You've already forked DataMate
118 lines
3.8 KiB
Python
118 lines
3.8 KiB
Python
# -- encoding: utf-8 --
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"""
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Description: 医疗图片按坐标切片
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Create: 2025/02/08 11:00
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"""
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import copy
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import time
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import os
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from typing import List, Dict, Any
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import xml.etree.ElementTree as ET
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from loguru import logger
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import numpy as np
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import cv2
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from openslide import OpenSlide
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from datamate.core.base_op import Slicer
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from datamate.common.utils import bytes_transform
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class AnnotationSlicer(Slicer):
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def __init__(self, *args, **kwargs):
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super(AnnotationSlicer, self).__init__(*args, **kwargs)
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self.last_ops = True
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def execute(self, sample: Dict[str, Any]) -> List[Dict[str, Any]]:
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start = time.time()
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slide: OpenSlide = OpenSlide(sample[self.filepath_key])
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if not isinstance(slide, OpenSlide):
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logger.error("Not desired <Image.Image> object.")
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annotation_path: str = sample["extraFilePath"]
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annotations = self.parse_xml_annotations(annotation_path)
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patch_num = self.auto_coordinate_slicer(sample, slide, annotations)
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sample["slice_num"] = patch_num
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file_name = sample[self.filename_key]
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logger.info(f"fileName: {file_name}, method: CoordinateSlider costs {(time.time() - start):6f} s")
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return [sample]
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def parse_xml_annotations(self, xml_path: str) -> List:
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""" 解析 XML 文件，提取所有 Annotation 的坐标和 PartOfGroup """
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tree = ET.parse(xml_path)
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root = tree.getroot()
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annotations = []
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# 找到所有 <Annotations> 标签
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annotations_tag = root.find('Annotations')
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if annotations_tag is None:
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raise ValueError("未找到 Annotations 标签")
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# 遍历所有 <Annotation> 标签
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for annotation in annotations_tag.findall('Annotation'):
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part_of_group = annotation.get('PartOfGroup')
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coordinates = []
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for coord in annotation.find('Coordinates').findall('Coordinate'):
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x = float(coord.get('X'))
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y = float(coord.get('Y'))
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coordinates.append((x, y))
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annotations.append({
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'part_of_group': part_of_group,
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'coordinates': np.array(coordinates, dtype=np.int32)
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})
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return annotations
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def auto_coordinate_slicer(
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self,
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original_sample: Dict,
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slide: OpenSlide,
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annotations: List
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) -> int:
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"""
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自动根据给定的标注文件切片原图像
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Return:
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List[Content] 每个 content 都是一个 data 为 patch 的 content
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"""
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wsi_width, wsi_height = slide.dimensions
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patch_no = 0
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# 遍历每个 Annotation
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for _, annotation in enumerate(annotations):
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part_of_group = annotation['part_of_group']
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coordinates = annotation['coordinates']
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# 转换坐标为整数（确保在图像范围内）
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coordinates = coordinates.clip(min=0, max=(wsi_width, wsi_height))
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# 创建掩码（mask）图像
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mask = np.zeros((wsi_height, wsi_width), dtype=np.uint8)
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cv2.fillPoly(mask, [coordinates], 255) # 填充多边形区域为白色
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# 找到掩码中的非零区域（肿瘤区域）
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x, y, w, h = cv2.boundingRect(coordinates) # 获取多边形的边界框
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# 读取 WSI 图像的切片区域
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region = slide.read_region((x, y), 0, (w, h))
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# 转换为 NumPy 数组
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region_np = np.array(region.convert("RGB"))
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patch_sample = copy.deepcopy(original_sample)
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patch_sample[self.data_key] = bytes_transform.numpy_to_bytes(region_np, '.png')
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patch_no += 1
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self.save_patch_sample(patch_sample, patch_no, save_format="image")
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logger.info(f">>> {patch_no} annotations found and sliced.")
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return patch_no
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