Azure 计算机视觉：识别印刷文本
Azure Computer Vision : Recognize Printed Text
我正在使用 Azure 计算机视觉和 nodejs，我想在图像上提取文本，它按预期工作，但我面临一些挑战：
代码：
'use strict';
const request = require('request');
const subscriptionKey = 'key';
const endpoint = 'endpoint'
var uriBase = endpoint + 'vision/v3.1/ocr';
const imageUrl = 'https://livesimply.me/wp-content/uploads/2015/09/foods-to-avoid-real-food-3036-2-1024x683.jpg';
// Request parameters.
const params = {
'language': 'unk',
'detectOrientation': 'true',
};
const options = {
uri: uriBase,
qs: params,
body: '{"url": ' + '"' + imageUrl + '"}',
headers: {
'Content-Type': 'application/json',
'Ocp-Apim-Subscription-Key' : subscriptionKey
}
};
request.post(options, (error, response, body) => {
if (error) {
console.log('Error: ', error);
return;
}
let jsonResponse = JSON.stringify(JSON.parse(body), null, ' ');
console.log('JSON Response\n');
console.log(jsonResponse);
});
输出：
"regions": [
{
"boundingBox": "0,191,277,281",
"lines": [
{
"boundingBox": "53,191,23,49",
"words": [
{
"boundingBox": "53,191,23,49",
"text": "in"
}
]
},
{
"boundingBox": "0,285,277,82",
"words": [
{
"boundingBox": "0,285,150,82",
"text": ")arb.0g"
},
{
"boundingBox": "214,288,63,63",
"text": "0%"
}
]
},
{
"boundingBox": "14,393,45,79",
"words": [
{
"boundingBox": "14,393,45,79",
"text": "Og"
}
]
},
{
"boundingBox": "213,394,63,63",
"words": [
{
"boundingBox": "213,394,63,63",
"text": "00/0"
}
]
}
]
},
{
"boundingBox": "322,184,352,457",
"lines": [
{
"boundingBox": "326,184,348,54",
"words": [
{
"boundingBox": "326,184,239,52",
"text": "INGREDIENTS:"
},
{
"boundingBox": "588,188,86,50",
"text": "WHITE"
}
]
},
{
"boundingBox": "325,248,281,59",
"words": [
{
"boundingBox": "325,248,83,56",
"text": "TUNA,"
},
{
"boundingBox": "417,250,127,51",
"text": "SOYBEAN"
},
{
"boundingBox": "555,252,51,55",
"text": "OIL,"
}
]
},
{
"boundingBox": "324,313,341,60",
"words": [
{
"boundingBox": "324,313,155,52",
"text": "VEGETABLE"
},
{
"boundingBox": "489,316,101,56",
"text": "BROTH,"
},
{
"boundingBox": "598,317,67,56",
"text": "SALT,"
}
]
},
{
"boundingBox": "324,378,334,53",
"words": [
{
"boundingBox": "324,378,235,52",
"text": "PYROPHOSPHATE"
},
{
"boundingBox": "566,381,92,50",
"text": "ADDED"
}
]
},
{
"boundingBox": "323,519,248,52",
"words": [
{
"boundingBox": "323,519,193,51",
"text": "DISTRIBUTED"
},
{
"boundingBox": "528,521,43,50",
"text": "BY:"
}
]
},
{
"boundingBox": "322,584,298,57",
"words": [
{
"boundingBox": "322,584,124,50",
"text": "BUMBLE"
},
{
"boundingBox": "457,585,52,50",
"text": "BEE"
},
{
"boundingBox": "519,585,101,56",
"text": "FOODS,"
}
]
}
]
},
{
"boundingBox": "791,400,198,117",
"lines": [
{
"boundingBox": "921,400,68,45",
"words": [
{
"boundingBox": "921,400,68,45",
"text": ",11."
}
]
},
{
"boundingBox": "791,464,128,53",
"words": [
{
"boundingBox": "791,464,75,53",
"text": "PRC:"
},
{
"boundingBox": "874,467,45,48",
"text": "x"
}
]
}
]
}
]
}
但我在使用这段代码时遇到了一些挑战：
- 我希望输出为字符串而不是 JSON 树。
- 我只想提取成分而不是所有文本。
- 在某些情况下，图像可能包含成分但未指定成分关键字，在这种情况下如何提取成分？
图片：
感谢各位专家的帮助。
我们使用计算机视觉 REST API 从图像中提取带有光学字符识别 (OCR) 的印刷文本。并在 JSON 中返回成功响应。您无法从此 Azure 认知服务获得直接字符串输出。
针对问题-
I want the output as a string and not JSON tree.
我们不能像图中看到的那样直接将成分打印成字符串。要提取内容并以特定格式显示，在获得 JSON 字符串后，将其解析为 JSON 对象和 运行 循环以从中提取数据.之后使用split函数将数据存储到数组中。如以下片段所示。
function(error, response, body){
if(error) {
console.log(error);
} else {
//parsing the JSON string
var jsonObj = JSON.parse(body);
var ob = jsonObj;
//running loop to extract the text values
for(i=0;i<....){
for(j=0;j<....){
for(k=0;k<....){
var str = str + " "+ob.....text;
}
str = str + "\n";
}
}
var arr = str.split("\n");
根据您得到的 JSON 结构放置您的逻辑。
对于你的第二个和第三个问题-
I would like to extract just the ingredients and not the all text.
In some cases the images may have ingredients without specifying the ingredient key-word, how can I extract the ingredients in this case ?
计算机视觉将从图像中提取所有打印文本并将它们作为 JSON 提供给您，您无法提取特定文本。您可以使用与上述相同的方法并仅提取成分来达到所需的结果。
我建议阅读此 Extract printed text (OCR) using the Computer Vision REST API and Node.js GitHub 文档以获取更多信息。
我正在使用 Azure 计算机视觉和 nodejs，我想在图像上提取文本，它按预期工作，但我面临一些挑战： 代码：
'use strict';
const request = require('request');
const subscriptionKey = 'key';
const endpoint = 'endpoint'
var uriBase = endpoint + 'vision/v3.1/ocr';
const imageUrl = 'https://livesimply.me/wp-content/uploads/2015/09/foods-to-avoid-real-food-3036-2-1024x683.jpg';
// Request parameters.
const params = {
'language': 'unk',
'detectOrientation': 'true',
};
const options = {
uri: uriBase,
qs: params,
body: '{"url": ' + '"' + imageUrl + '"}',
headers: {
'Content-Type': 'application/json',
'Ocp-Apim-Subscription-Key' : subscriptionKey
}
};
request.post(options, (error, response, body) => {
if (error) {
console.log('Error: ', error);
return;
}
let jsonResponse = JSON.stringify(JSON.parse(body), null, ' ');
console.log('JSON Response\n');
console.log(jsonResponse);
});
输出：
"regions": [
{
"boundingBox": "0,191,277,281",
"lines": [
{
"boundingBox": "53,191,23,49",
"words": [
{
"boundingBox": "53,191,23,49",
"text": "in"
}
]
},
{
"boundingBox": "0,285,277,82",
"words": [
{
"boundingBox": "0,285,150,82",
"text": ")arb.0g"
},
{
"boundingBox": "214,288,63,63",
"text": "0%"
}
]
},
{
"boundingBox": "14,393,45,79",
"words": [
{
"boundingBox": "14,393,45,79",
"text": "Og"
}
]
},
{
"boundingBox": "213,394,63,63",
"words": [
{
"boundingBox": "213,394,63,63",
"text": "00/0"
}
]
}
]
},
{
"boundingBox": "322,184,352,457",
"lines": [
{
"boundingBox": "326,184,348,54",
"words": [
{
"boundingBox": "326,184,239,52",
"text": "INGREDIENTS:"
},
{
"boundingBox": "588,188,86,50",
"text": "WHITE"
}
]
},
{
"boundingBox": "325,248,281,59",
"words": [
{
"boundingBox": "325,248,83,56",
"text": "TUNA,"
},
{
"boundingBox": "417,250,127,51",
"text": "SOYBEAN"
},
{
"boundingBox": "555,252,51,55",
"text": "OIL,"
}
]
},
{
"boundingBox": "324,313,341,60",
"words": [
{
"boundingBox": "324,313,155,52",
"text": "VEGETABLE"
},
{
"boundingBox": "489,316,101,56",
"text": "BROTH,"
},
{
"boundingBox": "598,317,67,56",
"text": "SALT,"
}
]
},
{
"boundingBox": "324,378,334,53",
"words": [
{
"boundingBox": "324,378,235,52",
"text": "PYROPHOSPHATE"
},
{
"boundingBox": "566,381,92,50",
"text": "ADDED"
}
]
},
{
"boundingBox": "323,519,248,52",
"words": [
{
"boundingBox": "323,519,193,51",
"text": "DISTRIBUTED"
},
{
"boundingBox": "528,521,43,50",
"text": "BY:"
}
]
},
{
"boundingBox": "322,584,298,57",
"words": [
{
"boundingBox": "322,584,124,50",
"text": "BUMBLE"
},
{
"boundingBox": "457,585,52,50",
"text": "BEE"
},
{
"boundingBox": "519,585,101,56",
"text": "FOODS,"
}
]
}
]
},
{
"boundingBox": "791,400,198,117",
"lines": [
{
"boundingBox": "921,400,68,45",
"words": [
{
"boundingBox": "921,400,68,45",
"text": ",11."
}
]
},
{
"boundingBox": "791,464,128,53",
"words": [
{
"boundingBox": "791,464,75,53",
"text": "PRC:"
},
{
"boundingBox": "874,467,45,48",
"text": "x"
}
]
}
]
}
]
}
但我在使用这段代码时遇到了一些挑战：
- 我希望输出为字符串而不是 JSON 树。
- 我只想提取成分而不是所有文本。
- 在某些情况下，图像可能包含成分但未指定成分关键字，在这种情况下如何提取成分？
图片：
感谢各位专家的帮助。
我们使用计算机视觉 REST API 从图像中提取带有光学字符识别 (OCR) 的印刷文本。并在 JSON 中返回成功响应。您无法从此 Azure 认知服务获得直接字符串输出。
针对问题-
I want the output as a string and not JSON tree.
我们不能像图中看到的那样直接将成分打印成字符串。要提取内容并以特定格式显示，在获得 JSON 字符串后，将其解析为 JSON 对象和 运行 循环以从中提取数据.之后使用split函数将数据存储到数组中。如以下片段所示。
function(error, response, body){
if(error) {
console.log(error);
} else {
//parsing the JSON string
var jsonObj = JSON.parse(body);
var ob = jsonObj;
//running loop to extract the text values
for(i=0;i<....){
for(j=0;j<....){
for(k=0;k<....){
var str = str + " "+ob.....text;
}
str = str + "\n";
}
}
var arr = str.split("\n");
根据您得到的 JSON 结构放置您的逻辑。
对于你的第二个和第三个问题-
I would like to extract just the ingredients and not the all text.
In some cases the images may have ingredients without specifying the ingredient key-word, how can I extract the ingredients in this case ?
计算机视觉将从图像中提取所有打印文本并将它们作为 JSON 提供给您，您无法提取特定文本。您可以使用与上述相同的方法并仅提取成分来达到所需的结果。
我建议阅读此 Extract printed text (OCR) using the Computer Vision REST API and Node.js GitHub 文档以获取更多信息。