upload train code

CTAI_model/cv/get_ROI-one.py

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+import SimpleITK as sitk
+import cv2
+import numpy as np
+
+image = sitk.ReadImage('../data/train/train/10087.dcm')
+image = sitk.GetArrayFromImage(image)[0, :, :]
+
+image[image < -300] = 0
+image[image > 300] = 0
+
+ROI = np.zeros(image.shape, np.uint8)
+# 获取图像中的像素数据
+slices = [image]
+
+# 复制Dicom图像中的像素数据
+img = slices[int(len(slices) / 2)].copy()
+img = np.uint8(img)
+
+kernel = np.ones((4, 4), np.uint8)
+img = cv2.dilate(img, kernel, iterations=1)
+
+# 对图像进行阈值分割
+ret, img = cv2.threshold(img, 150, 255, cv2.THRESH_BINARY_INV)
+
+xxx = img
+# 提取分割结果中的轮廓，并填充孔洞
+im2, contours, x = cv2.findContours(img.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
+# 需要反色处理一下  现在找的是白色的  应该是黑色的
+
+# mask = np.zeros(img.shape, np.uint8)
+# for contour in contours:
+#     cv2.fillPoly(mask, [contour], 255)
+# img[(mask > 0)] = 255
+
+
+area = []
+for c in contours:
+    area.append(cv2.contourArea(c))
+cparea = area.copy()
+
+area.sort(reverse=True)
+
+for i in range(3, 8):
+    max_idx = cparea.index(area[i])
+    perimeter = cv2.arcLength(contours[max_idx], True)
+    if area[i] > 5000 or perimeter > 500:
+        continue
+    print('周长', perimeter)
+
+    cv2.drawContours(ROI, contours, max_idx, (220, 20, 60), -1)
+
+# max_idx = cparea.index(area[3])
+# cv2.drawContours(ROI, contours, max_idx, (220, 20, 60), -1)
+# cv2.drawContours(ROI, contours, max_idx, (220, 20, 60), -1)
+
+
+# 对分割结果进行形态学的开操作
+# kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2, 2))
+# img = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)
+
+# plt.figure(figsize=(10, 7))
+# plt.imshow(img, 'gray')
+# plt.title('Mask')
+# plt.show()
+
+
+cv2.imshow("Image", ROI)
+cv2.waitKey(0)