2017年春节入坑DP，学着caffe做了一个杂草小苗的APP，模型和功能均在云端。
pypic.py
#!/usr/bin/env python
#-*-coding:utf-8-*-
import numpy as np ?
import sys,os?
import re ?
# 设置当前的工作环境在caffe下 ?
caffe_root = 'caffe/caffe-master/' ??
# 我们也把caffe/python也添加到当前环境 ?
sys.path.insert(0, caffe_root + 'python')?
sys.path.insert(0, caffe_root + 'python/caffe')?
# os.environ['GLOG_minloglevel'] = '2'
import caffe ?
os.chdir(caffe_root)#更换工作目录 ?
#GPU模式
#caffe.set_device(0) ?# 如果你有多个GPU，那么选择第一个
caffe.set_mode_cpu()
# 设置网络结构 ?
net_file=caffe_root + 'examples/flower/deploy.prototxt' ?#现成的
# 添加训练之后的参数 ?
caffe_model=caffe_root + 'examples/flower/snapshot_iter_40000.caffemodel' ?
# 均值文件 ?
mean_file=caffe_root + 'examples/flower/ilsvrc_2012_mean.npy' ??
# 这里对任何一个程序都是通用的，就是处理图片 ?
# 把上面添加的两个变量都作为参数构造一个Net ?
net = caffe.Net(net_file,caffe_model,caffe.TEST) ?
# 得到data的形状，这里的图片是默认matplotlib底层加载的 ?
transformer = caffe.io.Transformer({'data': net.blobs['data'].data.shape}) ?
# matplotlib加载的image是像素[0-1],图片的数据格式[weight,high,channels]，RGB ?
# caffe加载的图片需要的是[0-255]像素，数据格式[channels,weight,high],BGR，那么就需要转换 ?
# channel 放到前面 ?
transformer.set_transpose('data', (2,0,1)) ?
transformer.set_mean('data', np.load(mean_file).mean(1).mean(1)) ?
# 图片像素放大到[0-255] ?
transformer.set_raw_scale('data', 255) ??
# RGB-->BGR 转换 ?
transformer.set_channel_swap('data', (2,1,0)) ?
# print "input image" + sys.argv[1]
# 这里才是加载图片 ?
#im=caffe.io.load_image(caffe_root+'examples/flower/jpg/zshuhe055.jpg')?
im=caffe.io.load_image(sys.argv[1])?
# 用上面的transformer.preprocess来处理刚刚加载图片 ?
net.blobs['data'].data[...] = transformer.preprocess('data',im) ?
#注意,网络开始向前传播啦 ?
output = net.forward() ?
# 最终的结果: 当前这个图片的属于哪个物体的概率(列表表示) ?
output_prob = output['prob'][0]?
?
# 找出最大的那个概率 ?
# print 'predicted class is:', output_prob.argmax() ?
# 也可以找出前五名的概率 ?
top_inds = output_prob.argsort()[::-1][:5] ? ?
# 最后加载数据集进行验证 ?
imagenet_labels_filename = caffe_root + 'examples/flower/synset_words.txt' ? ?
labels = np.loadtxt(imagenet_labels_filename, str, delimiter='\t') ?
# print 'probabilities and labels:' ?
# zip(output_prob[top_inds], labels[top_inds]) ?
top_k = net.blobs['prob'].data[0].flatten().argsort()[-1:-6:-1] ?
#for i in np.arange(top_k.size): ?
# ? ?print labels[top_k[i]] ?
with open("pestTemp.txt", "w") as f:
# ? ?f.write(''.join(labels[top_k[0]])+';'.join(labels[top_k[1]])+';'.join(labels[top_k[2]])+';'.join(labels[top_k[3]])+';'.join(labels[top_k[4]]))?
? ? f.write(labels[top_k[0]]+';'+labels[top_k[1]]+';'+labels[top_k[2]]+';'+labels[top_k[3]]+';'+labels[top_k[4]])
upImgAi.php
date_default_timezone_set('Asia/Shanghai');
require_once('../include/DbMysqli.php');//BbsDbclass
require_once("PYClass.php");
//post 传值
$tblId = $_POST['tblId'];?
$act = $_POST['act']; ?
$imgtxt = $_POST['imgtxt'];?
$UpPest = $_POST['UpPest'];?
$recId = $_POST['recId']; ?
$UpLoc = $_POST['UpLoc'];?
$UpImgName = $_FILES["image"]["name"];
$UpAiDir = 'caffe/caffe-master/examples/flower/AiImg/';
if(!file_exists($UpAiDir)) {
? ? mkdir($UpAiDir); //新建文件夹
}
UpImgFile($UpImgName,$UpAiDir);//上传图片到指定目录?
$pestImg = $UpAiDir.$UpImgName;
system("python pypic.py ".$pestImg, $ret);
$pyDlFile = "caffe/caffe-master/pestTemp.txt"; //结果
if(file_exists($pyDlFile)){ //文件内容读入到字符串?
? $dlStr = file_get_contents($pyDlFile);
? $dlStr = preg_replace('|[0-9]+|','',$dlStr);
? $dlPestArr = explode(";",$dlStr); ?//诊断结果数组
? AiJson($dlPestArr);
}
function UpImgFile($TempName,$UpAiDir){//上传图片移到指定目录
?? ?if(move_uploaded_file($_FILES['image']['tmp_name'], $UpAiDir.$TempName)){
?? ??? ?//echo "The file ".basename($TempName)." has been uploaded successful.";
?? ?}else{
?? ??? ?echo "Sorry, there was a problem uploading your file.failed";
?? ?}
}
function AiJson($dlPestArr){
?? ?$response = array();//zsh;yc;znB;zyy;ehm
?? ?$pestArrEn = array('jc','zyy','dzZ','znA','zsh','dzB','pop','yc','znB','fl','ehm','zjym','mg','dzC','cec','dm','fs','dqb','ze','zheqi','znC','znZ','dzA','bph','sbph');
? ? $pestArr = array('荠菜','猪殃殃','0级稻桩','1级子囊','早熟禾','2级稻桩','婆婆纳','硬草','2级子囊','繁缕','二化螟','纵卷叶螟','毛茛','3级稻桩','刺儿菜','大螟','褐稻虱','稻曲病','卷耳','泽漆','3级子囊','0级子囊','1级稻桩','褐飞虱','灰飞虱');
?? ?for($i=0;$i<count($dlPestArr);$i++){
?? ? ? ? ?$RecArr["Id"] = "1";//表ID序号
?? ? ? ? ?$RecArr["demoImg"] = "http://localhost/jsipm/admin/".$dlPestArr[$i].".jpg"; ?//图标
?? ??? ? ?if(in_array($dlPestArr[$i],$pestArrEn)){
?? ??? ??? ? ?$pId = array_search($dlPestArr[$i],$pestArrEn);
?? ??? ??? ? ?$RecArr["ShowTbl"] = $pestArr[$pId]; ?//诊断结果
?? ??? ? ?}else{
?? ??? ??? ? ?$RecArr["ShowTbl"] = "未知"; ?//诊断结果
?? ??? ? ?}
? ? ? ? ??
? ? ? ? ? $RecArr["RealTbl"] = "http://localhost/jsipm/pestimg/csvpro.mp4"; ?//表格名
?? ? ? ? ?array_push($response, $RecArr);
?? ?}
?? ?$JsonStr = json_encode($response);
? ? echo $JsonStr;
}
致敬贾神！
