tesseract

TesseractNotFound issue when containerizing in docker

由 独自空忆成欢 提交于 2021-01-01 08:14:57
问题 Problem: I had tesseract installed in local machine and its path is at /usr/local/Cellar/tesseract/4.1.1/bin/tesseract . Everything works perfectly until I containerized it in docker with error message as: pytesseract.pytesseract.TesseractNotFoundError: is not installed or it's not your PATH What I've tried: Based on the error message, this is what I've tried: 1). Add PATH in docker desktop app under file sharing to /usr/local and mount the file path from local to docker - still getting the

TesseractNotFound issue when containerizing in docker

由 我的未来我决定 提交于 2021-01-01 08:12:53
问题 Problem: I had tesseract installed in local machine and its path is at /usr/local/Cellar/tesseract/4.1.1/bin/tesseract . Everything works perfectly until I containerized it in docker with error message as: pytesseract.pytesseract.TesseractNotFoundError: is not installed or it's not your PATH What I've tried: Based on the error message, this is what I've tried: 1). Add PATH in docker desktop app under file sharing to /usr/local and mount the file path from local to docker - still getting the

How to Make Tesseract Faster [closed]

由 人盡茶涼 提交于 2020-12-29 08:12:16
问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 4 years ago . Improve this question This is a long shot, but I have to ask. I need any ideas that might make Tesseract OCR engine faster. I'm processing 2M PDFs consisting of about 20M pages of text, and I need to get every bit of performance that I can. Current estimate is that this will take

How to Make Tesseract Faster [closed]

由 做~自己de王妃 提交于 2020-12-29 08:10:59
问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 4 years ago . Improve this question This is a long shot, but I have to ask. I need any ideas that might make Tesseract OCR engine faster. I'm processing 2M PDFs consisting of about 20M pages of text, and I need to get every bit of performance that I can. Current estimate is that this will take

How to Make Tesseract Faster [closed]

由 ℡╲_俬逩灬. 提交于 2020-12-29 08:09:08
问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 4 years ago . Improve this question This is a long shot, but I have to ask. I need any ideas that might make Tesseract OCR engine faster. I'm processing 2M PDFs consisting of about 20M pages of text, and I need to get every bit of performance that I can. Current estimate is that this will take

opencv--文档扫描OCR识别

由 有些话、适合烂在心里 提交于 2020-12-12 09:59:41
检测流程： 边缘检测 -> 获得轮廓 -> 透视变换(即放平，包括平移旋转反转等) -> OCR识别 一、边缘检测 if __name__ == "__main__": # 读取输入 image = cv2.imread(args["image"]) # resize 坐标也会相同变化 ratio = image.shape[0] / 500.0 orig = image.copy() image = resize(orig, height = 500) # 同比例变化：h指定500,w也会跟着变化 # 预处理 gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) gray = cv2.GaussianBlur(gray, (5, 5), 0)#去噪声 edged = cv2.Canny(gray, 75, 200) # 边缘检测 # 展示预处理结果 print("STEP 1: 边缘检测") cv2.imshow("Image", image) cv2.imshow("Edged", edged) cv2.waitKey(0) cv2.destroyAllWindows() 注： Line 5：缩放比例 ratio 也可以resize后再计算，透视变换中还原到原始的原图上时，需要用到ratio 二、获得轮廓 在main函数下 # 轮廓检测

Tesseract quiet mode

由 不羁的心 提交于 2020-12-05 12:26:35
问题 Under Ubuntu I use tesseract-ocr in version 3.02. Especially the wrapper pytesseract for python, but this question is also about the commandline-tool. In the FAQ under https://code.google.com/p/tesseract-ocr/wiki/FAQ#How_can_I_make_the_error_messages_go_to_tesseract.log_instead_of is written that there is a option/config-file "quiet" supressing the info line of tesseract. However, when I call tesseract command line with this option, it says "read_params_file: Can't open quiet" And it is right

Tesseract OCR text order for documents with tables or rows

由 给你一囗甜甜゛ 提交于 2020-12-01 07:24:31
问题 I am using Tesseract OCR to convert scanned PDF's into plain text. Overall it is highly effective but I am having issues with the order that the text is scanned. Documents with tabular data seem to scan down column by column when it seems like the more natural way would be to scan row by row. A very small scale example would be: This is column A, row 1 This is column B, row 1 This is column C, row 1 This is column A, row 2 This is column B, row 2 This is column C, row 2 Is yielding the

Tesseract OCR text order for documents with tables or rows

由 断了今生、忘了曾经 提交于 2020-12-01 07:23:44
问题 I am using Tesseract OCR to convert scanned PDF's into plain text. Overall it is highly effective but I am having issues with the order that the text is scanned. Documents with tabular data seem to scan down column by column when it seems like the more natural way would be to scan row by row. A very small scale example would be: This is column A, row 1 This is column B, row 1 This is column C, row 1 This is column A, row 2 This is column B, row 2 This is column C, row 2 Is yielding the

python之web自动化验证码识别解决方案

由 主宰稳场 提交于 2020-11-26 04:26:29
验证码识别解决方案 对于web应用程序来讲，处于安全性考虑，在登录的时候，都会设置验证码，验证码的类型种类繁多，有图片中辨别数字字母的，有点击图片中指定的文字的，也有算术计算结果的，再复杂一点就是滑动验证的。诸如此类的验证码，对我们的系统增加了安全性的保障，但是对于我们测试人员来讲，在自动化测试的过程中，无疑是一个棘手的问题。 1、web自动化验证码解决方案 一般在我们测试过程中，登录遇到上述的验证码的时候，有以下种解决方案: 第一种、让开发去掉验证码 第二种、设置一个万能的验证码 第三种、通过cookie绕过登录 第四种、自动识别技术识别验证码 2、自动识别技术识别验证码 前三种解决方案，想必大家都比较了解，本文重点阐述第四种解决方案，也就是验证码的自动识别，关于验证码识别这一块，可以通过两个方案来解决， 第一种是：OCR自动识别技术， 第二种是：通过第三方打码平台的接口来识别。 OCR识别技术 OCR中文名称光学识别， tesseract是一个有名的开源OCR识别框架，它与Leptonica图片处理库结合，可以读取各种格式的图像并将它们转化成超过60种语言的文本，可以不断训练自己的识别库，使图像转换文本的能力不断增强。如果团队深度需要，还可以以它为模板，开发出符合自身需求的OCR引擎。那么接下来给大家介绍一下如何使用tessract来识别我们的验证码。 关于OCR自动识别这一块
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