ae9cf55f6a5775a0d39a869166e8b33d4f39c273,region_properties.py,RegionProperties,__compute_mask,#RegionProperties#,59

Before Change

        mask_temp[mask_temp < 0.5] = False
        mask_temp[mask_temp >= 0.5] = True
        mask_temp = np.tile(mask_temp, [1, 1, 1, self.img.shape[3]])
        masked_array = ma.masked_array(self.img, mask_temp)
        return masked_array.reshape(-1, masked_array.shape[-1])

    def centre_of_mass(self):
        return np.mean(np.argwhere(self.seg > self.threshold), 0)

After Change

    def __compute_mask(self):
        // TODO: check whether this works for probabilities type
        foreground_selector = np.where((self.seg > 0).reshape(-1))[0]
        probs = self.seg.reshape(-1)[foreground_selector]
        regions = np.zeros((foreground_selector.shape[0], self.img_channels))
        for i in np.arange(self.img_channels):
            regions[:,i] = self.img[..., i].reshape(-1)[foreground_selector]
        return regions, probs

    def centre_of_mass(self):
        return np.mean(np.argwhere(self.seg > self.threshold), 0)

Instances