I am trying optimize my DCGAN code but cant find anything on how to actually implement feature matching and i cant figure it out, any help would be greatly appreacieted.
i am using DCGAN code from the pytorch tutorial: https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html
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I have to create a workflow that uses pytorch models or torch script models in c++. However, I can't find the binary format. I tried looking through the serializer but to no avail. Does anybody have documentation or code that gives me a clue as to the model format?
PyTorch has a great tutorial of Tracing/Scripting models and Loading them via C++.
I'm trying to get a start on using opencv in python to do some object detection. Are there any example code projects out there?
I've seen some examples that are specific to face detection but they seem to use preprocessed data that I don't know how to generate.
Thanks!
There are a lot of examples, but I would suggest in any case to give a look at the following sources:
http://opencv-python-tutroals.readthedocs.org/en/latest/
http://www.pyimagesearch.com/
I want to create grabcut algorithm for image processing but i can't find perfect implementation .I have tried so many code but i cant found solution.
is there any example for Grabcut in openCV.So I can implement in my application.?
You can check this tutorial here.
grabcut algorithm
People reply to problems independently. Please do not demand to reply fast. Googling the problem will get you some hints.
Cheers.
See this repository.
It is demo application using GrabCut
https://github.com/naver/grabcutIOS
I am new in opencv and I want to work on face detection methods. I have understand that one of the best methods is by haar features. I know some functions in opencv library for detection faces and training.
can any one help me to understand how haarcascade_frontalface_alt.xml is made?
and how can I modify this file?
thanks a lot for your help.
First read this:
http://docs.opencv.org/doc/user_guide/ug_traincascade.html
followed by:
http://note.sonots.com/SciSoftware/haartraining.html
http://opencvuser.blogspot.in/2011/08/creating-haar-cascade-classifier-aka.html
http://achuwilson.wordpress.com/2011/07/01/create-your-own-haar-classifier-for-detecting-objects-in-opencv/
Start with good training data.
Cheers.
I´m a beginner on computer vision, but I know how to use some functions on opencv. I´m tryng to use Opencv for Document Recognition, I want a help to find the steps for it.
I´m thinking to use opencv example find_obj.cpp , but the documents, for example passport, has some variables, name, birthdate, pictures. So, I need a help to define the steps for it, and if is possible how function I have to use on the steps.
I'm not asking a whole code, but if anyone has any example link or you can just type a walkthrough, it is of great help.
There are two very different steps involved here. One is detecting your object, and the other is analyzing it.
For object detection, you're just trying to figure out whether the object is in the frame, and approximately where it's located. The OpenCv features framework is great for this. For some tutorials and comprehensive sample code, see the OpenCv features2d tutorials and especially the feature matching tutorial.
For analysis, you need to dig into optical character recognition (OCR). OpenCv does not include OCR libraries, but I recommend checking out tesseract-ocr, which is a great OCR library. If your documents have a fixed structured (consistent layout of text fields) then tesseract-ocr is all you need. For more advanced analysis checking out ocropus, which uses tesseract-ocr but adds layout analysis.