image-recognition

I've been looking around for some papers (or info) on this topic. To avoid a misunderstanding: I'm not talking about finding a supplied pattern in multiple locations. Repeating patterns can also be understood to mean repeating images. The definition of pattern here isn't abstract. Imagine, for instance, a brick wall. The wall is composed of individual bricks. A picture of the wall is composed of the repeating image of a brick. The solution must preferably find the largest repeating pattern. Large in this context can be defined two ways: pixel area or number of repetitions. In the above example

I am a newbie in TensorFlow. Currently, I am testing some classification's examples "Convolutional Neural Network" in the TensorFlow website, and it explains how to classify input images into pre-defined classes, but the problem is: I can't figure out how to locate multiple objects in the same image. For example, I had an input image with a cat and dog and I want my graph to display in the output that there are both of them "a cat and a dog" in the image. Great question. Detecting multiple objects in the same image boils is essentially a "segmentation problem". Two nice and popular algorithms

Is there any free PHP OCR API, that is well documented in PHP, jQuery or JavaScript? I'm programming a web app for iOS and I'd like to utilize the new photo upload API in iOS 6 safari to use for OCR image processing. Thanks a ton! :) ( Edit: Oh and a Google-Googles like API for image recognition would also suffice, it doesn't have to be OCR, though I would pefer it. :) Tesseract is really simple to use. Someone has even written a PHP wrapper for it so you won't have to deal with the exec() command. Have a look at this here: http://github.com/thiagoalessio/tesseract-ocr-for-php You can try http

I want to build a clothing classifier that takes a photo of an item of clothing and classifies it as 'jeans', 'dress', 'trainers' etc. Some examples: These images are from retailer websites, so are typically taken from the same angle, typically on a white or pale background -- they tend to be very similar. I have a set of several thousand images whose category I already know, which I can use to train a machine-learning algorithm. However, I'm struggling for ideas of what features I should use. The features I have so far: def get_aspect_ratio(pil_image): _, _, width, height = pil_image.getbbox(

Sadly, the face.com API is being shut down due acquisition by Facebook. Are there any decent alternatives out there? I'm looking to check for a given image if there is a face in it + demographics content about it. bcmoney Sad news indeed. If you have a good reason and already have an account, they may extend you until October, 2012: http://developers.face.com/extension-request/ For everyone else, here's a list of potential alternatives I've compiled: OpenCV: http://opencv.willowgarage.com/ (C/C++ but at least its opensource, standalone and downloadable) Viewdle (Objective-C)... bought/axed by

clock http://img710.imageshack.us/img710/2623/circlock.jpg I do not know how to determine the top of the needle of the clock. If you determine the coordinates of them, I can think of the time of the clock. Please help me solve this problem. Thank you very much! Test points in a circle of radius M, around the centre of the clock. (You could use a for loop to vary the angle from -pi to pi.) First set M so that the long hand will touch the circle but not the short hand. You will find a region of black points and these reveal the angle of the long hand. Then repeat with smaller M, so your circle

I know there is a lot of vision recognition APIs such as Clarifai, Watson, Google Cloud Vision, Microsoft Cognitive Services which provide recognition of image content. The response of these services is simple json that contains different tags, for example { man: 0.9969295263290405, portrait: 0.9949591159820557, face: 0.9261120557785034 } The problem is that I need to know not only what is on the image but also the position of that object. Some of those APIs have such feature but only for face detection. So does anyone know if there is such API or I need to train own haar cascades on OpenCV

I'm not sure what this error means. This error occurs when I try to calculate acc : acc = accuracy.eval(feed_dict = {x: batch_images, y: batch_labels, keep_prob: 1.0}) I've tried looking up solutions, but I couldn't find any online. Any ideas on what's causing my error? Here's a link to my full code . I had a similar error but the problem for me was that I was trying to use argmax on a 1 dimensional vector. So the shape of my label was (50,) and I was trying to do a tf.argmax(y,1) on that when evaluating. The solution reference is Tensorflow: I get something wrong in accuracy The source code