diff --git a/MV.py b/MV.py new file mode 100644 index 0000000..fcb4250 --- /dev/null +++ b/MV.py @@ -0,0 +1,34 @@ +import cv2 as cv +import numpy as np +cap = cv.VideoCapture("./vid/zootopia.mkv") +ret, frame1 = cap.read() +prvs = cv.cvtColor(frame1,cv.COLOR_BGR2GRAY) +hsv = np.zeros_like(frame1) +hsv[...,1] = 255 +print("read") +cap.set(cv.CAP_PROP_POS_FRAMES,59760) +print("read done") +while(1): + for i in range(1,12): + cap.read() + ret, frame2 = cap.read() + next = cv.cvtColor(frame2,cv.COLOR_BGR2GRAY) + flow = cv.calcOpticalFlowFarneback(prvs,next, None, 0.5, 3, 15, 3, 5, 1.2, 0) + mag, ang = cv.cartToPolar(flow[...,0], flow[...,1]) + hsv[...,0] = ang*180/np.pi/2 + hsv[...,2] = cv.normalize(mag,None,0,255,cv.NORM_MINMAX) + bgr = cv.cvtColor(hsv,cv.COLOR_HSV2BGR) + cv.namedWindow("frame2", cv.WINDOW_NORMAL) + cv.namedWindow("frame", cv.WINDOW_NORMAL) + cv.imshow('frame2',bgr) + cv.imshow("frame",frame2) + cv.waitKey(1) + #k = cv.waitKey(0.1) & 0xff + #if k == 27: + # break + #elif k == ord('s'): + # cv.imwrite('opticalfb.png',frame2) + # cv.imwrite('opticalhsv.png',bgr) + prvs = next +cap.release() +cv.destroyAllWindows() \ No newline at end of file diff --git a/StereoVidComfort.py b/StereoVidComfort.py index 659761f..579d0ae 100644 --- a/StereoVidComfort.py +++ b/StereoVidComfort.py @@ -6,34 +6,111 @@ import os import sys from matplotlib import pyplot as plt -cap = cv2.VideoCapture('./vid/zootopia.mkv') -frameCount = cap.get(cv2.CAP_PROP_FRAME_COUNT) -frameRate = cap.get(cv2.CAP_PROP_FPS) -for frameID in range(int(frameRate), int(frameCount), int(frameRate*100)): - cap.set(cv2.CAP_PROP_POS_FRAMES, frameID) - isSuccess, img = cap.read() - if isSuccess: - cv2.namedWindow("img",cv2.WINDOW_NORMAL); - cv2.imshow('img', img) - imgL = np.split(img, 2, 1)[0] - imgR = np.split(img, 2, 1)[1] - cv2.waitKey(1) - stereo = cv2.StereoSGBM_create(numDisparities=96, blockSize=7) - disparity = stereo.compute(imgL, imgR) - plt.title("DepthMap") - plt.imshow(disparity) - plt.pause(0.1) +def openVid(): + fileName = input("video path:") + while not os.path.isfile(fileName): + print("file doesn't exist!") + fileName = input("video path:") + cap = cv2.VideoCapture(fileName) + if not cap.isOpened(): + print("Video cannot be opened.") + sys.exit() + else: + return cap +def getFrameCount(cap): + if not cap.isOpened(): + print("Video cannot be opened.") + sys.exit() + else: + return cap.get(cv2.CAP_PROP_FRAME_COUNT) +def getFrameRate(cap): + if not cap.isOpened(): + print("Video cannot be opened.") + sys.exit() + else: + return cap.get(cv2.CAP_PROP_FPS) + + +if __name__ == "__main__": + cap = openVid() + frameRate = getFrameRate(cap) + frameCount = getFrameCount(cap) + + + for frameID in range(int(frameRate), int(frameCount), int(frameRate*100)): + cap.set(cv2.CAP_PROP_POS_FRAMES, frameID) + isSuccess, img = cap.read() + if isSuccess: + cv2.namedWindow("img", cv2.WINDOW_NORMAL) + cv2.imshow('img', img) + imgL = np.split(img, 2, 1)[0] + imgR = np.split(img, 2, 1)[1] + stereo = cv2.StereoSGBM_create(numDisparities=96, blockSize=11) + disparity = stereo.compute(imgL, imgR) + plt.title("DepthMap") + plt.imshow(disparity) + plt.pause(0.5) + + +# ffmpeg.input("./vid/avatar.mkv") + +# Motion Vector +#cap = cv2.VideoCapture('./vid/zootopia.mkv') +# for i in range(1,10000): +# cap.read() +# params for ShiTomasi corner detection +# feature_params = dict( maxCorners = 100, +# qualityLevel = 0.3, +# minDistance = 7, +# blockSize = 7 ) +# Parameters for lucas kanade optical flow +# lk_params = dict( winSize = (15,15), +# maxLevel = 2, +# criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03)) +# Create some random colors +#color = np.random.randint(0,255,(100,3)) +# Take first frame and find corners in it +#ret, old_frame = cap.read() +#old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY) +#p0 = cv2.goodFeaturesToTrack(old_gray, mask = None, **feature_params) +# Create a mask image for drawing purposes +#mask = np.zeros_like(old_frame) +# while(1): +# ret,frame = cap.read() +# frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) +# # calculate optical flow +# p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params) +# # Select good points +# good_new = p1[st==1] +# good_old = p0[st==1] +# # draw the tracks +# for i,(new,old) in enumerate(zip(good_new,good_old)): +# a,b = new.ravel() +# c,d = old.ravel() +# mask = cv2.line(mask, (a,b),(c,d), color[i].tolist(), 2) +# frame = cv2.circle(frame,(a,b),5,color[i].tolist(),-1) +# img = cv2.add(frame,mask) +# cv2.imshow('frame',img) +# k = cv2.waitKey(30) & 0xff +# if k == 27: +# break +# # Now update the previous frame and previous points +# old_gray = frame_gray.copy() +# p0 = good_new.reshape(-1,1,2) +# cv2.destroyAllWindows() +# cap.release() + # 中文文件名无法识别 # imgDirs = os.listdir("./pic_en") -#def read_frame_as_jpeg(in_filename, frame_num): +# def read_frame_as_jpeg(in_filename, frame_num): # out, err = ( # ffmpeg # .input(in_filename) @@ -59,9 +136,7 @@ for frameID in range(int(frameRate), int(frameCount), int(frameRate*100)): # plt.show() - - -#for imgDir in imgDirs: +# for imgDir in imgDirs: # dir = "./pic_en/"+imgDir # print(dir) # img = cv2.imread(dir) @@ -80,10 +155,10 @@ for frameID in range(int(frameRate), int(frameCount), int(frameRate*100)): # import numpy as np # import cv2 # from matplotlib import pyplot as plt -# +# # imgL = cv2.imread('tsukuba_l.png',0) # imgR = cv2.imread('tsukuba_r.png',0) -# +# # stereo = cv2.StereoBM_create(numDisparities=16, blockSize=15) # disparity = stereo.compute(imgL,imgR) # plt.imshow(disparity,'gray')