2015-12-19 09:22:25 -0600 | received badge | ● Self-Learner (source) |
2015-12-19 08:41:39 -0600 | received badge | ● Scholar (source) |
2015-12-19 08:40:24 -0600 | answered a question | Train Boost model by huge size of data I found the answer and case closed. I use a Matlab tool box: GML Adaboost solve this problem. I transferred my csv files into .mat, and the dataset is compressed into a 2GB .Mat file from a 60 GB .csv. The model can be trained by this toolbox and export as a txt file. This model can be used in my C++ program by using a parser which provided by GML Adaboost . |
2015-12-16 11:07:08 -0600 | asked a question | Train Boost model by huge size of data Hi all, I am trying to train my dataset (over 15G). Obviously, it is not possible to load entire data set into memory at once. Therefore, I am considering to load my data separately, and it worked fine on my own implementation of adaboost. Now, I would like to train this dataset by OpenCV. I found the training data is store into a smart pointer I need to load all my data, because training process on OpenCV can only input one set of TrainData according to the following OpenCV 3 source code Is there any other function can make me divide my dataset into several chunks and put into training process? If not, does anyone know other adaboost library can handle huge size of data? |
2015-11-05 00:54:29 -0600 | received badge | ● Enthusiast |
2015-11-04 18:48:07 -0600 | commented question | OpenCV 3.0 Assertion fail while train boost model I had tried both |
2015-11-04 02:15:48 -0600 | asked a question | OpenCV 3.0 Assertion fail while train boost model Hi all, I am trying to train my own boosting model, but I encountered Assertion failed on trainning stage. My program is trying to read a CSV file into cv::Mat and use cv::Mat to be the input of trainning process. Following is my code: } And I got this As you can see, the input data is pretty simple, just a four dimensions data. Alternatively, if I used: Then, everything is fine, no assertion failed occured. Does anyone have idea about this? Thanks |
2015-10-11 21:36:37 -0600 | commented question | Using OpenCV 3.0 UMat on Odroid XU3 Ok, thanks for your help. I will keep working on this, and post my answer here if I got one. |
2015-10-07 20:00:43 -0600 | commented question | Using OpenCV 3.0 UMat on Odroid XU3 Hi Steven, thanks for your reply. I did build OpenCV3 with OpenCL enable. In the other way, I think OpenCL on Odroid is supported by OpenCL, because I can derived devices information by OpenCV API. Am I correct or not? |
2015-10-06 23:44:35 -0600 | asked a question | Using OpenCV 3.0 UMat on Odroid XU3 Hi all, I am trying to use OpenCV3.0 OpenCL API on my Odroid XU3. Unfortunately, I am encountering some real weird problems. The following is my devices information which is derived by OpenCL 1.1: I tried to using do some performance test on Odroid by OpenCV3.0 OpenCL API, so I wrote following code: and I got following results on my Odroid: As you can see, the results are merely no differences whether use UMat or not. To ensure UMat really did some effect to performance, I try the exactly same code on my PC, and I got following results: The result showed that performance was dramatically improved by OpenCL. So, why OpenCL API not work on Odroid? Is it related to the version of OpenCL? |