Add Bow histogram computation #26
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… can train a vocabulary of words. Based on SIFT descriptors
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Hey @niosus would you have time to review this one? |
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A solid PR, @ovysotska! I left a couple of nitpicks here and there, but feel free to ignore them. I think the code is easy to read and the intent is clear. Added plus for having a couple of tests.
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| def rescaleImageIfNeeded(image): |
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nit: very minor, but you seem to have docs for the other functions and not for these. Maybe add docstring to these too?
src/python/bow/bow.py
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| def computeIDF(descriptorsPerImage, clusters): | ||
| """Compute inverse document frequence (IDF). Here means in how many images does the word occur. |
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Here means in how many images does the word occur.
nit: This reads a bit strange. What did you mean to say here?
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I meant the IDF (which is inverse document frequency) , here stands for how many images (not documents) does the word occur in.
src/python/bow/bow.py
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| descriptors = [ | ||
| descriptor for descriptors in descriptorsPerImage for descriptor in descriptors | ||
| ] | ||
| descriptors = np.array(descriptors) |
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I don't really know how to improve this, but the naming seems to be overloaded here. The word descriptors is very overused here. Maybe use more descriptive names?
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It is the best. I also don't know now what that suppose to be :)
src/python/bow/bow.py
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| idfs = computeIDF(descriptorsPerImage, words) | ||
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| plt.bar(range(0, len(idfs)), idfs) | ||
| plt.savefig("idf_" + str(kDefaultClusterSize) + ".png") |
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nit: Do you want to always save these images? Or should it be hidden behind some flag?
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Neh, not really important. Will just remove it and reduce the dependencies list.
src/python/bow/bow.py
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| def getVocabulary(imageTrainFolder, vocabularyFile): | ||
| if vocabularyFile is not None: |
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nit: you can simplify this to:
if vocabularyFile and vocabularyFile.exists():
This PR adds the Python code to:
In the testing mode, the code takes a folder with images and returns the np.array of Bow features stored in the specified file.
The computed features can be used in the current codebase further, by first turning them into proto files, and then the full pipeline for image_sequence_localizer can be used as usual.