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

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
uoip / KCFpy

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