diff --git a/MV.py b/MV.py
deleted file mode 100644
index 3294277..0000000
--- a/MV.py
+++ /dev/null
@@ -1,38 +0,0 @@
-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("jump ahead")
-cap.set(cv.CAP_PROP_POS_FRAMES, 4)
-print("jump 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("MotionVector", cv.WINDOW_NORMAL)
-    cv.namedWindow("frame", cv.WINDOW_NORMAL)
-    cv.imshow('MotionVector', 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()
diff --git a/bridge.png b/bridge.png
deleted file mode 100644
index f370f4f..0000000
Binary files a/bridge.png and /dev/null differ
diff --git a/judy.png b/judy.png
deleted file mode 100644
index 553bd7c..0000000
Binary files a/judy.png and /dev/null differ
diff --git a/picMV.py b/picMV.py
deleted file mode 100644
index 58371b9..0000000
--- a/picMV.py
+++ /dev/null
@@ -1,130 +0,0 @@
-import cv2 as cv
-import numpy as np
-
-img = cv.imread("./pic/2.jpg")
-imgL = np.split(img, 2, 1)[0]
-imgR = np.split(img, 2, 1)[1]
-
-prvs = cv.cvtColor(imgL, cv.COLOR_BGR2GRAY)
-hsv = np.zeros_like(imgL)
-hsv[..., 1] = 255
-
-next = cv.cvtColor(imgR, 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("MotionVector", cv.WINDOW_NORMAL)
-cv.namedWindow("frame", cv.WINDOW_NORMAL)
-cv.imshow('MotionVector', bgr)
-cv.imshow("frame", img)
-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()