descriptor

please i like to classify a set of image in 4 class with SIFT DESCRIPTOR and SVM. Now, using SIFT extractor I get keypoints of different sizes exemple img1 have 100 keypoints img2 have 55 keypoints.... how build histograms that give fixed size vectors with matlab In this case, perhaps dense sift is a good choice. There are two main stages: Stage 1 : Creating a codebook. Divide the input image into a set of sub-images. Apply sift on each sub-image. Each key point will have 128 dimensional feature vector. Encode these vectors to create a codebook by simply applying k-means clustering with a

According to Python's documentation , Data descriptors with __set__() and __get__() defined always override a redefinition in an instance dictionary. I have no problem understanding this sentence, but can someone clarify for me why such a rule is in place? After all, if I want to override an attribute in an instance dictionary, I already need to do that explicitely ( inst.__dict__["attr"] = val ), as a naive inst.attr = val would call the descriptor's __set__ method, which would (usually) not override the attribute in the instance dictionary. edit: just to make it clear, I understand what is

I'm attempting to build a decorator for an instance method of a class that will memoize the result. (This has been done a million times before) However, I'd like the option of being able to reset the memoized cache at any point (say, if something in the instance state changes, which might change the result of the method having nothing to do with its args). So, I attempted to build a decorator as a class instead of a function, so that I might have access to the cache as a class member. This led me down the path of learning about descriptors, specifically the __get__ method, which is where I'm

I'm aware that a property is a descriptor, but are there specific examples of when using a descriptor class might be more advantageous, pythonic, or provide some benefit over using @property on a method function? Better encapsulation and re-usability: A descriptor class can have custom attributes set on instantiating. Sometimes it's useful to keep data confined in this manner, instead of having to worry about it getting set or overwritten on the descriptor's owner. Let me quote from the EuroPython 2012 great video "Discovering Descriptors" : How to choose between descriptors and properties:

I am trying to use opencv with python. I wrote a descriptor (SIFT, SURF, or ORB) matching code in C++ version of opencv 2.4. I want to convert this code to opencv with python. I found some documents about how to use opencv functions in c++ but many of the opencv function in python I could not find how to use them. Here is my python code, and my current problem is that I don't know how to use "drawMatches" of opencv c++ in python. I found cv2.DRAW_MATCHES_FLAGS_DEFAULT but I have no idea how to use it. Here is my python code of matching using ORB descriptors: im1 = cv2.imread(r'C:\boldt.jpg')

To the question: Why can't descriptors be instance attributes? it has been answered that: descriptor objects needs to live in the class, not in the instance because that is the way that the __getattribute__ is implemented. A simple example. Consider a descriptor: class Prop(object): def __get__(self, obj, objtype=None): if obj is None: return self return obj._value * obj._multiplier def __set__(self, obj, value): if obj is None: return self obj._value = value class Obj(object): val = Prop() def __init__(self): self._value = 1 self._multiplier = 0 Consider the case in which each obj has

When I make the "data" variable a class variable, the following works, but when I make it an object variable, the descriptor is not called. Please help. class Data(object): products = { 'milk': {'price': 1.50, 'quantity': 10}, 'eggs': {'price': 0.20, 'quantity': 100}, 'cheese': {'price': 2.00, 'quantity': 10} } def __get__(self, obj, klas): print "Here in descriptor" return self.products class BusinessLogic(object): def __init__(self): # When I remove these 2 lines self.data = Data() #data = Data() # and enable this line it does work ! def main(): b = BusinessLogic() b.data if __name__ == '_