vision

I need to use a neural network in my OpenCV (version 3.0) project. I've created and trained neural network and it works, but if I want to load neural network from YML file, it doesn't predict. This is a code where I creat, train and save my neural network: FileStorage fs("nn.yml", FileStorage::WRITE); int input_neurons = 7; int hidden_neurons = 100; int output_neurons = 5; Ptr<TrainData> train_data = TrainData::loadFromCSV("data.csv", 10, 7, 12); Ptr<ANN_MLP> neural_network = ANN_MLP::create(); neural_network->setTrainMethod(ANN_MLP::BACKPROP); neural_network->setBackpropMomentumScale(0.1);

I would like to keep everything contained within the virtualenv. Is this possible with OpenCV? I'm fine with building from scratch, do I just need to setup the virtualenv first then use special compile flags to tell it where to install to? I found the solution was that I had to copy over cv2.so and cv.py to the directory running the virtualenv, then pip install numpy. To do this on Ubuntu 12.04 I used. virtualenv virtopencv cd virtopencv cp /usr/local/lib/python2.7/dist-packages/cv* ./lib/python2.7/site-packages/ ./bin/pip install numpy source bin/activate python import cv From opencv install

I often work with scanned papers. The papers contain tables (similar to Excel tables) which I need to type into the computer manually. To make the task worse the tables can be of different number of columns. Manually entering them into Excel is mundane to say the least. I thought I can save myself a week of work if I can put a program to OCR it. Would it be possible to detect headers text areas with the OpenCV and OCR the text behind the detected image coordinates. Can I achieve this with the help of OpenCV or do I need entirely different approach? Edit: Example table is really just a standard