Python Image.load方法代碼示例

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def test_all(self):
     futures = []
     start = time.time()
     with concurrent.futures.ProcessPoolExecutor() as exec:
         for pdir, sdir, files in os.walk(self.image_bank_dir):
             for file in files:
                 filepath = osp.join(pdir, file)
                 try:
                     Image.load(filepath)
                 except:
                     pass
                 else:
                     future = exec.submit(run_star, filepath)
                     futures.append(future)
         for future in concurrent.futures.as_completed(futures):
             print(future.result())
     end = time.time() - start
     print('Processing of {} files took {}s'.format(len(futures), end))

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
    def load_image(self, filepath):
        """Load the image via the file path.

        Parameters
        ----------
        filepath : str
            Path to the file to be loaded.
        """
        self.image = Image.load(filepath)

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
    def _find_bb(self):
        """Find the BB within the radiation field. Iteratively searches for a circle-like object
        by lowering a low-pass threshold value until found.

        Returns
        -------
        Point
            The weighted-pixel value location of the BB.
        """

        def is_boxlike(array):
            """Whether the binary object's dimensions are symmetric, i.e. box-like"""
            ymin, ymax, xmin, xmax = get_bounding_box(array)
            y = abs(ymax - ymin)
            x = abs(xmax - xmin)
            if x > max(y * 1.05, y+3) or x < min(y * 0.95, y-3):
                return False
            return True

        # get initial starting conditions
        hmin = np.percentile(self.array, 5)
        hmax = self.array.max()
        spread = hmax - hmin
        max_thresh = hmax

        # search for the BB by iteratively lowering the low-pass threshold value until the BB is found.
        found = False
        while not found:
            try:
                lower_thresh = hmax - spread / 2
                t = np.where((max_thresh > self) & (self >= lower_thresh), 1, 0)
                labeled_arr, num_roi = ndimage.measurements.label(t)
                roi_sizes, bin_edges = np.histogram(labeled_arr, bins=num_roi + 1)
                bw_node_cleaned = np.where(labeled_arr == np.argsort(roi_sizes)[-3], 1, 0)
                expected_fill_ratio = np.pi / 4
                actual_fill_ratio = get_filled_area_ratio(bw_node_cleaned)
                if (expected_fill_ratio * 1.1 < actual_fill_ratio) or (actual_fill_ratio < expected_fill_ratio * 0.9):
                    raise ValueError
                if not is_boxlike(bw_node_cleaned):
                    raise ValueError
            except (IndexError, ValueError):
                max_thresh -= 0.05 * spread
                if max_thresh < hmin:
                    raise ValueError("Unable to locate the BB")
            else:
                found = True

        # determine the center of mass of the BB
        inv_img = Image.load(self.array)
        inv_img.invert()
        x_arr = np.abs(np.average(bw_node_cleaned, weights=inv_img, axis=0))
        x_com = SingleProfile(x_arr).fwxm_center(interpolate=True)
        y_arr = np.abs(np.average(bw_node_cleaned, weights=inv_img, axis=1))
        y_com = SingleProfile(y_arr).fwxm_center(interpolate=True)
        return Point(x_com, y_com)

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def __init__(self, filepath=None):
     """
     Parameters
     ----------
     filepath : None, str
         If None, image must be loaded later.
         If a str, path to the image file.
     """
     if filepath is not None and is_valid_file(filepath):
         self.image = Image.load(filepath)
     else:
         self.image = np.zeros((1,1))

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
    def load_image(self, file_path, filter=None):
        """Load the image

        Parameters
        ----------
        file_path : str
            Path to the image file.
        filter : int, None
            If None (default), no filtering will be done to the image.
            If an int, will perform median filtering over image of size *filter*.
        """
        self.image = Image.load(file_path)
        if isinstance(filter, int):
            self.image.median_filter(size=filter)
        self._check_for_noise()
        self.image.check_inversion()

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
    def load_image(self, file_path, im_type=None):
        """Load the image directly by the file path.

        Parameters
        ----------
        file_path : str, file-like object
            The path to the DICOM image or I/O stream.
        im_type : {'open', 'mlcs', None}
            Specifies what image type is being loaded in. If None, will try to determine the type from the name.
            The name must have 'open' or 'dmlc' in the name.
        """
        img = Image.load(file_path)
        if im_type is not None:
            if _is_open_type(im_type):
                self.image_open = img
            elif _is_dmlc_type(im_type):
                self.image_dmlc = img
        else:
            # try to guess type by the name
            imtype = self._try_to_guess_image_type(osp.basename(file_path))
            if imtype is not None:
                self.load_image(file_path, imtype)
            else:
                raise ValueError("Image type was not given nor could it be determined from the path name. Please enter and image type.")

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def load_demo_image(self):
     """Load the demo image."""
     demo_file = osp.join(osp.dirname(__file__), 'demo_files', 'flatsym', 'flatsym_demo.dcm')
     self.image = Image.load(demo_file)

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def setUpClass(cls):
     image = Image.load(cls.image_file_location)
     cls.profile = cls.klass(cls.center_point, cls.radius, image.array)

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def setUp(self):
     self.img = Image.load(tif_path)
     self.dcm = Image.load(dcm_path)
     array = np.arange(42).reshape(6, 7)
     self.arr = Image.load(array)

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def test_nonsense(self):
     with self.assertRaises(TypeError):
         Image.load('blahblah')

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def test_array(self):
     arr = np.arange(36).reshape(6, 6)
     img = Image.load(arr)
     self.assertIsInstance(img, ArrayImage)

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def test_file(self):
     img = Image.load(tif_path)
     self.assertIsInstance(img, FileImage)

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def test_dicom(self):
     img = Image.load(dcm_path)
     self.assertIsInstance(img, DicomImage)

# 需要導入模塊: from pylinac.core.image import Image [as 別名]
# 或者: from pylinac.core.image.Image import load [as 別名]
 def setUpClass(cls):
     cls.dcm = Image.load(dcm_path)