detection

I do get track the "real" IP of an user, if he has an proxy wich sends the header of the real IP... does any of have a better solution, or even more headers? Since this function is used very often in the script, it has to be very fast, and it does not seem in that constellation :/ A few suggestions I came up with, but could not realise: put the headers in the order, what is used the most "in the wild", sothat the functions finishes fast making the pre_match-detecting for IP faster === function get_real_ip() { $proxy_headers = array( 'CLIENT_IP', 'FORWARDED', 'FORWARDED_FOR', 'FORWARDED_FOR_IP'

Are there any good, open source engines out there for detecting what language a text is in, perhaps with a probability metric? One that I can run locally and doesn't query Google or Bing? I'd like to detect language for each page in about 15 million pages of OCR'ed text. Not all documents will contain languages which use the Latin alphabet. Depending on what you're doing, you might want to check out the python Natural Language Processing Toolkit (NLTK), which has some support for Bayesian Learning Algorithms. In general, the letter and word frequencies would probably be the fastest evaluation,

Has anyone implement the FRCNN for TensorFlow version? I found some related repos as following: Implement roi pool layer Implement fast RCNN based on py-faster-rcnn repo but for 1: assume the roi pooling layer works (I haven't tried), and there are something need to be implemented as following: ROI data layer e.g. roidb . Linear Regression e.g. SmoothL1Loss ROI pool layer post-processing for end-to-end training which should convert the ROI pooling layer's results to feed into CNN for classifier. For 2: em...., it seems based on py-faster-rcnn which based on Caffe to prepared pre-processing (e

I'm looking for a way to detect which of two (similar) images is sharper. I'm thinking this could be using some measure of overall sharpness and generating a score (hypothetical example: image1 has sharpness score of 9, image2 has sharpness score of 7; so image1 is sharper) I've done some searches for sharpness detection/scoring algorithms, but have only come across ones that will enhance image sharpness. Has anyone done something like this, or have any useful resources/leads? I would be using this functionality in the context of a webapp, so PHP or C/C++ is preferred. The simple method is to

I'm working in a project. A part of project consist to integrate the HOG people detector of OpenCV with a camera streaming . Currently It's working the camera and the basic HOG detector (CPP detectMultiScale -> http://docs.opencv.org/modules/gpu/doc/object_detection.html ). But don't work very well... The detections are very noising and the algorithm isn't very accuracy... Why? My camera image is 640 x 480 pixels. The snippet code I'm using is: std::vector<cv::Rect> found, found_filtered; cv::HOGDescriptor hog; hog.setSVMDetector(cv::HOGDescriptor::getDefaultPeopleDetector()); hog