adding trackers that might work
parent
bbc3fefdfc
commit
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# importing libraries
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import cv2
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import numpy as np
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from scipy import stats
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drawing = False
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point1 = ()
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point2 = ()
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def mouse_drawing(event, x, y, flags, params):
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global point1, point2, drawing
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if event == cv2.EVENT_LBUTTONDOWN:
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if drawing is False:
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drawing = True
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point1 = (x, y)
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else:
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drawing = False
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elif event == cv2.EVENT_MOUSEMOVE:
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if drawing is True:
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point2 = (x, y)
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# Our ROI, defined by two points
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p1, p2 = None, None
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state = 0
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# Called every time a mouse event happen
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def on_mouse(event, x, y, flags, userdata):
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global state, point1, point2
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# Left click
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if event == cv2.EVENT_LBUTTONUP:
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# Select first point
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if state == 0:
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point1 = (x,y)
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state += 1
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# Select second point
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elif state == 1:
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point2 = (x,y)
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state += 1
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#xFine = (848, 187, 225, 21.0)
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#yFine = (604, 402, 20.5, 276)
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xFine = (848, 187, 848 + 225, 187 + 21.0)
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yFine = (604, 402, 604 + 20.5, 402 + 276)
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frameCountMod = 0
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centroidX = [0, 0]
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centroidY = [0, 0]
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def track(frame, ROI, centroid, update):
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if(update):
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crop = frame[int(ROI[1]):int(ROI[3]), int(ROI[0]):int(ROI[2])]
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crop = cv2.cvtColor(crop, cv2.COLOR_RGB2GRAY)
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crop = cv2.GaussianBlur(crop,(7,7),cv2.BORDER_DEFAULT)
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#ret, thresh = cv2.threshold(crop, 100, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY)
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ret,thresh = cv2.threshold(crop, 50, 255, 0)
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M = cv2.moments(thresh)
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# calculate x,y coordinate of center
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if M["m00"] != 0:
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centroid[0] = int(M["m10"] / M["m00"])
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centroid[1] = int(M["m01"] / M["m00"])
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#else:
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# cX, cY = 0, 0
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#print(cY)
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cv2.circle(frame, (int(ROI[0]) + centroid[0], int(ROI[1]) + centroid[1]), 3, (0, 255, 0), -1)
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cv2.namedWindow("Frame")
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cv2.setMouseCallback("Frame", mouse_drawing)
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cv2.namedWindow("Process")
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# Create a VideoCapture object and read from input file
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cap = cv2.VideoCapture("/home/mwinter/Portfolio/a_history_of_the_domino_problem/a_history_of_the_domino_problem_source/recs/a_history_of_the_domino_problem_final_documentation_hq.mp4")
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cap.set(cv2.CAP_PROP_POS_FRAMES, 10000)
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# Check if camera opened successfully
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if (cap.isOpened()== False):
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print("Error opening video file")
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frameCountMod = 0
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centroidX = [0, 0]
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centroidY = [0, 0]
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# Read until video is completed
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while(cap.isOpened()):
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# Capture frame-by-frame
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ret, frame = cap.read()
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if ret == True:
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# Display the resulting frame
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if point1 and point2:
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px = sorted([point1[0], point2[0]])
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py = sorted([point1[1], point2[1]])
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#cv2.rectangle(frame, point1, point2, (0, 255, 0))
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xFine = (px[0], py[0], px[1], py[1])
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crop = frame[int(xFine[1]):int(xFine[3]), int(xFine[0]):int(xFine[2])]
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gray = cv2.cvtColor(crop, cv2.COLOR_BGR2GRAY)
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fm = cv2.Laplacian(gray, cv2.CV_64F).var()
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kernel = np.ones((30, 50), np.uint8)
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text = "Not Blurry"
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blur = cv2.GaussianBlur(cv2.bitwise_not(crop),(1001,3), 3, 1) * 3
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dilation = cv2.dilate(gray, kernel, iterations=1)
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ret,dilation = cv2.threshold(dilation,20,255,cv2.THRESH_BINARY_INV)
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mean = pow(dilation.mean(), 3)
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# if the focus measure is less than the supplied threshold,
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# then the image should be considered "blurry"
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if fm < 100.0:
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text = "Blurry"
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# show the image
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cv2.rectangle(frame, (int(xFine[0]), int(xFine[1])), (int(xFine[2]),int(xFine[3])), (0, 255, 0))
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cv2.rectangle(frame, (int(xFine[0]), int(xFine[1])), (int(xFine[2]),int(xFine[3])), (0, 255, 0))
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cv2.putText(frame, "{}: {:.2f}".format(text, fm), (10, 30),
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cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
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cv2.putText(frame, "{}: {:.2f}".format("Brightness", mean), (10, 100),
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cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
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cv2.imshow("Frame", frame)
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cv2.imshow("Process", crop)
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# Press Q on keyboard to exit
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key = cv2.waitKey(100)
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if key == 32:
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cv2.waitKey()
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elif key == ord('q'):
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break
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# Break the loop
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else:
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break
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# When everything done, release
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# the video capture object
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cap.release()
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# Closes all the frames
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cv2.destroyAllWindows()
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@ -0,0 +1,148 @@
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# importing libraries
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import cv2
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import numpy as np
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from scipy import stats
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rectToSet = 'x'
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moving = False
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roiXCenter = (960, 195)
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roiYCenter = (615, 530)
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w = 10
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l1 = 50
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l2 = 150
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l3 = 20
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roiXInner = (roiXCenter[0] - l1, roiXCenter[1] - w, roiXCenter[0] + l1, roiXCenter[1] + w)
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roiXOuter = (roiXCenter[0] - l2, roiXCenter[1] - w, roiXCenter[0] + l2, roiXCenter[1] + w)
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roiXCourse = (roiXCenter[0] - l3, roiXCenter[1] + (w * 1), roiXCenter[0] + l3, roiXCenter[1] + (w * 3))
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roiYInner = (roiYCenter[0] - w, roiYCenter[1] - l1, roiYCenter[0] + w, roiYCenter[1] + l1)
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roiYOuter = (roiYCenter[0] - w, roiYCenter[1] - l2, roiYCenter[0] + w, roiYCenter[1] + l2)
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roiYCourse = (roiYCenter[0] + (w * 1), roiYCenter[1] - l3, roiYCenter[0] + (w * 3), roiYCenter[1] + l3)
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dilationVal = 75
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def moveROI(event, x, y, flags, params):
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global roiXCenter, roiYCenter, roiXInner, roiXOuter, roiXCourse, roiYInner, roiYOuter, roiYCourse, moving
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if event == cv2.EVENT_LBUTTONDOWN:
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moving = True
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elif event==cv2.EVENT_MOUSEMOVE:
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if moving==True:
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if rectToSet=='x':
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roiXCenter = (x, y)
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roiXInner = (roiXCenter[0] - l1, roiXCenter[1] - w, roiXCenter[0] + l1, roiXCenter[1] + w)
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roiXOuter = (roiXCenter[0] - l2, roiXCenter[1] - w, roiXCenter[0] + l2, roiXCenter[1] + w)
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roiXCourse = (roiXCenter[0] - l3, roiXCenter[1] + (w * 1), roiXCenter[0] + l3, roiXCenter[1] + (w * 3))
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elif rectToSet=='y':
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roiYCenter = (x, y)
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roiYInner = (roiYCenter[0] - w, roiYCenter[1] - l1, roiYCenter[0] + w, roiYCenter[1] + l1)
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roiYOuter = (roiYCenter[0] - w, roiYCenter[1] - l2, roiYCenter[0] + w, roiYCenter[1] + l2)
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roiYCourse = (roiYCenter[0] + (w * 1), roiYCenter[1] - l3, roiYCenter[0] + (w * 3), roiYCenter[1] + l3)
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elif event == cv2.EVENT_LBUTTONUP:
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moving = False
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cv2.namedWindow("Frame")
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cv2.setMouseCallback("Frame", moveROI)
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#cv2.namedWindow("Process")
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# Create a VideoCapture object and read from input file
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cap = cv2.VideoCapture("/home/mwinter/Portfolio/a_history_of_the_domino_problem/a_history_of_the_domino_problem_source/recs/a_history_of_the_domino_problem_final_documentation_hq.mp4")
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cap.set(cv2.CAP_PROP_POS_FRAMES, 10000)
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# Check if camera opened successfully
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if (cap.isOpened()== False):
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print("Error opening video file")
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def track(frame, roiInner, roiOuter, roiCourse):
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w = 30
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l1 = 30
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l2 = 100
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cropFine = frame[roiOuter[1]:roiOuter[3], roiOuter[0]:roiOuter[2]]
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cropCourse = frame[roiCourse[1]:roiCourse[3], roiCourse[0]:roiCourse[2]]
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#gray = cv2.cvtColor(crop, cv2.COLOR_BGR2GRAY)
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#may not need any of this
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kernel = np.ones((dilationVal, dilationVal), np.uint8)
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dilation = cv2.dilate(cropFine, kernel, iterations=1)
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ret,tresh = cv2.threshold(dilation,20,255,cv2.THRESH_BINARY)
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#mean = pow(frame[roiInner[1]:roiInner[3], roiInner[0]:roiInner[2]].mean(), 3)
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frame[roiOuter[1]:roiOuter[3], roiOuter[0]:roiOuter[2]] = tresh
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meanFine = pow(frame[roiInner[1]:roiInner[3], roiInner[0]:roiInner[2]].mean(), 2)
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meanCourse = frame[roiCourse[1]:roiCourse[3], roiCourse[0]:roiCourse[2]].mean()
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mean = 0
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if(meanCourse > 10):
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mean = meanFine
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distance = pow(255, 2) - mean
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return distance
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def drawRects(frame):
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cv2.rectangle(frame, (roiXOuter[0], roiXOuter[1]), (roiXOuter[2], roiXOuter[3]), (0, 255, 0))
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cv2.rectangle(frame, (roiXCenter[0] - l1, roiXInner[1]), (roiXCenter[0], roiXInner[3]), (0, 255, 0))
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cv2.rectangle(frame, (roiXCenter[0], roiXInner[1]), (roiXCenter[0] + l1, roiXInner[3]), (0, 255, 0))
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cv2.rectangle(frame, (roiXCourse[0], roiXCourse[1]), (roiXCourse[2], roiXCourse[3]), (0, 255, 0))
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cv2.rectangle(frame, (roiYOuter[0], roiYOuter[1]), (roiYOuter[2], roiYOuter[3]), (0, 255, 0))
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cv2.rectangle(frame, (roiYInner[0], roiYCenter[1] - l1), (roiYInner[2], roiYCenter[1]), (0, 255, 0))
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cv2.rectangle(frame, (roiYInner[0], roiYCenter[1]), (roiYInner[2], roiYCenter[1] + l1), (0, 255, 0))
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cv2.rectangle(frame, (roiYCourse[0], roiYCourse[1]), (roiYCourse[2], roiYCourse[3]), (0, 255, 0))
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# Read until video is completed
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while(cap.isOpened()):
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# Capture frame-by-frame
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ret, frame = cap.read()
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if ret == True:
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# Display the resulting frame
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distanceX = track(frame, roiXInner, roiXOuter, roiXCourse)
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distanceY = track(frame, roiYInner, roiYOuter, roiYCourse)
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drawRects(frame)
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cv2.putText(frame, "{}: {:.2f}".format("distance x", distanceX), (10, 100), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
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cv2.putText(frame, "{}: {:.2f}".format("distance y", distanceY), (10, 200), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
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#fm = cv2.Laplacian(gray, cv2.CV_64F).var()
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#cv2.putText(frame, "{}: {:.2f}".format("blur", fm), (10, 30),
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#cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 3)
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cv2.imshow("Frame", frame)
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#cv2.imshow("Process", tresh)
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# Press Q on keyboard to exit
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key = cv2.waitKey(1)
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if key == 32:
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cv2.waitKey()
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elif key == ord('+'):
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dilationVal = dilationVal + 1
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elif key == ord('-'):
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if dilationVal > 0:
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dilationVal = dilationVal - 1
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elif key == ord('x'):
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rectToSet = 'x'
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elif key == ord('y'):
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rectToSet = 'y'
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elif key == ord('q'):
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break
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# Break the loop
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else:
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break
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# When everything done, release
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# the video capture object
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cap.release()
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# Closes all the frames
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cv2.destroyAllWindows()
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