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:
关于这个模型的具体的信息,在这里不做详细的介绍和说明。通过与 Python Web 框架结合,将 AI 模型通过接口对外暴露:
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 + localNamewith 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"] = Truereturn 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 Yaml规范 - Serverless Devs
完成 s.yaml 的编写:
edition: 1.0.0 name: start-ai access: "default" vars: # 全局变量region: cn-hangzhouservice:name: ainasConfig: # NAS配置, 配置后function可以访问指定NASuserId: 10003 # userID, 默认为10003groupId: 10003 # groupID, 默认为10003mountPoints: # 目录配置- serverAddr: 0fe764bf9d-kci94.cn-hangzhou.nas.aliyuncs.com # NAS 服务器地址nasDir: /python3fcDir: /mnt/python3vpcConfig:vpcId: vpc-bp1rmyncqxoagiyqnbcxksecurityGroupId: sg-bp1dpxwusntfryekord6vswitchIds:- vsw-bp1wqgi5lptlmk8nk5yi0 services:image:component: fcprops: # 组件的属性值region: ${vars.region}service: ${vars.service}function:name: image_serverdescription: 图片处理服务runtime: python3codeUri: ./ossBucket: temp-code-cn-hangzhouhandler: index.appmemorySize: 3072timeout: 300environmentVariables:PYTHONUSERBASE: /mnt/python3/pythontriggers:- name: httpTriggertype: httpconfig:authType: anonymousmethods:- GET- POST- PUTcustomDomains:- domainName: avatar.aialbum.netprotocol: HTTProuteConfigs:- 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:
页面相关布局:
<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 = thiswx.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 = thiswx.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0if (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 = thiswx.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 = thiswx.editImage({src: this.data.userChosePhoho,success(res) {that.setData({userChosePhoho: res.tempFilePath})}})},getNewPhoto() {const that = thiswx.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.substyleconst previewSubStyleUrl = this.data.styleList[this.data.currentStyle].detailList[previewSubStyle].previewif(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 = thisreturn 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)
原文链接
本文为阿里云原创内容,未经允许不得转载。