get targets per shape

+import pandas as pd
+import os
+import csv
+
+file_path = "../../data/MICCAI_BraTS_2019_Data_Training/train_frame_m1"
+csv_name = "../../data/MICCAI_BraTS_2019_Data_Training/train_targets.csv"
+
+f=open(csv_name, 'w', newline='')
+w=csv.writer(f)
+count = 0
+st = 'BraTS19_2013_10_1' #BraTS19_2013_10_1
+for path, dirs, files in os.walk(file_path):
+    for filename in files:
+        print(filename)
+        if(filename.split('_seg_flair')[0] != st):
+            st = filename.split('_seg_flair')[0]
+            count = count + 1
+        w.writerow([filename, count])
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+import cv2
+import os
+import numpy as np
+import shutil 
+import time
+
+font = cv2.FONT_HERSHEY_COMPLEX
+
+load_path = "./total_frame_m1"
+#load_path = "./sample"
+color = (255,255,255)
+
+for path, dirs, files in os.walk(load_path):
+    for filename in files:
+        img = cv2.imread(os.path.join(path, filename), cv2.IMREAD_GRAYSCALE)
+        # (img, threshold_value, value, flag): if pixel val >= threshold_value: pixel_val = value
+        _, threshold = cv2.threshold(img, 1, 255, cv2.THRESH_BINARY)
+        contours, _ = cv2.findContours(threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+        n_ellipse, n_circle = 0, 0
+        if (len(contours) > 0):
+            area = cv2.contourArea(contours[0])
+        largest = ""
+
+        for cnt in contours:
+            approx = cv2.approxPolyDP(cnt, 0.01*cv2.arcLength(cnt, True), True)
+            cv2.drawContours(img, [approx], 0, (0), 5)
+            x = approx.ravel()[0]
+            y = approx.ravel()[1]
+
+            #print("approx", len(approx))
+            if len(approx) < 12:
+                #cv2.putText(img, "Ellipse", (x, y), font, 1, color)
+                n_ellipse = n_ellipse + 1
+                if (area < cv2.contourArea(cnt)):
+                    area = cv2.contourArea(cnt)
+                    largest = "e"
+            else:
+                #cv2.putText(img, "Circle", (x, y), font, 1, color)
+                n_circle = n_circle + 1
+                if (area < cv2.contourArea(cnt)):
+                    area = cv2.contourArea(cnt)
+                    largest = "c"
+
+        print(n_ellipse, n_circle, filename)
+        #assert n_ellipse !=0 or n_circle !=0
+        
+        if (n_ellipse > n_circle) or (n_ellipse==n_circle and largest == "e"):
+            ellipase_path = os.path.join("./ellipse/", filename)
+            shutil.copy(os.path.join(path, filename), ellipase_path)
+
+        elif (n_ellipse < n_circle) or (n_ellipse==n_circle and largest == "c"):
+            circle_path = os.path.join("./circle/", filename)
+            shutil.copy(os.path.join(path, filename), circle_path)
+
+        elif n_circle == 0 and n_ellipse == 0:
+            shutil.copy(os.path.join(path, filename), os.path.join("./zero/", filename))
+        
+
+# cv2.imshow("shapes", img)
+# cv2.imshow("Threshold", threshold)
+# cv2.waitKey(0)
+# cv2.destroyAllWindows()
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+import cv2
+import numpy as np
+
+font = cv2.FONT_HERSHEY_COMPLEX
+
+#file_path = "../../data/MICCAI_BraTS_2019_Data_Training/train_frame_m1"
+
+# for path, dirs, files in os.walk(file_path):
+#     for filename in files:
+
+img = cv2.imread("BraTS19_2013_2_1_seg_flair_8.png", cv2.IMREAD_GRAYSCALE)
+ # (img, threshold_value, value, flag): if pixel val >= threshold_value: pixel_val = value
+_, threshold = cv2.threshold(img, 1, 255, cv2.THRESH_BINARY)
+contours, _ = cv2.findContours(threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+color = (255,255,255)
+n_ellipse, n_circle = 0, 0
+area = cv2.contourArea(contours[0])
+
+for cnt in contours:
+    approx = cv2.approxPolyDP(cnt, 0.01*cv2.arcLength(cnt, True), True)
+    cv2.drawContours(img, [approx], 0, (0), 5)
+    x = approx.ravel()[0]
+    y = approx.ravel()[1]
+    
+    print(area)
+    if (area < cv2.contourArea(cnt)):
+            area = cv2.contourArea(cnt)
+
+    # ss = ""
+    
+    # if len(approx) == 3:
+    #     cv2.putText(img, "Triangle", (x, y), font, 1, color)
+    # elif len(approx) == 4:
+    #     cv2.putText(img, "Rectangle", (x, y), font, 1, color)
+    # elif len(approx) == 5:
+    #     cv2.putText(img, "Pentagon", (x, y), font, 1, color)
+    if len(approx) < 12:
+        cv2.putText(img, "Ellipse", (x, y), font, 1, color)
+        n_ellipse = n_ellipse + 1
+        # if (area < cv2.contourArea(cnt)):
+        #     area = cv2.contourArea(cnt)
+        #     ss = "ellipse"
+    else:
+        cv2.putText(img, "Circle", (x, y), font, 1, color)
+        n_circle = n_circle + 1
+        # if (area < cv2.contourArea(cnt)):
+        #     area = cv2.contourArea(cnt)
+        #     ss = "circle"
+
+print(n_ellipse, n_circle)
+#print(ss)
+
+cv2.imshow("shapes", img)
+cv2.imshow("Threshold", threshold)
+cv2.waitKey(0)
+cv2.destroyAllWindows()
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