feat(image preprocessor): calculate offsetnd for each chunk

gnes/preprocessor/image/base.py

@@ -32,14 +32,14 @@ def __init__(self,
     def _get_all_chunks_weight(self, image_set: List['np.ndarray']) -> List[float]:
         pass
 
-    @classmethod
-    def _torch_transform(cls, image):
+    @staticmethod
+    def _torch_transform(image):
         import torchvision.transforms as transforms
         return transforms.Compose([transforms.ToTensor(),
                                    transforms.Normalize(mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5))])(image)
 
-    @classmethod
-    def _get_all_subarea(cls, image):
+    @staticmethod
+    def _get_all_subarea(image):
         from itertools import product
         x_list = [0, image.size[0] / 3, 2 * image.size[0] / 3, image.size[0]]
         y_list = [0, image.size[1] / 3, 2 * image.size[1] / 3, image.size[1]]

gnes/preprocessor/image/segmentation.py

@@ -91,8 +91,8 @@ def _get_seg_offset_nd(self, all_subareas: List[List[int]], index: List[List[int
         iou_list = [self._cal_iou(area, chunk) for area in all_subareas]
         return index[int(np.argmax(iou_list))][:2]
 
-    @classmethod
-    def _cal_area(cls, coordinate: List[int]):
+    @staticmethod
+    def _cal_area(coordinate: List[int]):
         return (coordinate[2] - coordinate[0]) * (coordinate[3] - coordinate[1])
 
     def _cal_iou(self, image: List[int], chunk: List[int]) -> float:
@@ -105,7 +105,5 @@ def _cal_iou(self, image: List[int], chunk: List[int]) -> float:
         y2 = min(chunk[3], image[3])
 
         overlap_area = max(0, x2 - x1) * max(0, y2 - y1)
-
         iou = overlap_area / (chunk_area + image_area - overlap_area)
-
         return iou

gnes/preprocessor/image/sliding_window.py

@@ -97,8 +97,8 @@ def _get_slid_offset_nd(self, all_subareas: List[List[int]], index: List[List[in
         location = [i for i in range(len(location_list)) if location_list[i] is True][0]
         return index[location][:2]
 
-    @classmethod
-    def _get_location(cls, all_subareas: List[List[int]], center_point: List[float]) -> List[bool]:
+    @staticmethod
+    def _get_location(all_subareas: List[List[int]], center_point: List[float]) -> List[bool]:
         location_list = []
         x_boundary = max([x[1] for x in all_subareas])
         y_boundary = max([y[3] for y in all_subareas])