接口:
import bottle @bottle.route('/system/styles', method='GET') def styles(): return { "AI动漫风": { 'color': 'red', 'detailList': { "风格1": { 'uri': "images/comic_style", 'name': 'celeba_distill', 'color': 'orange', 'preview': 'https://serverless-article-picture.oss-cn-hangzhou.aliyuncs.com/1647773808708_20220320105649389392.png' }, "风格2": { 'uri': "images/comic_style", 'name': 'face_paint_512_v1', 'color': 'blue', 'preview': 'https://serverless-article-picture.oss-cn-hangzhou.aliyuncs.com/1647773875279_20220320105756071508.png' }, "风格3": { 'uri': "images/comic_style", 'name': 'face_paint_512_v2', 'color': 'pink', 'preview': 'https://serverless-article-picture.oss-cn-hangzhou.aliyuncs.com/1647773926924_20220320105847286510.png' }, "风格4": { 'uri': "images/comic_style", 'name': 'paprika', 'color': 'cyan', 'preview': 'https://serverless-article-picture.oss-cn-hangzhou.aliyuncs.com/1647773976277_20220320105936594662.png' }, } }, } app = bottle.default_app() if __name__ == "__main__": bottle.run(host='localhost', port=8099)
可以看到,此时我的做法是,新增了一个函数作为新接口对外暴露,那么为什么不在刚刚的项目中,增加这样的一个接口呢?而是要多维护一个函数呢?
- AI 模型加载速度慢,如果把获取AI处理列表的接口集成进去,势必会影响该接口的性能;
- AI 模型所需配置的内存会比较多,而获取 AI 处理列表的接口所需要的内存非常少,而内存会和计费有一定的关系,所以分开有助于成本的降低;
关于第二个接口(获取 AI 处理列表的接口),相对来说是比较简单的,没什么问题,但是针对第一个 AI 模型的接口,就有比较头疼的点:
- 模型所需要的依赖,可能涉及到一些二进制编译的过程,所以导致无法直接跨平台使用;
- 模型文件比较大 (单纯的 Pytorch 就超过 800M),函数计算的上传代码最多才 100M,所以这个项目无法直接上传;
所以这里需要借助 Serverless Devs 项目来进行处理:
参考
完成 s.yaml 的编写:
edition: 1.0.0 name: start-ai access: "default" vars: # 全局变量 region: cn-hangzhou service: name: ai nasConfig: # NAS配置, 配置后function可以访问指定NAS userId: 10003 # userID, 默认为10003 groupId: 10003 # groupID, 默认为10003 mountPoints: # 目录配置 - serverAddr: 0fe764bf9d-kci94.cn-hangzhou.nas.aliyuncs.com # NAS 服务器地址 nasDir: /python3 fcDir: /mnt/python3 vpcConfig: vpcId: vpc-bp1rmyncqxoagiyqnbcxk securityGroupId: sg-bp1dpxwusntfryekord6 vswitchIds: - vsw-bp1wqgi5lptlmk8nk5yi0 services: image: component: fc props: # 组件的属性值 region: ${vars.region} service: ${vars.service} function: name: image_server description: 图片处理服务 runtime: python3 codeUri: ./ ossBucket: temp-code-cn-hangzhou handler: index.app memorySize: 3072 timeout: 300 environmentVariables: PYTHONUSERBASE: /mnt/python3/python triggers: - name: httpTrigger type: http config: authType: anonymous methods: - GET - POST - PUT customDomains: - domainName: avatar.aialbum.net protocol: HTTP routeConfigs: - path: /*
然后进行:
1、依赖的安装:s build --use-docker
2、项目的部署:s deploy
3、在 NAS 中创建目录,上传依赖:
s nas command mkdir /mnt/python3/python s nas upload -r 本地依赖路径 /mnt/python3/python
完成之后可以通过接口对项目进行测试。
另外,微信小程序需要 https 的后台接口,所以这里还需要配置 https 相关的证书信息,此处不做展开。
小程序项目
小程序项目依旧采用 colorUi,整个项目就只有一个页面:
<scroll-view scroll-y class="scrollPage"> <image src='/images/topbg.jpg' mode='widthFix' class='response'></image> <view class="cu-bar bg-white solid-bottom margin-top"> <view class="action"> <text class="cuIcon-title text-blue"></text>第一步:选择图片 </view> </view> <view class="padding bg-white solid-bottom"> <view class="flex"> <view class="flex-sub bg-grey padding-sm margin-xs radius text-center" bindtap="chosePhoto">本地上传图片</view> <view class="flex-sub bg-grey padding-sm margin-xs radius text-center" bindtap="getUserAvatar">获取当前头像</view> </view> </view> <view class="padding bg-white" hidden="{{!userChosePhoho}}"> <view class="images"> <image src="{{userChosePhoho}}" mode="widthFix" bindtap="previewImage" bindlongpress="editImage" data-image="{{userChosePhoho}}"></image> </view> <view class="text-right padding-top text-gray">* 点击图片可预览,长按图片可编辑</view> </view> <view class="cu-bar bg-white solid-bottom margin-top"> <view class="action"> <text class="cuIcon-title text-blue"></text>第二步:选择图片处理方案 </view> </view> <view class="bg-white"> <scroll-view scroll-x class="bg-white nav"> <view class="flex text-center"> <view class="cu-item flex-sub {{style==currentStyle?'text-orange cur':''}}" wx:for="{{styleList}}" wx:for-index="style" bindtap="changeStyle" data-style="{{style}}"> {{style}} </view> </view> </scroll-view> </view> <view class="padding-sm bg-white solid-bottom"> <view class="cu-avatar round xl bg-{{item.color}} margin-xs" wx:for="{{styleList[currentStyle].detailList}}" wx:for-index="substyle" bindtap="changeStyle" data-substyle="{{substyle}}" bindlongpress="showModal" data-target="Image"> <view class="cu-tag badge cuIcon-check bg-grey" hidden="{{currentSubStyle == substyle ? false : true}}"></view> <text class="avatar-text">{{substyle}}</text> </view> <view class="text-right padding-top text-gray">* 长按风格圆圈可以预览模板效果</view> </view> <view class="padding-sm bg-white solid-bottom"> <button class="cu-btn block bg-blue margin-tb-sm lg" bindtap="getNewPhoto" disabled="{{!userChosePhoho}}" type="">{{ userChosePhoho ? (getPhotoStatus ? 'AI将花费较长时间' : '生成图片') : '请先选择图片' }}</button> </view> <view class="cu-bar bg-white solid-bottom margin-top" hidden="{{!resultPhoto}}"> <view class="action"> <text class="cuIcon-title text-blue"></text>生成结果 </view> </view> <view class="padding-sm bg-white solid-bottom" hidden="{{!resultPhoto}}"> <view wx:if="{{resultPhoto == 'error'}}"> <view class="text-center padding-top">服务暂时不可用,请稍后重试</view> <view class="text-center padding-top">或联系开发者微信:<text class="text-blue" data-data="zhihuiyushaiqi" bindtap="copyData">zhihuiyushaiqi</text></view> </view> <view wx:else> <view class="images"> <image src="{{resultPhoto}}" mode="aspectFit" bindtap="previewImage" bindlongpress="saveImage" data-image="{{resultPhoto}}"></image> </view> <view class="text-right padding-top text-gray">* 点击图片可预览,长按图片可保存</view> </view> </view> <view class="padding bg-white margin-top margin-bottom"> <view class="text-center">自豪的采用 Serverless Devs 搭建</view> <view class="text-center">Powered By Anycodes <text bindtap="showModal" class="text-cyan" data-target="Modal">{{"<"}}作者的话{{">"}}</text></view> </view> <view class="cu-modal {{modalName=='Modal'?'show':''}}"> <view class="cu-dialog"> <view class="cu-bar bg-white justify-end"> <view class="content">作者的话</view> <view class="action" bindtap="hideModal"> <text class="cuIcon-close text-red"></text> </view> </view> <view class="padding-xl text-left"> 大家好,我是刘宇,很感谢您可以关注和使用这个小程序,这个小程序是我用业余时间做的一个头像生成小工具,基于“人工智障”技术,反正现在怎么看怎么别扭,但是我会努力让这小程序变得“智能”起来的。如果你有什么好的意见也欢迎联系我<text class="text-blue" data-data="service@52exe.cn" bindtap="copyData">邮箱</text>或者<text class="text-blue" data-data="zhihuiyushaiqi" bindtap="copyData">微信</text>,另外值得一提的是,本项目基于阿里云Serverless架构,通过Serverless Devs开发者工具建设。 </view> </view> </view> <view class="cu-modal {{modalName=='Image'?'show':''}}"> <view class="cu-dialog"> <view class="bg-img" style="background-image: url("{{previewStyle}}");height:200px;"> <view class="cu-bar justify-end text-white"> <view class="action" bindtap="hideModal"> <text class="cuIcon-close "></text> </view> </view> </view> <view class="cu-bar bg-white"> <view class="action margin-0 flex-sub solid-left" bindtap="hideModal">关闭预览</view> </view> </view> </view> </scroll-view> 页面逻辑也是比较简单的: // index.js // 获取应用实例 const app = getApp() Page({ data: { styleList: {}, currentStyle: "动漫风", currentSubStyle: "v1模型", userChosePhoho: undefined, resultPhoto: undefined, previewStyle: undefined, getPhotoStatus: false }, // 事件处理函数 bindViewTap() { wx.navigateTo({ url: '../logs/logs' }) }, onLoad() { const that = this wx.showLoading({ title: '加载中', }) app.doRequest(`system/styles`, {}, option = { method: "GET" }).then(function (result) { wx.hideLoading() that.setData({ styleList: result, currentStyle: Object.keys(result)[0], currentSubStyle: Object.keys(result[Object.keys(result)[0]].detailList)[0], }) }) }, changeStyle(attr) { this.setData({ "currentStyle": attr.currentTarget.dataset.style || this.data.currentStyle, "currentSubStyle": attr.currentTarget.dataset.substyle || Object.keys(this.data.styleList[attr.currentTarget.dataset.style].detailList)[0] }) }, chosePhoto() { const that = this wx.chooseImage({ count: 1, sizeType: ['compressed'], sourceType: ['album', 'camera'], complete(res) { that.setData({ userChosePhoho: res.tempFilePaths[0], resultPhoto: undefined }) } }) }, headimgHD(imageUrl) { imageUrl = imageUrl.split('/'); //把头像的路径切成数组 //把大小数值为 46 || 64 || 96 || 132 的转换为0 if (imageUrl[imageUrl.length - 1] && (imageUrl[imageUrl.length - 1] == 46 || imageUrl[imageUrl.length - 1] == 64 || imageUrl[imageUrl.length - 1] == 96 || imageUrl[imageUrl.length - 1] == 132)) { imageUrl[imageUrl.length - 1] = 0; } imageUrl = imageUrl.join('/'); //重新拼接为字符串 return imageUrl; }, getUserAvatar() { const that = this wx.getUserProfile({ desc: "获取您的头像", success(res) { const newAvatar = that.headimgHD(res.userInfo.avatarUrl) wx.getImageInfo({ src: newAvatar, success(res) { that.setData({ userChosePhoho: res.path, resultPhoto: undefined }) } }) } }) }, previewImage(e) { wx.previewImage({ urls: [e.currentTarget.dataset.image] }) }, editImage() { const that = this wx.editImage({ src: this.data.userChosePhoho, success(res) { that.setData({ userChosePhoho: res.tempFilePath }) } }) }, getNewPhoto() { const that = this wx.showLoading({ title: '图片生成中', }) this.setData({ getPhotoStatus: true }) app.doRequest(this.data.styleList[this.data.currentStyle].detailList[this.data.currentSubStyle].uri, { style: this.data.styleList[this.data.currentStyle].detailList[this.data.currentSubStyle].name, image: wx.getFileSystemManager().readFileSync(this.data.userChosePhoho, "base64") }, option = { method: "POST" }).then(function (result) { wx.hideLoading() that.setData({ resultPhoto: result.error ? "error" : result.photo, getPhotoStatus: false }) }) }, saveImage() { wx.saveImageToPhotosAlbum({ filePath: this.data.resultPhoto, success(res) { wx.showToast({ title: "保存成功" }) }, fail(res) { wx.showToast({ title: "异常,稍后重试" }) } }) }, onShareAppMessage: function () { return { title: "头头是道个性头像", } }, onShareTimeline() { return { title: "头头是道个性头像", } }, showModal(e) { if(e.currentTarget.dataset.target=="Image"){ const previewSubStyle = e.currentTarget.dataset.substyle const previewSubStyleUrl = this.data.styleList[this.data.currentStyle].detailList[previewSubStyle].preview if(previewSubStyleUrl){ this.setData({ previewStyle: previewSubStyleUrl }) }else{ wx.showToast({ title: "暂无模板预览", icon: "error" }) return } } this.setData({ modalName: e.currentTarget.dataset.target }) }, hideModal(e) { this.setData({ modalName: null }) }, copyData(e) { wx.setClipboardData({ data: e.currentTarget.dataset.data, success(res) { wx.showModal({ title: '复制完成', content: `已将${e.currentTarget.dataset.data}复制到了剪切板`, }) } }) }, })
因为项目会请求比较多次的后台接口,所以,我将请求方法进行额外的抽象:
// 统一请求接口 doRequest: async function (uri, data, option) { const that = this return new Promise((resolve, reject) => { wx.request({ url: that.url + uri, data: data, header: { "Content-Type": 'application/json', }, method: option && option.method ? option.method : "POST", success: function (res) { resolve(res.data) }, fail: function (res) { reject(null) } }) }) }
完成之后配置一下后台接口,发布审核即可。
本文作者刘宇(花名:江昱)
本文为阿里云原创内容,未经允许不得转载。