ocr

调用百度OCR模块进行文字识别

给你一囗甜甜゛ 提交于 2020-01-10 10:47:48
1.登录百度云平台,创建应用 2.编写代码 from aip import AipOcr import codecs import os #读取图片函数 def ocr(path): with open(path,'rb') as f: return f.read() def main(): filename = "c.jpg" print("已经收到,正在处理,请稍后....") app_id = '16193547' api_key = 'B0R5gbezdGSzCY4oIlOpuLy8' secret_key = 'CyevG1PTfpPvkw9vwItPdya09GrzZ462' client = AipOcr(app_id,api_key,secret_key) #读取图片 image = ocr(filename) #进程OCR识别 dict1 = client.general(image) # print(dict1) with codecs.open(filename + ".txt","w","utf-8") as f: for i in dict1["words_result"]: f.write(str(i["words"] + "\r\n")) print ("处理完成") if __name__ == '__main__': main() 效果图: 来源:

百度ocr接口,限制调用的响应时间

落爺英雄遲暮 提交于 2020-01-08 19:43:05
一、百度提供的工具类 1.HttpUtil package com.baidu.ai.aip.utils; import java.io.BufferedReader; import java.io.DataOutputStream; import java.io.InputStreamReader; import java.net.HttpURLConnection; import java.net.URL; import java.util.List; import java.util.Map; /** * http 工具类 */ public class HttpUtil { public static String post(String requestUrl, String accessToken, String params) throws Exception { String contentType = "application/x-www-form-urlencoded"; return HttpUtil.post(requestUrl, accessToken, contentType, params); } public static String post(String requestUrl, String accessToken, String

驾驶证、行驶证识别

痞子三分冷 提交于 2020-01-07 21:10:27
一、OCR证件识别技术种类 OCR识别技术可谓当下人工智能领域最为火热的一项技术,在各种APP爆发式增长的同时,可以看到的是几乎所有的智能软件,开发人员如果想要提高客户人机交互的感受,那么智能识别技术是一个必选项。那么总体来说当今的ocr识别技术主要细分为以下功能:ocr综合文字识别、ocr视频文字识别、人脸识别、证件识别、票据识别、车牌Vin码识别、银行卡识别、云识别。那么今天就和大家聊聊应用广泛的证件识别。 二、OCR识别技术应用背景 这些年,随着移动互联网的的发展,越来越多的企业都推出了自己的移动APP,这些APP多数都涉及到个人身份证信息的输入认证(即实名认证),如果手动去输入身份证号码和姓名,速度非常慢,且用户体验非常差。为了提高在移动终端上输入身份证信息的速度和准确性,OCR证件识别技术应运而生。需要说明的是OCR证件识别不仅仅只有身份证识别,还有护照识别以及其他,但是我们今天就应用最广泛的身份证进行说明。 三、OCR手机身份证号识别技术简介 OCR手机身份证号识别技术SDK可支持Android、iOS主流移动操作系统,android平台提供jar包,ios提供静态库.a文件。APP集成OCR手机身份证号识别技术SDK后,用户采用手机、平板电脑对身份证进行拍摄识别即可自动识别身份证信息(如图-1所示); OCR手机身份证号识别技术技术还可以部署在识别服务器上

I want to detect objects in the image and redraw it in another page, so anyone would please suggest which algorithm can be used?

≡放荡痞女 提交于 2020-01-06 14:52:39
问题 I am doing project on image processing (molecule identification in an image and drawing those molecules in an editor). So want help in identifying, which algorithm can be used to detect the objects like lines, curves, bifurcations and characters in an image. Yes, canny's algorithm detects the edges in image. But to draw these edges in an editor I want the end points(pixel values) of these edges. So how the canny's algorithm will be helpful to do so? or are there any algorithms for recognising

VNDetectTextRectanglesRequest Not Working For Less Than 3 Digits

不问归期 提交于 2020-01-06 07:12:55
问题 I'm experimenting with Apple's Vision framework to detect the location of characters (letters, numbers, etc). Why can't I get the VisionBasics demo project to detect text in images with less than 3 digits? I've already tried binarizing the image by reducing saturation and increasing contrast. I even tried inverting the black and white portions, but it didn't improve the results. The 2-digit images are approximately 28x24 pixels. Link to Xcode Project: https://docs-assets.developer.apple.com

OCR for android application tess4j

て烟熏妆下的殇ゞ 提交于 2020-01-06 06:53:22
问题 Basically am designing an application that will capture an image from the android devices default camera and will display that image in an image view! works fine! good enough! capt_but.setOnClickListener(new View.OnClickListener() { //@Override // TODO Auto-generated method stub public void onClick(View v) { Intent cameraIntent = new Intent(android.provider.MediaStore.ACTION_IMAGE_CAPTURE); startActivityForResult(cameraIntent, CAMERA_REQUEST); } }); } protected void onActivityResult(int

extracting numbers from Bitmap in android using tess-two library

喜你入骨 提交于 2020-01-05 09:06:19
问题 I want to extract a number from a Bitmap. I'm using the tess-two library, but it does not recognize correctly. Example Code: @Override public void onClick(View v) { switch (v.getId()){ case R.id.b2: InputStream is = null; try { is = getApplicationContext().getAssets().open("zak.jpeg"); } catch (IOException e1) { e1.printStackTrace(); } final Drawable drw = Drawable.createFromStream(is, null); bmp = ((BitmapDrawable) drw).getBitmap(); TessBaseAPI baseApi = new TessBaseAPI(); bmp =BITMAP

OCR fails due to font specifics

血红的双手。 提交于 2020-01-05 08:52:43
问题 I have a library which contains all font characters (Arial in my case). For example: I'm using this library to OCR text from image. The problem is that when you try to OCR such characters as "j", "/", "t" - characters could overlap one another! So OCR is now impossible, because characters do not match pattern images (up to 3 pixels are different). How do I have to deal with this problem? Is there a better way to compare images? (C#, WinForms app) I'm using this method for comparison: unsafe

Training tesseract - shapeclustering issue

荒凉一梦 提交于 2020-01-05 08:17:16
问题 I'm trying to train tesseract (adding a new, digit only font) as per the instructions found here: http://code.google.com/p/tesseract-ocr/wiki/TrainingTesseract3 What I've done: Created a PDF with sample text, converted to tif, ran tesseract num.dot.exp0.tif num.dot.exp0 batch.nochop makebox digits . Then edited the generated box file, correcting wrong detections Ran tesseract on training mode: tesseract num.dot.exp0.tif num.dot.exp0 nobatch box.train and extracted the unicharset with

Which features can i use for handwritten OCR other than a downsampled binary grid of the image?

社会主义新天地 提交于 2020-01-05 07:15:16
问题 Hi I have been searching though research papers on what features would be good for me to use in my handwritten OCR classifying neural network. I am a beginner so I have been just taking the image of the handwritten character, made a bounding box around it, and then resize it into a 15x20 binary image. So this means i have an input layer of 300 features. From the papers i have found on google (most of which are quite old) the methods really vary. My accuracy is not bad with just a binary grid