AI实战：上海垃圾分类系列（二）之快速搭建垃圾分类模型后台服务

前言

AI实战：上海垃圾分类系列（一）之快速搭建垃圾分类模型
AI实战：上海垃圾分类系列（二）之快速搭建垃圾分类模型后台服务
AI实战：上海垃圾分类系列（三）之快速搭建垃圾分类智能问答机器人

前一篇文章 AI实战：上海垃圾分类系列之快速搭建垃圾分类模型 ，本文在其之上搭建了一个基于Django、REST的web服务，实现了从浏览器中上传图片做垃圾分类的功能。

2019上海市生活垃圾按照以下标准分类!：http://sh.bendibao.com/zffw/2019225/202535.shtm

上海生活垃圾分类标准及投放要求：https://www.sohu.com/a/163450869_688983

模型介绍

垃圾分类模型详情请查看这里：AI实战：上海垃圾分类系列之快速搭建垃圾分类模型

环境

• Python 3.5
• Django 1.10.8
• Django Rest Framework 3.5
• Pillow

安装环境

pip install -r requirements.txt

垃圾分类识别模型

具体见：./refuse_recognize_service/refuse_recognize/readme.md

配置修改

• 1、修改checkpoints

  ./refuse_recognize_service/refuse_recognize/runs/checkpoints
  把路径改为自己的全路径

• 2、修改html样式：

  ./refuse_recognize_service/imageupload_frontend/static/index.html

核心代码

models.py :

import os
import uuid

from PIL import Image
from django.db import models
from django.conf import settings

import sys, time
sys.path.append('./refuse_recognize/')
sys.path.append('./refuse_recognize/textcnn/')
from refuse import *

refuse_classification = RefuseRecognize()#加载垃圾识别模型


def scramble_uploaded_filename(instance, filename):
    """
    Scramble / uglify the filename of the uploaded file, but keep the files extension (e.g., .jpg or .png)
    :param instance:
    :param filename:
    :return:
    """
    extension = filename.split(".")[-1]
    return "{}.{}".format(uuid.uuid4(), extension)


def create_thumbnail(input_image, thumbnail_size=(500, 500)):
    """
    Create a thumbnail of an existing image
    :param input_image:
    :param thumbnail_size:
    :return:
    """
    # make sure an image has been set
    if not input_image or input_image == "":
        return

    # open image
    image = Image.open(input_image)

    # use PILs thumbnail method; use anti aliasing to make the scaled picture look good
    image.thumbnail(thumbnail_size, Image.ANTIALIAS)

    # parse the filename and scramble it
    filename = scramble_uploaded_filename(None, os.path.basename(input_image.name))
    arrdata = filename.split(".")
    # extension is in the last element, pop it
    extension = arrdata.pop()
    basename = "".join(arrdata)
    # add _thumb to the filename
    new_filename = basename + "_thumb." + extension

    # save the image in MEDIA_ROOT and return the filename
    image.save(os.path.join(settings.MEDIA_ROOT, new_filename))

    return new_filename


class UploadedImage(models.Model):
    """
    Provides a Model which contains an uploaded image aswell as a thumbnail
    """
    image = models.ImageField("Uploaded image", upload_to=scramble_uploaded_filename)

    # thumbnail
    thumbnail = models.ImageField("Thumbnail of uploaded image", blank=True)

    # title and description
    title = models.CharField("Title of the uploaded image", max_length=800, default="Unknown Picture")
    description = models.TextField("Description of the uploaded image", default="")


    def __str__(self):
        return self.title

    def save(self, force_insert=False, force_update=False, using=None, update_fields=None):
        """
        On save, generate a new thumbnail
        :param force_insert:
        :param force_update:
        :param using:
        :param update_fields:
        :return:
        """
        # generate and set thumbnail or none
        self.thumbnail = create_thumbnail(self.image)
        

        # 垃圾类别识别
        image_data = Image.open(self.image)
        img_path = str(time.time) + '.png'
        while os.path.exists(img_path):
            img_path = str(time.time) + '.png'
        image_data.save(img_path, 'png')
        
        image_data = tf.gfile.FastGFile(img_path, 'rb').read()
        classify_res = refuse_classification.recognize_image(image_data)
        self.title = classify_res
        os.remove(img_path)

        # force update as we just changed something
        super(UploadedImage, self).save(force_update=force_update)

HTML显示样式

index.html ：

    
    
    
    
    
    
    

    
    
    
    

    
    

    
    
    




    

        
        

            

                

                    

                        
选择一张图片：
                        
                        File too large
                            {{ errorFile.size / 1000000 | number:1 }} MB: max 10M
                        
                        Remove
                    
                    
                        上传
                    
                
            
        

        

            请选择一张图片上传！
        

        
        

            

                
                    
                    
{{ image.description }}
                
                
垃圾类别：
                
                
                {{ image.title }}
                
                

                    删除
                
            
        
    


 

开启服务

• 服务

    cd refuse_recognize_service
    python manage.py migrate
    python manage.py runserver &  # 后台运行
  

效果展示

• 在浏览器中打开 http://localhost:8000/static/index.html （我是在本机测试的，服务器测试的话修改localhost为相应的ip即可）。

• 起始页面

- 上传效果图

• 点击上传后，垃圾分类结果效果图

效果展示大概就是这样了，整体比较粗糙，识别准确率就不再优化了。
还有很多细节工作需要做，主要是垃圾类别标注数据、imagenet的结果的1000类中文对照优化等工作。

完整工程代码

完整的工程包括：
1、完整代码
2、完整的数据
3、完整的垃圾分类识别模型
4、文档

工程下载地址： 快速搭建垃圾分类模型后台服务