Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

On 10/29/2013 07:19 AM, jim vickroy wrote: On 10/29/2013 5:11 AM, Olivier Grisel wrote: 2013/10/23 j vickroy: On 10/23/2013 10:18 AM, Andreas Mueller wrote: FYI, the features I would use for the superpixel based approach would be "color" histogramms (bag of words of channel intensities): Resha

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

On 10/29/2013 5:11 AM, Olivier Grisel wrote: 2013/10/23 j vickroy : On 10/23/2013 10:18 AM, Andreas Mueller wrote: FYI, the features I would use for the superpixel based approach would be "color" histogramms (bag of words of channel intensities): Reshape the images to (-1, 6) so you have lists

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

2013/10/23 j vickroy : > On 10/23/2013 10:18 AM, Andreas Mueller wrote: >> FYI, the features I would use for the superpixel based approach would be >> "color" histogramms (bag of words of channel intensities): >> Reshape the images to (-1, 6) so you have lists of pixels (subsample if >> they are ma

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

On 10/23/2013 10:18 AM, Andreas Mueller wrote: > FYI, the features I would use for the superpixel based approach would be > "color" histogramms (bag of words of channel intensities): > Reshape the images to (-1, 6) so you have lists of pixels (subsample if > they are many), run (MiniBatch)KMeans, a

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

Thanks Kyle! I'm certainly interested in any followup suggestions you may have. I probably could send a sample, labeled map. They are not publicly available yet, but eventually they will be on a web site in near-real-time. During our so-called "proving ground" phase, we are using NASA SDO/AIA

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

FYI, the features I would use for the superpixel based approach would be "color" histogramms (bag of words of channel intensities): Reshape the images to (-1, 6) so you have lists of pixels (subsample if they are many), run (MiniBatch)KMeans, and use the cluster-histograms as features to describ

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

If differences in the labels correspond to borders in the image, then you should try a superpixel base approach. Run SLIC from skimage and see if you would be ok with labeling each of the resulting superpixels with a single label (you may need to adjust the number of superpixels produced -- oh a

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

Other lists of techniques to look at: Convolutional Neural Networks are another approach to image classification. This goes outside the realm of sklearn, but has been used successfully on some fairly complex data. For example, I have some code at https://github.com/kastnerkyle/kaggle-cifar10 which

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

On 10/22/2013 9:30 PM, Andreas Mueller wrote: I would also suggest the book "computer vision" by Richard Szeliski. For you classification problem it really depends on what you want as output and what the statistics of the data are. If I understand you correctly, you want a prediction for each l

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

I would also suggest the book "computer vision" by Richard Szeliski. For you classification problem it really depends on what you want as output and what the statistics of the data are. If I understand you correctly, you want a prediction for each label. If your images are somewhat natural, the

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

On 10/22/2013 3:32 PM, Joseph Jacobs wrote: The best book I have come across for image processing/vision + machine learning is one by Simon Prince. You can download the book from his website (http://computervisionmodels.com/). Chapter 13 gives a good intro to feature extraction. OK, great --

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

On 10/22/2013 3:32 PM, Joseph Jacobs wrote: The best book I have come across for image processing/vision + machine learning is one by Simon Prince. You can download the book from his website (http://computervisionmodels.com/). Chapter 13 gives a good intro to feature extraction. Joe On 22 Oc

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

The best book I have come across for image processing/vision + machine learning is one by Simon Prince. You can download the book from his website (http://computervisionmodels.com/). Chapter 13 gives a good intro to feature extraction. Joe On 22 Oct 2013, at 22:27, jim vickroy wrote: > On 10/

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

On 10/22/2013 2:47 PM, Joseph Jacobs wrote: Hey Jim, From my (non-expert) perspective, performing classification pixel-wise would not be ideal (please correct me if I am wrong). I think the better way would be to perform some sort of feature extraction on the image (eg. SIFT, SURF, HOG, LBP a

Re: [Scikit-learn-general] Image Feature Classification Conceptual Fog

Hey Jim, From my (non-expert) perspective, performing classification pixel-wise would not be ideal (please correct me if I am wrong). I think the better way would be to perform some sort of feature extraction on the image (eg. SIFT, SURF, HOG, LBP and many, many more...checkout scikit-image or

[Scikit-learn-general] Image Feature Classification Conceptual Fog

Hi, Apologies if this is an inappropriate question for this forum. I have a collection of (1024x1024) mono-chromatic images in which each pixel is to be labeled as 1 of several categories (e.g., 10). Furthermore, each mono-chromatic image was captured through several filters (e.g., 5). My