最终粗糙版
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38
MV.py
38
MV.py
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import cv2 as cv
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import numpy as np
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cap = cv.VideoCapture("./vid/zootopia.mkv")
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ret, frame1 = cap.read()
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prvs = cv.cvtColor(frame1, cv.COLOR_BGR2GRAY)
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hsv = np.zeros_like(frame1)
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hsv[..., 1] = 255
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print("jump ahead")
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cap.set(cv.CAP_PROP_POS_FRAMES, 4)
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print("jump done")
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while(1):
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for i in range(1, 12):
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cap.read()
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ret, frame2 = cap.read()
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next = cv.cvtColor(frame2, cv.COLOR_BGR2GRAY)
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flow = cv.calcOpticalFlowFarneback(
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prvs, next, None, 0.5, 3, 15, 3, 5, 1.2, 0)
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mag, ang = cv.cartToPolar(flow[..., 0], flow[..., 1])
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hsv[..., 0] = ang*180/np.pi/2
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hsv[..., 2] = cv.normalize(mag, None, 0, 255, cv.NORM_MINMAX)
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bgr = cv.cvtColor(hsv, cv.COLOR_HSV2BGR)
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cv.namedWindow("MotionVector", cv.WINDOW_NORMAL)
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cv.namedWindow("frame", cv.WINDOW_NORMAL)
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cv.imshow('MotionVector', bgr)
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cv.imshow("frame", frame2)
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cv.waitKey(1)
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#k = cv.waitKey(0.1) & 0xff
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# if k == 27:
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# break
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# elif k == ord('s'):
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# cv.imwrite('opticalfb.png',frame2)
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# cv.imwrite('opticalhsv.png',bgr)
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prvs = next
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cap.release()
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cv.destroyAllWindows()
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BIN
bridge.png
BIN
bridge.png
Binary file not shown.
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Before Width: | Height: | Size: 2.8 MiB |
130
picMV.py
130
picMV.py
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import cv2 as cv
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import numpy as np
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img = cv.imread("./pic/2.jpg")
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imgL = np.split(img, 2, 1)[0]
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imgR = np.split(img, 2, 1)[1]
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prvs = cv.cvtColor(imgL, cv.COLOR_BGR2GRAY)
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hsv = np.zeros_like(imgL)
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hsv[..., 1] = 255
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next = cv.cvtColor(imgR, cv.COLOR_BGR2GRAY)
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flow = cv.calcOpticalFlowFarneback(prvs, next, None, 0.5, 3, 15, 3, 5, 1.2, 0)
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mag, ang = cv.cartToPolar(flow[..., 0], flow[..., 1])
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hsv[..., 0] = ang*180/np.pi/2
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hsv[..., 2] = cv.normalize(mag, None, 0, 255, cv.NORM_MINMAX)
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bgr = cv.cvtColor(hsv, cv.COLOR_HSV2BGR)
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cv.namedWindow("MotionVector", cv.WINDOW_NORMAL)
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cv.namedWindow("frame", cv.WINDOW_NORMAL)
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cv.imshow('MotionVector', bgr)
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cv.imshow("frame", img)
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cv.waitKey(100)
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# ffmpeg.input("./vid/avatar.mkv")
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# Motion Vector
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#cap = cv2.VideoCapture('./vid/zootopia.mkv')
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# for i in range(1,10000):
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# cap.read()
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# params for ShiTomasi corner detection
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# feature_params = dict( maxCorners = 100,
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# qualityLevel = 0.3,
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# minDistance = 7,
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# blockSize = 7 )
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# Parameters for lucas kanade optical flow
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# lk_params = dict( winSize = (15,15),
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# maxLevel = 2,
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# criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))
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# Create some random colors
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#color = np.random.randint(0,255,(100,3))
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# Take first frame and find corners in it
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#ret, old_frame = cap.read()
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#old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
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#p0 = cv2.goodFeaturesToTrack(old_gray, mask = None, **feature_params)
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# Create a mask image for drawing purposes
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#mask = np.zeros_like(old_frame)
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# while(1):
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# ret,frame = cap.read()
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# frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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# # calculate optical flow
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# p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
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# # Select good points
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# good_new = p1[st==1]
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# good_old = p0[st==1]
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# # draw the tracks
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# for i,(new,old) in enumerate(zip(good_new,good_old)):
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# a,b = new.ravel()
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# c,d = old.ravel()
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# mask = cv2.line(mask, (a,b),(c,d), color[i].tolist(), 2)
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# frame = cv2.circle(frame,(a,b),5,color[i].tolist(),-1)
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# img = cv2.add(frame,mask)
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# cv2.imshow('frame',img)
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# k = cv2.waitKey(30) & 0xff
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# if k == 27:
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# break
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# # Now update the previous frame and previous points
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# old_gray = frame_gray.copy()
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# p0 = good_new.reshape(-1,1,2)
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# cv2.destroyAllWindows()
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# cap.release()
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# 中文文件名无法识别
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# imgDirs = os.listdir("./pic_en")
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# def read_frame_as_jpeg(in_filename, frame_num):
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# out, err = (
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# ffmpeg
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# .input(in_filename)
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# .filter('select', 'gte(n,{})'.format(frame_num))
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# .output('pipe:', vframes=1, format='image2', vcodec='mjpeg')
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# .run(capture_stdout=True)
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# )
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# return out
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# ffmpeg.input("./vid/venom.mkv")
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# ffmpeg.
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#img = read_frame_as_jpeg("./vid/venom.mkv", 648)
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# print(type(img))
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#img = cv2.imdecode(img,0)
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# print(img)
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# cv2.imshow("img",img)
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#imgL = np.split(img, 2, 1)[0]
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#imgR = np.split(img, 2, 1)[1]
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#stereo = cv2.StereoBM_create(numDisparities=64, blockSize=11)
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#disparity = stereo.compute(imgL, imgR)
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# plt.imshow(disparity)
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# plt.show()
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# for imgDir in imgDirs:
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# dir = "./pic_en/"+imgDir
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# print(dir)
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# img = cv2.imread(dir)
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# imgL = np.split(img, 2, 1)[0]
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# imgR = np.split(img, 2, 1)[1]
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# print(img.shape)
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# print(imgL.shape)
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# print(imgR.shape)
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# cv2.imshow("img", img)
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# stereo = cv2.StereoSGBM_create(numDisparities=96, blockSize=11)
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# disparity = stereo.compute(imgL, imgR)
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# plt.imshow(disparity)
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# plt.show()
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# import numpy as np
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# import cv2
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# from matplotlib import pyplot as plt
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#
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# imgL = cv2.imread('tsukuba_l.png',0)
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# imgR = cv2.imread('tsukuba_r.png',0)
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#
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# stereo = cv2.StereoBM_create(numDisparities=16, blockSize=15)
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# disparity = stereo.compute(imgL,imgR)
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# plt.imshow(disparity,'gray')
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# plt.show()
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