diff --git a/tasks/tasks/torpedoes/cv_solution/python_code/ellipse.py b/tasks/tasks/torpedoes/cv_solution/python_code/ellipse.py
new file mode 100644
index 0000000..b9c7b49
--- /dev/null
+++ b/tasks/tasks/torpedoes/cv_solution/python_code/ellipse.py
@@ -0,0 +1,79 @@
+import cv2
+import numpy as np
+import math
+
+MIN_AREA = 2000  # in order to ignore too small areas
+PI = 3.14159265358979323846
+MAX_TOL = 5  # depends on proximity, ca. 5 if ellipses are close
+THRESH = 134  # depends on light intensity: no water -> 120, simulation -> 134
+MIN_RATIO = 1.5
+MAX_RATIO = 2.5
+ELLIPSE_COLOUR = (0, 0, 255)
+
+
+class EllipseDetector:
+
+    @staticmethod
+    def img_area(image):
+        img_info = image.shape
+        x_img = img_info[0]
+        y_img = img_info[1]
+        max_area = x_img * y_img
+        return max_area
+
+    @staticmethod
+    def prepare_img(image):
+        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+        blur = cv2.GaussianBlur(gray, (5, 5), 0)
+        ret, thresh = cv2.threshold(blur, THRESH, 255, 0)
+        return thresh
+
+    def get_oval_holes_coordinates(self, image):
+        thresh = self.prepare_img(image)
+        im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+        ellipse_coords = []
+        for cnt in contours:
+            actual_area = abs(cv2.contourArea(cnt))
+            if actual_area < MIN_AREA:
+                continue
+
+            rect = cv2.minAreaRect(cnt)
+            box = cv2.boxPoints(rect)
+            box = np.int0(box)
+
+            x0 = box[0, 0]
+            y0 = box[0, 1]
+
+            x1 = box[1, 0]
+            y1 = box[1, 1]
+
+            x2 = box[2, 0]
+            y2 = box[2, 1]
+
+            x = x2 - x1
+            y = y0 - y1
+
+            ratio = 1
+            circle_radius = math.sqrt(x ** 2 / 4 + y ** 2 / 4)
+            circle_area = PI * circle_radius ** 2
+            ellipse_area = PI * x * y / 4
+            if x > 0 and y > 0:
+                if x > y:
+                    ratio = x/y  # ideally 1.6
+                else:
+                    ratio = y/x
+
+            if ellipse_area:
+                if (circle_area / ellipse_area < MAX_TOL) and (circle_area / self.img_area(image) < MAX_TOL / 100):
+                    if (ratio > MIN_RATIO) and (ratio < MAX_RATIO):
+                        # if np.any(img[x0, y0] == 0):
+                        ellipse = cv2.fitEllipse(cnt)
+                        cv2.ellipse(image, ellipse, ELLIPSE_COLOUR, 2)
+                        # print(x*y)
+                        # print(("x{} y{}").format(x, y))
+                        ellipse_coords.append(dict({"x": ((x0-x1)/2+x1), "y": (y1-y2)/2+y2}))
+        # cv2.imshow("Key points", image)
+        return ellipse_coords
+
+
+