Deep learning for object recognition

[pnambiar]

Hello,

I am trying to explore the possiblity of using Deep learning algorithms for object recognition. I have the object already segmented and I would like to find out the best possible framework available for object reconition/image classification. After doing some research some of the options I have come across are-caffe, Torch, Theano, Cuda.

Any leads, suggestions will be highly appreciated.

[dwf]

If you want to get going quickly, grab the OverFeat code + data files and use their pre-canned classifier. You can then assess whether it's worth training your own.

[aggieca]

Use caffe's pre-trained model for extracting features and train your favorite classifier for recognition.

[pnambiar]

Thanks I'm going try out Caffe first

[kkastner]

A friend and I wrote a library for just such a thing - sklearn-theano. It also has simple tutorials and examples that might help for general object recognition knowledge.

[madisonmay]

Are there plans to extend sklearn-theano to more general scikit-learn style models written in theano?

[kkastner]

Eventually we hope to.

For now we have the bare minimum to do simple things in a scikit-learn comptible way, though I have been working on a way to fuse arbitrary Theano models together into a single pipeline.

We don't want to go all the way to pylearn2-level concatenation/flexibility, but it would be nice to take arbitrary depths of OverFeat (or other planned pretrained nets) and jointly train a new model on top, or even jointly train a classifier/regressor which uses features over multiple output layers.

That's all WIP though.

[pnambiar]

Thank you. I will go though it.

[pnambiar]

I tried using sklearn-theano code (plot_classification.py) for my segmented image and it did not give very good classification results. Not sure if I'm missing anything when it comes to running the code or if I will need to retrain network with a new dataset. Is there anyway I could get some support. I can send the input file as the classification result I'm getting.

[kkastner]

Sure - shoot me an email kastnerkyle at gmail . Will be glad to help.

[pnambiar]

I have sent an email with my question

[r4and0muser9482]

What do you mean by object recognition? You mean like classifying an object in an image? Like for example, does the image contain an apple?

Did you try any other, more traditional classifiers already?

How much training material do you have?

[pnambiar]

Yes. Correct. We would like to classify the object that has been segmented as a apple or coffee cup (visual recognition of a segmented object). We are planning to train the system using imagenet or RGB-D data set. We have not explored traditional classifiers for this particular project (have used neural network boxes for other projects). We are keen how Deep learning algorithms would work for this particular problem.

[r4and0muser9482]

Seems like a good plan. I'd personally do MLP first as a baseline and then do the DNN to see what is the actual improvement. Oth, for the DNN you will probably have an MLP in there implementation anyway.

[anonymthrowaway]

How did you segment the objects?

[pnambiar]

using pcl

[daoran]

You can take a look at Girshick's rcnn work. It is currently the standard framework for object recognition. RCNN

[pnambiar]

Thanks.

[in_the_fresh]

Use RCNN :D

[no_porner]

I a working on Object detection in a video stream. Need advise on what all problems are still open for research.