init commit

README.md

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+OpenCV 做图形监测

realtime_Detection.py

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+import cv2
+import numpy as np
+
+
+cap = cv2.VideoCapture(0)
+
+def nothing(x):
+    # any operation
+    pass
+
+'''
+HoughLinesP:
+threshold: The minimum number of intersections to "*detect*" a line
+minLineLength: The minimum number of points that can form a line. Lines with less than this number of points are disregarded.
+maxLineGap: The maximum gap between two points to be considered in the same line.
+'''
+
+cv2.namedWindow("Trackbars", cv2.WINDOW_AUTOSIZE)
+
+cv2.createTrackbar("threshold", "Trackbars", 0, 255, nothing)
+cv2.createTrackbar("minLineLength", "Trackbars", 0, 255, nothing)
+cv2.createTrackbar("maxLineGap", "Trackbars", 0, 255, nothing)
+
+
+'''
+Canny:
+threshold1	first threshold for the hysteresis procedure.
+threshold2	second threshold for the hysteresis procedure.
+apertureSize	aperture size for the Sobel operator.
+'''
+
+cv2.createTrackbar("threshold1", "Trackbars", 0, 255, nothing)
+cv2.createTrackbar("threshold2", "Trackbars", 0, 255, nothing)
+# cv2.createTrackbar("apertureSize", "Trackbars", 3, 7, nothing)
+
+
+
+cv2.namedWindow("CircleTrackbars", cv2.WINDOW_AUTOSIZE)
+
+'''
+Hough Circle Transform:
+Blur
+param_1 = 200: Upper threshold for the internal Canny edge detector.
+param_2 = 100*: Threshold for center detection.
+min_radius = 0: Minimum radius to be detected. If unknown, put zero as default.
+max_radius = 0: Maximum radius to be detected. If unknown, put zero as default.
+
+'''
+# cv2.createTrackbar("blur", "CircleTrackbars", 5, 16, nothing)
+cv2.createTrackbar("param_1", "CircleTrackbars", 260, 500, nothing)
+cv2.createTrackbar("param_2", "CircleTrackbars", 30, 255, nothing)
+cv2.createTrackbar("min_radius", "CircleTrackbars", 0, 255, nothing)
+cv2.createTrackbar("max_radius", "CircleTrackbars", 0, 255, nothing)
+
+font = cv2.FONT_HERSHEY_COMPLEX
+
+
+while True:
+
+    #HoughLinesP:
+    threshold = cv2.getTrackbarPos("threshold", "Trackbars")
+    minLineLength = cv2.getTrackbarPos("minLineLength", "Trackbars")
+    maxLineGap = cv2.getTrackbarPos("maxLineGap", "Trackbars")
+
+    #Canny:
+    threshold1 = cv2.getTrackbarPos("threshold1", "Trackbars")
+    threshold2 = cv2.getTrackbarPos("threshold2", "Trackbars")
+    # apertureSize = cv2.getTrackbarPos("apertureSize", "Trackbars")
+
+
+    #Hough Circle Transform:
+    # blur = cv2.getTrackbarPos("blur", "CircleTrackbars")
+    param_1 = cv2.getTrackbarPos("param_1", "CircleTrackbars")
+    param_2 = cv2.getTrackbarPos("param_2", "CircleTrackbars")
+    min_radius = cv2.getTrackbarPos("min_radius", "CircleTrackbars")
+    max_radius = cv2.getTrackbarPos("max_radius", "CircleTrackbars")
+
+    _, frame = cap.read()
+    src = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    # dst = cv2.Canny(src, 50, 200, None, 3)
+    # dst = cv2.Canny(src, threshold1, threshold2, None, apertureSize)
+
+    dst = cv2.Canny(src, threshold1, threshold2, None, 3)
+    
+    cdstP = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR)
+
+    # linesP = cv2.HoughLinesP(dst, 1, np.pi / 180, 50, None, 50, 10)
+    linesP = cv2.HoughLinesP(dst, 1, np.pi / 180, threshold, None, minLineLength, maxLineGap)
+    
+    if linesP is not None:
+        for i in range(0, len(linesP)):
+            l = linesP[i][0]
+            cv2.line(cdstP, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3, cv2.LINE_AA)
+
+            #draw circles
+            cv2.circle(cdstP, (l[0], l[1]), 10, (0,255,0), -1)
+            cv2.circle(cdstP, (l[2], l[3]), 10, (0,255,0), -1)
+
+    
+    gray = cv2.medianBlur(src, 5)
+    # gray = cv2.medianBlur(src, 9)
+    rows = gray.shape[0]
+
+    # cv2.imshow("gray Blur", gray)
+
+    # circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, rows / 8,
+    #                            param1=260, param2=30,
+    #                            minRadius=10, maxRadius=150)
+
+
+    circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, rows / 8,
+                               param1=param_1, param2=param_2,
+                               minRadius=min_radius, maxRadius=max_radius)
+
+    if circles is not None:
+        circles = np.uint16(np.around(circles))
+        for i in circles[0, :]:
+            center = (i[0], i[1])
+            # circle center
+            # cv2.circle(src, center, 1, (0, 100, 100), 3)
+            cv2.circle(src, center, 1, (60, 100, 100), 3)
+            # circle outline
+            radius = i[2]
+            #cv2.circle(src, center, radius, (255, 0, 255), 3)
+            cv2.circle(src, center, radius, (190, 90, 190), 3)
+
+
+    cv2.imshow("Source", src)
+    cv2.imshow("Detected Lines (in red) - Probabilistic Line Transform", cdstP)
+    
+
+    key = cv2.waitKey(1)
+    if key == 27:
+        break
+
+cap.release()
+cv2.destroyAllWindows()