diff --git a/.vscode/settings.json b/.vscode/settings.json
deleted file mode 100644
index b881eff..0000000
--- a/.vscode/settings.json
+++ /dev/null
@@ -1,3 +0,0 @@
-{
-    "python.analysis.autoImportCompletions": true
-}
\ No newline at end of file
diff --git a/1/4.ipynb b/1/4.ipynb
index 78f82d4..86bce9d 100644
--- a/1/4.ipynb
+++ b/1/4.ipynb
@@ -2,51 +2,27 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "hellohellohello\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(\"hello\" * 3)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "x = 2, y = 3.000000\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(\"x = %d, y = %f\" % (2, 3.0))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(2-3j)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "x = 3 + 2j\n",
     "y = -1j\n",
@@ -55,26 +31,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "abcdefg\n",
-      "bc\n",
-      "bcdefg\n",
-      "abc\n",
-      "abcdef\n",
-      "ef\n",
-      "efg\n",
-      "abcdefg\n",
-      "aceg\n",
-      "gfedcba\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "strs = \"abcdefg\"\n",
     "print(strs[0:7:1])\n",
@@ -91,17 +50,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "较小值为：  5.7\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "def minimal(x, y):\n",
     "    if x > y:\n",
diff --git a/1/5.py b/1/5.py
index 3b14152..89cf8d9 100644
--- a/1/5.py
+++ b/1/5.py
@@ -1,9 +1,9 @@
 import cv2
 
-lenna = cv2.imread(r"img\Lenna.png")
+lenna = cv2.imread(r"src.jpg")
 print(type(lenna))
 cv2.namedWindow("Lena", cv2.WINDOW_AUTOSIZE)
 cv2.imshow("Lena", lenna)
 cv2.waitKey(0)
 cv2.destroyWindow("Lena")
-cv2.imwrite(r"img\test_imwrite.png", lenna, (cv2.IMWRITE_PNG_COMPRESSION, 5))
+cv2.imwrite(r"1\imwrite.png", lenna, (cv2.IMWRITE_PNG_COMPRESSION, 5))
diff --git a/1/6.py b/1/6.py
index bb83d43..7087944 100644
--- a/1/6.py
+++ b/1/6.py
@@ -3,7 +3,7 @@ import matplotlib.pyplot as plt
 
 plt.rcParams["font.family"] = ["SimHei"]
 plt.rcParams["axes.unicode_minus"] = False
-img_BGR = cv2.imread(r"img\iris.jpg")
+img_BGR = cv2.imread(r"src.jpg")
 img_RGB = cv2.cvtColor(img_BGR, cv2.COLOR_BGR2RGB)
 plt.imshow(img_RGB)
 plt.show()
diff --git a/1/img/Lenna.png b/1/img/Lenna.png
deleted file mode 100644
index 1538e24..0000000
Binary files a/1/img/Lenna.png and /dev/null differ
diff --git a/1/img/iris.jpg b/1/img/iris.jpg
deleted file mode 100644
index 847face..0000000
Binary files a/1/img/iris.jpg and /dev/null differ
diff --git a/2/1.py b/2/1.py
index d1ece85..b1b8b89 100644
--- a/2/1.py
+++ b/2/1.py
@@ -21,7 +21,7 @@ def histogram_equalization(im):
 
 
 if __name__ == "__main__":
-    im = cv.imread(r"E:\OneDrive\Code\Python\2\iris.jpg", cv.IMREAD_GRAYSCALE)
+    im = cv.imread(r"src.jpg", cv.IMREAD_GRAYSCALE)
     im1 = global_linear_transmation(im, 0, 150)
     im2 = global_linear_transmation(im, 100)
     im3 = global_linear_transmation(im, 50, 150)
diff --git a/2/2.py b/2/2.py
index aaa6c63..d26111b 100644
--- a/2/2.py
+++ b/2/2.py
@@ -10,7 +10,7 @@ def gamma_trans(img, gamma=1.0):
 
 
 if __name__ == "__main__":
-    im = cv.imread(r"E:\OneDrive\Code\Python\2\iris.jpg", cv.IMREAD_GRAYSCALE)
+    im = cv.imread(r"src.jpg", cv.IMREAD_GRAYSCALE)
     im1 = gamma_trans(im, 0.5)
     im2 = gamma_trans(im, 1.5)
     plt.figure()
diff --git a/2/3.py b/2/3.py
index cda9dc5..793fc78 100644
--- a/2/3.py
+++ b/2/3.py
@@ -2,7 +2,7 @@ import cv2 as cv
 from matplotlib import pyplot as plt
 import numpy as np
 
-img = cv.imread(r"E:\OneDrive\Code\Python\2\iris.jpg", 0)
+img = cv.imread(r"src.jpg", 0)
 fil1 = 1 / 16 * np.array([[1, 2, 1], [2, 4, 2], [1, 2, 1]])
 fil2 = 1 / 9 * np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]])
 fil3 = 1 / 10 * np.array([[1, 1, 1], [1, 2, 1], [1, 1, 1]])
diff --git a/2/4.py b/2/4.py
index e1e4e51..b9400ce 100644
--- a/2/4.py
+++ b/2/4.py
@@ -33,7 +33,7 @@ def addGaussianNoise(src, means, sigma):
 
 
 if __name__ == "__main__":
-    im = cv.imread(r"E:\OneDrive\Code\Python\2\iris.jpg", cv.IMREAD_GRAYSCALE)
+    im = cv.imread(r"src.jpg", cv.IMREAD_GRAYSCALE)
     im1 = addSaltAndPepper(im, 0.1)
     im11 = cv.blur(im1, (3, 3))
     im12 = cv.medianBlur(im1, 3)
diff --git a/2/5.py b/2/5.py
index 816a171..9918d9b 100644
--- a/2/5.py
+++ b/2/5.py
@@ -2,7 +2,7 @@ import cv2 as cv
 from matplotlib import pyplot as plt
 import numpy as np
 
-img = cv.imread(r"E:\OneDrive\Code\Python\2\iris.jpg", 0)
+img = cv.imread(r"src.jpg", 0)
 lplc = np.array([[0, -1, 0], [-1, 4, -1], [0, -1, 0]])
 lplcEnhance = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
 ImgLplc = cv.filter2D(img, -1, lplc, borderType=cv.BORDER_DEFAULT)
diff --git a/2/iris.jpg b/src.jpg
similarity index 100%
rename from 2/iris.jpg
rename to src.jpg