init datamate

runtime/ops/slicer/slide_simple_slicer/process.py

@@ -0,0 +1,98 @@
+# -- encoding: utf-8 --
+
+"""
+Description: 医疗图片按坐标切片
+Create: 2025/02/08 11:00
+"""
+import copy
+import time
+from typing import List, Tuple, Dict, Any
+
+import itertools
+from loguru import logger
+
+from openslide import OpenSlide
+import numpy as np
+
+from datamate.core.base_op import Slicer
+
+from datamate.common.utils import bytes_transform
+
+
+class SimpleSlicer(Slicer):
+
+    def __init__(self, *args, **kwargs):
+        super(SimpleSlicer, self).__init__(*args, **kwargs)
+
+        self._target_size = kwargs.get("sliceSize", [128, 128])
+        self._overlap = kwargs.get("overlap", 0)
+        self.last_ops = True
+
+        if not isinstance(self._target_size, List):
+            raise TypeError(f"<targetSize> received as {type(self._target_size)}, but expected list.")
+        if len(self._target_size) != 2:
+            raise ValueError(f"<targetSize> has {len(self._target_size)} elements, but expected 2.")
+        if not all(isinstance(dim, int) for dim in self._target_size):
+            raise TypeError(f"Elements in <targetSize> must be integers, but got {self._target_size}.")
+        if not isinstance(self._overlap, (int, float)):
+            raise TypeError(f"<overlap> received as {type(self._overlap)}, but expected int.")
+        if self._overlap < 0 or self._overlap > 1:
+            raise ValueError(
+                f"<overlap> received an out of range value: {self._overlap}, "
+                f"but (0 <= overlap <= 1) is expected."
+            )
+
+    def execute(self, sample: Dict[str, Any]) -> List[Dict]:
+        start = time.time()
+
+        slide: OpenSlide = OpenSlide(sample["filePath"])
+        if not isinstance(slide, OpenSlide):
+            logger.error("Not desired <Image.Image> object.")
+        dimensions: tuple[int, int] = slide.dimensions
+
+        target_size = self._target_size
+        overlap = self._overlap
+
+        patch_num = self.auto_simple_slicer(sample, slide, dimensions, target_size, overlap)
+        sample["slice_num"] = patch_num
+
+        file_name = sample[self.filename_key]
+        logger.info(f"fileName: {file_name}, method: CoordinateSlider costs {(time.time() - start):6f} s")
+
+        return [sample]
+
+    def auto_simple_slicer(
+            self,
+            original_sample: Dict[str, Any],
+            slide: OpenSlide,
+            dimensions: Tuple[int, int],
+            target_size: Tuple[int, int],
+            overlap: float
+    ) -> int:
+        """
+        自动根据给定规格切片原图像
+
+        Return: 
+            List[Content] 每个 content 都是一个 data 为 patch 的 content
+        """
+        stride_x, stride_y = map(lambda x: int(x * (1 - overlap)), target_size)
+        w, h = target_size
+
+        patch_no = 0
+        for x, y in itertools.product(
+                range(0, dimensions[0] - w + 1, stride_x),
+                range(0, dimensions[1] - h + 1, stride_y)
+        ):
+            # 切片
+            region = slide.read_region((x, y), 0, target_size)
+
+            region_np = np.array(region.convert("RGB"))
+
+            patch_sample = copy.deepcopy(original_sample)
+            patch_sample[self.data_key] = bytes_transform.numpy_to_bytes(region_np, ".png")
+            patch_no += 1
+            self.save_patch_sample(patch_sample, patch_no, save_format="image")
+
+        logger.info(f"One image sliced into pieces: {patch_no}")
+
+        return patch_no