diff --git a/StereoVidComfort.py b/StereoVidComfort.py
index 4d1b0e9..8e9dee3 100644
--- a/StereoVidComfort.py
+++ b/StereoVidComfort.py
@@ -18,8 +18,6 @@ TODO:
 '''
 
 # 打开视频文件
-
-
 def openVid():
     fileName = input("video path:")
     while not os.path.isfile(fileName):
@@ -42,8 +40,6 @@ def getFrameCount(cap):
         sys.exit()
 
 # 获取帧速率
-
-
 def getFrameRate(cap):
     if cap.isOpened():
         return cap.get(cv2.CAP_PROP_FPS)
@@ -52,8 +48,6 @@ def getFrameRate(cap):
         sys.exit()
 
 # 给出左右画面，计算景深
-
-
 def getDepthMap(imgL, imgR):
     stereo = cv2.StereoSGBM_create(numDisparities=64, blockSize=3)
     return stereo.compute(imgL, imgR)
@@ -136,110 +130,3 @@ if __name__ == "__main__":
         prvs = next  # 当前帧覆盖上一帧，继续计算
     print("success")
 
-
-# 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):
-#    out, err = (
-#        ffmpeg
-#        .input(in_filename)
-#        .filter('select', 'gte(n,{})'.format(frame_num))
-#        .output('pipe:', vframes=1, format='image2', vcodec='mjpeg')
-#        .run(capture_stdout=True)
-#    )
-#    return out
-
-# ffmpeg.input("./vid/venom.mkv")
-# ffmpeg.
-
-#img = read_frame_as_jpeg("./vid/venom.mkv", 648)
-# print(type(img))
-#img = cv2.imdecode(img,0)
-# print(img)
-# cv2.imshow("img",img)
-#imgL = np.split(img, 2, 1)[0]
-#imgR = np.split(img, 2, 1)[1]
-#stereo = cv2.StereoBM_create(numDisparities=64, blockSize=11)
-#disparity = stereo.compute(imgL, imgR)
-# plt.imshow(disparity)
-# plt.show()
-
-
-# for imgDir in imgDirs:
-#    dir = "./pic_en/"+imgDir
-#    print(dir)
-#    img = cv2.imread(dir)
-
-#    imgL = np.split(img, 2, 1)[0]
-#    imgR = np.split(img, 2, 1)[1]
-#    print(img.shape)
-#    print(imgL.shape)
-#    print(imgR.shape)
-#    cv2.imshow("img", img)
-#    stereo = cv2.StereoSGBM_create(numDisparities=96, blockSize=11)
-#    disparity = stereo.compute(imgL, imgR)
-
-#    plt.imshow(disparity)
-#    plt.show()
-# 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')
-# plt.show()
diff --git a/picMV.py b/picMV.py
index 1e16bba..58371b9 100644
--- a/picMV.py
+++ b/picMV.py
@@ -19,4 +19,112 @@ cv.namedWindow("MotionVector", cv.WINDOW_NORMAL)
 cv.namedWindow("frame", cv.WINDOW_NORMAL)
 cv.imshow('MotionVector', bgr)
 cv.imshow("frame", img)
-cv.waitKey(100)
\ No newline at end of file
+cv.waitKey(100)
+
+
+# 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):
+#    out, err = (
+#        ffmpeg
+#        .input(in_filename)
+#        .filter('select', 'gte(n,{})'.format(frame_num))
+#        .output('pipe:', vframes=1, format='image2', vcodec='mjpeg')
+#        .run(capture_stdout=True)
+#    )
+#    return out
+
+# ffmpeg.input("./vid/venom.mkv")
+# ffmpeg.
+
+#img = read_frame_as_jpeg("./vid/venom.mkv", 648)
+# print(type(img))
+#img = cv2.imdecode(img,0)
+# print(img)
+# cv2.imshow("img",img)
+#imgL = np.split(img, 2, 1)[0]
+#imgR = np.split(img, 2, 1)[1]
+#stereo = cv2.StereoBM_create(numDisparities=64, blockSize=11)
+#disparity = stereo.compute(imgL, imgR)
+# plt.imshow(disparity)
+# plt.show()
+
+
+# for imgDir in imgDirs:
+#    dir = "./pic_en/"+imgDir
+#    print(dir)
+#    img = cv2.imread(dir)
+
+#    imgL = np.split(img, 2, 1)[0]
+#    imgR = np.split(img, 2, 1)[1]
+#    print(img.shape)
+#    print(imgL.shape)
+#    print(imgR.shape)
+#    cv2.imshow("img", img)
+#    stereo = cv2.StereoSGBM_create(numDisparities=96, blockSize=11)
+#    disparity = stereo.compute(imgL, imgR)
+
+#    plt.imshow(disparity)
+#    plt.show()
+# 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')
+# plt.show()