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I think the code has some question in ' def getFeature()' #9

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StormArcher opened this issue Dec 22, 2018 · 1 comment
Open

I think the code has some question in ' def getFeature()' #9

StormArcher opened this issue Dec 22, 2018 · 1 comment

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@StormArcher
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StormArcher commented Dec 22, 2018

def getFeatures(self, image, inithann, scale_adjust=1.0):
	extracted_roi = [0,0,0,0]   #[int,int,int,int]
	cx = self._roi[0] + self._roi[2]/2  #float
	cy = self._roi[1] + self._roi[3]/2  #float

	if(inithann):
		padded_w = self._roi[2] * self.padding
		padded_h = self._roi[3] * self.padding

		if(self.template_size > 1):
			if(padded_w >= padded_h):
				self._scale = padded_w / float(self.template_size)
			else:
				self._scale = padded_h / float(self.template_size)
			self._tmpl_sz[0] = int(padded_w / self._scale)
			self._tmpl_sz[1] = int(padded_h / self._scale)
		else:
			self._tmpl_sz[0] = int(padded_w)
			self._tmpl_sz[1] = int(padded_h)
			self._scale = 1.

		if(self._hogfeatures):
			self._tmpl_sz[0] = int(self._tmpl_sz[0]) / (2*self.cell_size) * 2*self.cell_size + 2*self.cell_size
			self._tmpl_sz[1] = int(self._tmpl_sz[1]) / (2*self.cell_size) * 2*self.cell_size + 2*self.cell_size
		else:
			self._tmpl_sz[0] = int(self._tmpl_sz[0]) / 2 * 2
			self._tmpl_sz[1] = int(self._tmpl_sz[1]) / 2 * 2

	extracted_roi[2] = int(scale_adjust * self._scale * self._tmpl_sz[0])
	extracted_roi[3] = int(scale_adjust * self._scale * self._tmpl_sz[1])
	extracted_roi[0] = int(cx - extracted_roi[2]/2)
	extracted_roi[1] = int(cy - extracted_roi[3]/2)

	z = subwindow(image, extracted_roi, cv2.BORDER_REPLICATE)
	if(z.shape[1]!=self._tmpl_sz[0] or z.shape[0]!=self._tmpl_sz[1]):
		z = cv2.resize(z, tuple(self._tmpl_sz))

	if(self._hogfeatures):
		mapp = {'sizeX':0, 'sizeY':0, 'numFeatures':0, 'map':0}
		mapp = fhog.getFeatureMaps(z, self.cell_size, mapp)
		mapp = fhog.normalizeAndTruncate(mapp, 0.2)
		mapp = fhog.PCAFeatureMaps(mapp)
		self.size_patch = map(int, [mapp['sizeY'], mapp['sizeX'], mapp['numFeatures']])
		FeaturesMap = mapp['map'].reshape((self.size_patch[0]*self.size_patch[1], self.size_patch[2])).T   # (size_patch[2], size_patch[0]*size_patch[1])
	else:
		if(z.ndim==3 and z.shape[2]==3):
			FeaturesMap = cv2.cvtColor(z, cv2.COLOR_BGR2GRAY)   # z:(size_patch[0], size_patch[1], 3)  FeaturesMap:(size_patch[0], size_patch[1])   #np.int8  #0~255
		elif(z.ndim==2):
			FeaturesMap = z   #(size_patch[0], size_patch[1]) #np.int8  #0~255
		FeaturesMap = FeaturesMap.astype(np.float32) / 255.0 - 0.5
		self.size_patch = [z.shape[0], z.shape[1], 1]

	if(inithann):
		self.createHanningMats()  # createHanningMats need size_patch

	FeaturesMap = self.hann * FeaturesMap
	return FeaturesMap
@StormArcher
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FeaturesMap
i find the FeaturesMap is a local variables .and not be define before

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