update,

2025-01-31 22:56:58 +08:00
parent 57c7fd9332
commit b1cd1d4662
26 changed files with 6436 additions and 0 deletions
--- a/vinniesniper-54816/task1/_lab/001-test-integration/countour_util.py
+++ b/vinniesniper-54816/task1/_lab/001-test-integration/countour_util.py
@@ -0,0 +1,192 @@
+import cv2 as cv
+import math
+import numpy as np
+import os, sys
+
+img_cache = {}
+hist_rgb_cache = {}
+
+
+def readImage(img_path):
+    global img_cache
+
+    if img_path in img_cache.keys():
+        pass
+
+    else:
+        # read image
+        img_test_rgb = cv.imread(img_path)
+        # convert to gray scale
+        img_test_rgb = cv.resize(img_test_rgb, (1024, 1024))
+        img_cache[img_path] = img_test_rgb
+
+    return img_cache[img_path]
+
+
+def getCountourDiff():
+    pass
+
+
+def checkCountourImg1(img1):
+    try:
+        kernel = cv.getStructuringElement(cv.MORPH_RECT, (6, 6))
+
+        # calculation for the area of a circle in img1
+        heightCenter1 = img1.shape[0] / 2
+        widthCenter1 = img1.shape[1] / 2
+        heightCircle1 = img1.shape[0] / 2.3
+        widthCircle1 = img1.shape[1] / 2.7
+
+        center1 = (round(widthCenter1), round(heightCenter1))
+        axesLength1 = (round(widthCircle1), round(heightCircle1))
+        circleArea1 = round(math.pi * widthCircle1 * heightCircle1)
+
+        # calculation for contours and total area of img1
+        L, U, V = cv.split(cv.cvtColor(img1, cv.COLOR_BGR2LUV))
+
+        channel1 = cv.merge([U, U, U])
+        channel1 = cv.cvtColor(channel1, cv.COLOR_BGR2GRAY)
+        closed1 = cv.morphologyEx(channel1, cv.MORPH_CLOSE, kernel)
+        closed1 = cv.medianBlur(closed1, 3)
+        retval, threshold1 = cv.threshold(closed1, 100, 255, cv.THRESH_BINARY)
+
+        contours1, hierarchy1 = cv.findContours(threshold1, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)
+
+        # cv.drawContours(img1, contours1, -1, (0, 255, 0), 2)
+        # cv.imshow("Contours Image 1", img1)
+        # cv.waitKey(0)
+        # cv.destroyAllWindows()
+        # sys.exit()
+
+        return (contours1, circleArea1)
+    except Exception as e:
+        print(e)
+
+
+def checkCountourImg2(img2):
+    kernel = cv.getStructuringElement(cv.MORPH_RECT, (6, 6))
+
+    try:
+        # calculation for the area of a circle in img2
+        img2copy = img2.copy()
+
+        height, width, _ = img2.shape
+        heightCenter2, widthCenter2 = height / 2, width / 2
+        heightCircle2, widthCircle2 = height / 2.3, width / 2.5
+
+        center2 = (round(widthCenter2), round(heightCenter2))
+        axesLength2 = (round(widthCircle2), round(heightCircle2))
+        circleArea2 = round(math.pi * widthCircle2 * heightCircle2)
+
+        img2circle = cv.ellipse(img2copy, center2, axesLength2, 0, 0, 360, (0, 0, 255), 2)
+
+        # calculation for contours and total area of img2
+        L, U, V = cv.split(cv.cvtColor(img2circle, cv.COLOR_BGR2LUV))
+        channel2 = cv.merge([U, U, U])
+        channel2 = cv.cvtColor(channel2, cv.COLOR_BGR2GRAY)
+        closed2 = cv.morphologyEx(channel2, cv.MORPH_CLOSE, kernel)
+        closed2 = cv.medianBlur(closed2, 3)
+        retval, threshold2 = cv.threshold(closed2, 110, 255, cv.THRESH_BINARY)
+
+        contours2, hierarchy2 = cv.findContours(threshold2, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)
+
+        return (contours2, circleArea2)
+    except Exception as e:
+        print(e)
+
+
+def getCountour(img1, img2):
+    try:
+        kernel = cv.getStructuringElement(cv.MORPH_RECT, (6, 6))
+        totalArea1 = 0
+        totalArea2 = 0
+
+        # calculation for the area of a circle in img1
+        heightCenter1 = img1.shape[0] / 2
+        widthCenter1 = img1.shape[1] / 2
+        heightCircle1 = img1.shape[0] / 2.3
+        widthCircle1 = img1.shape[1] / 2.7
+
+        center1 = (round(widthCenter1), round(heightCenter1))
+        axesLength1 = (round(widthCircle1), round(heightCircle1))
+        circleArea1 = round(math.pi * widthCircle1 * heightCircle1)
+
+        # calculation for contours and total area of img1
+        L, U, V = cv.split(cv.cvtColor(img1, cv.COLOR_BGR2LUV))
+        channel1 = cv.merge([U, U, U])
+        channel1 = cv.cvtColor(channel1, cv.COLOR_BGR2GRAY)
+        closed1 = cv.morphologyEx(channel1, cv.MORPH_CLOSE, kernel)
+        closed1 = cv.medianBlur(closed1, 3)
+        retval, threshold1 = cv.threshold(closed1, 110, 255, cv.THRESH_BINARY)
+
+        contours1, hierarchy1 = cv.findContours(threshold1, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)
+
+        for contour in contours1:
+            totalArea1 += cv.contourArea(contour)
+
+        # calculation for the area of a circle in img2
+        img2copy = img2.copy()
+
+        heightCenter2 = img2copy.shape[0] / 2
+        widthCenter2 = img2copy.shape[1] / 2
+        heightCircle2 = img2copy.shape[0] / 2.3
+        widthCircle2 = img2copy.shape[1] / 2.5
+
+        center2 = (round(widthCenter2), round(heightCenter2))
+        axesLength2 = (round(widthCircle2), round(heightCircle2))
+        circleArea2 = round(math.pi * widthCircle2 * heightCircle2)
+
+        img2circle = cv.ellipse(img2copy, center2, axesLength2, 0, 0, 360, (0, 0, 255), 2)
+
+        # calculation for contours and total area of img2
+        L, U, V = cv.split(cv.cvtColor(img2circle, cv.COLOR_BGR2LUV))
+        channel2 = cv.merge([U, U, U])
+        channel2 = cv.cvtColor(channel2, cv.COLOR_BGR2GRAY)
+        closed2 = cv.morphologyEx(channel2, cv.MORPH_CLOSE, kernel)
+        closed2 = cv.medianBlur(closed2, 3)
+        retval, threshold2 = cv.threshold(closed2, 110, 255, cv.THRESH_BINARY)
+
+        contours2, hierarchy2 = cv.findContours(threshold2, cv.RETR_LIST, cv.CHAIN_APPROX_NONE)
+
+        for contour in contours2:
+            totalArea2 += cv.contourArea(contour)
+
+        # calculation of contour area over circle area
+        print(totalArea1, circleArea1, totalArea2, circleArea2)
+        sys.exit()
+
+        circleRatio1 = totalArea1 / circleArea1
+        circleRatio2 = totalArea2 / circleArea2
+        difference = circleRatio2 / circleRatio1
+
+        return difference
+
+    except Exception as e:
+        print(e)
+
+
+def getContourDiff(img1_path, img2_path):
+    totalArea1 = 0
+    totalArea2 = 0
+
+    img1 = readImage(img1_path)
+    img2 = readImage(img2_path)
+
+    try:
+        (contours1, circleArea1) = checkCountourImg1(img1)
+        for contour in contours1:
+            totalArea1 += cv.contourArea(contour)
+
+        (contours2, circleArea2) = checkCountourImg2(img2)
+        for contour in contours2:
+            totalArea2 += cv.contourArea(contour)
+
+        # calculation of contour area over circle area
+        circleRatio1 = totalArea1 / circleArea1
+        circleRatio2 = totalArea2 / circleArea2
+        difference = circleRatio2 / circleRatio1
+
+        return difference
+
+    except Exception as e:
+        print(e)