class,image_path,name,xmax,xmin,ymax,ymin
3.0,4a48c42c9579ec0399e6c5a3e825e765.jpg,GARBAGE,797.0,701.0,262.0,211.0
3.0,4a48c42c9579ec0399e6c5a3e825e765.jpg,GARBAGE,932.0,786.0,329.0,238.0
3.0,4a48c42c9579ec0399e6c5a3e825e765.jpg,GARBAGE,736.0,657.0,275.0,229.0
7.0,ea906a663da6321bcef78be4b7d1afff.jpg,BAD_BILLBOARD,986.0,786.0,136.0,0.0
8.0,1c7d48005a12d1b19261b8e71df7cafe.jpg,SAND_ON_ROAD,667.0,549.0,228.0,179.0
8.0,1c7d48005a12d1b19261b8e71df7cafe.jpg,SAND_ON_ROAD,799.0,628.0,238.0,176.0
How to covert above .CSV file to yolo format and through which platform?
I am a beginner and I want to convert above .csv file to yolo format.
I found below link for reference but still not able to solve the problem.
Reference solution : How to convert polygon coordinates to rectangle(yolo format) for an image labelling?
I am not getting how to integrate the above piece of code (provided in the link) with my .csv file to convert it into the YOLO Format.
you can use Roboflow for this purpose. It can automatically convert annotations into various formats. visit: https://app.roboflow.com/
I am working on invoice parser which extracts data from invoices in pdf or image format.It works on simple pdf with non tabular data but gives lots of output data to process with pdf which contains tables.I am not able to get a working generic solution for this.I have tried the following libraries
Invoice2Data : It is based on templates.It has given fairly good results in json format till now.But Template creation for complex pdfs containing dynamic table is complex.
Tabula : Table extraction is based on coordinates of the table to be extracted.If the data in the table increases the table length increases and hence the coordinates changes.So in this case it gives wrong results.
Pdftotext : It converts any pdfs to text but with the format that needs lots of parsing which we do not want.
Aws_Textract and Elis_Rossum_Ai : Gives all the data in json format.But if the table column contains multiple line then json parsing becomes difficult.Even the json given is huge in size to parse.
Tesseract : Same as pdftotext.Complex pdfs are not parseable.
Other than all this or with combination of the above libraries has anyone been able to parse complex pdf data please help.
I am working on a similar business problem. since invoices don't have fixed format so you can't directly use any text parsing method.
To solve this problem you have to use Computer Vision (Deep Learning) for field detection and Pytesseract OCR for converting image into text. For better understanding here are the steps:
Convert invoices to image and annotate the images with fields like address, Amount etc using tools like labelImg. (For better results use different types of 500-1000 invoices)
After Generating XML files train any object detection model like YOLO or TF object detection API.
The model will detect the fields and gives you coordinates of Region Of Interest(ROI). like
Apply Pytessract OCR on the ROI coordinates. Click Here
Finally, use regex to validate the text in the extracted field and perform any manipulation/transformation that is necessary. At last store data to CSV OR Database.
Hope my answer helps you! Upvote answer so it reaches to maximum people.
While Compressing a file Using Huffmann coding,
After assigning Huffmann codes to each character in a file, these characters should be replaced with equivalent Huffmann codes in the compressed file. Then how the equivalent characters gets extracted with those Huffman codes from the compressed files while decompressing the file. Do the compressed file contains some extra information to decode the Huffmann codes?
Yes. You need to send a description of the Huffman code in order to decode them.
The usual implementation is to encode using a canonical Huffman code, and then sending just the lengths for each symbol. The description of the code can itself be compressed.
I download some files, such as word, ppt, excel. But i don't know their MIMETYPE and suffix. Is there some way can get MIMETYPE of these file?
If you don't know the suffix, you're forced to look at the file contents. Typically this starts with looking for magic bytes, the first few bytes of the file. You can often qualify the type of file on that basis (though you obviously can't be sure unless you validate the whole file).
For modern Office documents, they should conform to OOXML and the first two bytes should be 0x50 0x4b (i.e. "PK") the indicator of a zip file.
You can then uncompress it (e.g. with ZipArchive).
You can then either parse the docProps/app.xml or see Office Open XML site with links at the top of the page for how to parse word processing, excel, and presentations, respectively.
I want to combine three different kind of data: jpeg, m4a, and utf8 text in one data file. Could anyone recommend any suitable data delimiter?
Particularly, I'm working on iOS.