ocr | 易学教程

Tess4J: Invalid memory access

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问题 I am trying to use Tess4J in my project to extract text from an image. I am getting the following error when I try run the OCR: Exception in thread "main" java.lang.Error: Invalid memory access try { File imageFile = new File("example4.jpg"); Tesseract instance = Tesseract.getInstance(); // JNA Interface Mapping //Tesseract1 instance = new Tesseract1(); String result = instance.doOCR(imageFile); System.out.println(result); } catch (Exception e) { e.printStackTrace(); } 回答1: you can set the

use pytesseract to recognize text from image

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问题 I need to use pytesseract to extract text from this picture: and the code: from PIL import Image, ImageEnhance, ImageFilter import pytesseract path = 'pic.gif' img = Image.open(path) img = img.convert('RGBA') pix = img.load() for y in range(img.size[1]): for x in range(img.size[0]): if pix[x, y][0] < 102 or pix[x, y][1] < 102 or pix[x, y][2] < 102: pix[x, y] = (0, 0, 0, 255) else: pix[x, y] = (255, 255, 255, 255) img.save('temp.jpg') text = pytesseract.image_to_string(Image.open('temp.jpg'))

Tesseract running error

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问题 I have a problem with running tesseract-ocr engine on linux. I've downloaded RUS language data and put it to tessdata directory (/usr/local/share/tessdata). When I'm trying to run tesseract with command tesseract blob.jpg out -l rus , it displays an error: Error opening data file /usr/local/share/tessdata/eng.traineddata Please make sure the TESSDATA_PREFIX environment variable is set to the parent directory of your "tessdata" directory. Failed loading language eng Tesseract couldn't load any

OpenCV Adaptive Threshold OCR

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问题 I am using OpenCV to prepare images for OCR from an iPhone camera, and I have been having trouble getting the results I need for an accurate OCR scan. Here is the code I am using now. cv::cvtColor(cvImage, cvImage, CV_BGR2GRAY); cv::medianBlur(cvImage, cvImage, 0); cv::adaptiveThreshold(cvImage, cvImage, 255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY, 5, 4); This method takes a bit too long and does not provide me good results. Any suggestions on how I could make this more effective? The

OCR技术（光学字符识别）

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什么是OCR？ OCR英文全称是optical character recognition，中文叫光学字符识别。它是利用光学技术和计算机技术把印在或者写在纸上的文字读取出来，并转换成一种计算机能够接受、人又可以理解的格式。文字识别是计算机视觉研究领域的分支之一，而且这个课题已经是比较成熟了，并且在商业中已经有很多落地项目了。比如汉王OCR，百度OCR，阿里OCR等等，很多企业都有能力都是拿OCR技术开始挣钱了。其实我们自己也能感受到，OCR技术确实也在改变着我们的生活：比如一个手机APP 就能帮忙扫描名片、身份证，并识别出里面的信息；汽车进入停车场、收费站都不要人工登记了，都是用车牌识别技术；我们看书时看到不懂的题，那个手机一扫，APP就能在网上帮你找到这题的答案。太多太多的应用了，OCR的应用在当今时代确实是百花齐放。 OCR的分类如果要给OCR进行分类，我觉得可以分为两类：手写识别和印刷体识别。这两个可以认为是OCR领域两个大主题了，当然印刷识别较手写体识别要简单得多，我们也能从直观上理解印刷体大多都是规则的字体，因为这些字体都是计算机自己生成再通过打印技术印刷到纸上。在印刷体的识别上有其独特的干扰；在印刷过程中字体很可能变得断裂或者墨水粘连，使得OCR识别异常困难。当然这些都可以通过一些图像处理的技术帮他尽可能的还原，进而提高识别率。总的来说

【OCR技术系列之四】基于深度学习的文字识别（3755个汉字）

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上一篇提到文字数据集的合成，现在我们手头上已经得到了3755个汉字（一级字库）的印刷体图像数据集，我们可以利用它们进行接下来的3755个汉字的识别系统的搭建。用深度学习做文字识别，用的网络当然是CNN，那具体使用哪个经典网络？VGG?RESNET？还是其他？我想了下，越深的网络训练得到的模型应该会更好，但是想到训练的难度以及以后线上部署时预测的速度，我觉得首先建立一个比较浅的网络（基于LeNet的改进）做基本的文字识别，然后再根据项目需求，再尝试其他的网络结构。这次任务所使用的深度学习框架是强大的Tensorflow。网络搭建第一步当然是搭建网络和计算图其实文字识别就是一个多分类任务，比如这个3755文字识别就是3755个类别的分类任务。我们定义的网络非常简单，基本就是LeNet的改进版，值得注意的是我们加入了batch normalization。另外我们的损失函数选择sparse_softmax_cross_entropy_with_logits，优化器选择了Adam，学习率设为0.1 #network: conv2d->max_pool2d->conv2d->max_pool2d->conv2d->max_pool2d->conv2d->conv2d->max_pool2d->fully_connected->fully_connected def build

How to ignore special characters in Tesseract OCR using java

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问题 I have extracted text from image through Tesseract OCR using java. But the output is consisting of some special characters because image contains some symbols. I want to ignore all the special characters and display just text. Is there any way that i can do that? 回答1: In tesseract you can set TessBaseAPI.VAR_CHAR_WHITELIST and TessBaseAPI.VAR_CHAR_BLACKLIST in order to ignore some special characters. Following would make tesseract only recognize A-Z and digits String whiteList =

How to ignore special characters in Tesseract OCR using java

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Where do I run this AWS rekognition code and do I need to install anything else? What result will I get?

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问题 ` import boto3 if __name__ == "__main__": bucket='random_name' photo='b4.png' client=boto3.client('rekognition') response=client.detect_text(Image={'S3Object': {'random_name':bucket,'b4.png':photo}}) textDetections=response['TextDetections'] print(response) print('Matching faces') for text in textDetections: print('Detected text:' + text['DetectedText']) print('Confidence: ' + "{:.2f}".format(text['Confidence']) + "%") print('Id: {}'.format(text['Id'])) if 'ParentId' in text: print('Parent Id

Tesseract OCR “VCRUNTIME140.dll is missing from your computer” but sample solution works?

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问题 I installed the Tesseract NuGet Package in my Visual Studio 2013 solution and during runtime when I initialise a Tesseract enginge it throws the error "The program can't start because VCRUNTIME140.dll is missing from your computer. Try reinstalling the program to fix this problem." The strange thing is that a sample solution found here does compile, build and run, and either can find the dll or doesn't need it? I've checked the Configuration Manager and the Reference Manager. They all have