What I do:
1.I installed the opencv-plugin-sample in the kurenoMediaPlayer(from the link https://github.com/Kurento/kms-opencv-plugin-sample) and run a sample opencv face detection.
What i have to do:
1.Now i need to integrate caffe(http://caffe.berkeleyvision.org/install_apt.html) into KMS ,so I can able to run more complex opencv algorithms in KMS.
What I need to know:
1.Is there any specific way to integrate caffe in KurentoMediaServer?
Related
I'm trying to migrate an algorithm that uses a 2d histogram to run using the new G-API on OpenCV. I see that there is equalizeHist() available, but not calcHist(). Is there any way to calculate the histogram using the new Graph API?
Please open an issue at OpenCV GitHub so we take this to work. Meanwhile, the API is extensible so you can add a missing operation/kernel locally (within your app): https://docs.opencv.org/master/d0/d25/gapi_kernel_api.html
I want to implement Structur from Motion (SfM) / Simultaneous Localization and mapping algorithms using my webcam. I am very new on this topic so I need advices from experts in the internet. I could now able to build OpenCV opencv sfm tutorial for this purpose and I looked OpenSFM but it seems like just a GUI. What other open libraries/programs that I can use for this task? any suggestions/advices/tutorials are appreciated.
I need to use an OCR library and have been trying to use Tesseract. The problem is that the accuracy of Tesseract on a few test images is not very good. I'm not able to improve the quality of the images either as they are going to be submitted by users.
However, when I uploaded the file using the OCR feature in GoogleDocs it was able to read the image perfectly. I was wondering whether there a google OCR library, I know it has been improving Tesseract, or is the Google OCR library strictly proprietary (I presume it is)?
Thanks
to have a good result and good detection, you may need to improve the detection by using some filters and automatic thresholding. You can try PILLOW library for filters and image manipulation.
Could anybody suggest an automatic way to convert from a list of images (without Kinect) to a point cloud in opencv?
Take a look at OpenCV Contrib Structure From Motion module (SFM). There are two nice examples trajectory_reconstruction.cpp and scene_reconstruction.cpp.
Also, there is alternative called Multi-View Environment which you could find on GitHub at simonfuhrmann/mve and which might meet your criteria too.
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.