diff --git a/ObjBodyFile/Sample/aa.mtl b/ObjBodyFile/Sample/aa.mtl
new file mode 100644
index 0000000..05f7434
--- /dev/null
+++ b/ObjBodyFile/Sample/aa.mtl
@@ -0,0 +1,9 @@
+
+newmtl material_0
+Ka 0.200000 0.200000 0.200000
+Kd 1.000000 1.000000 1.000000
+Ks 1.000000 1.000000 1.000000
+Tr 0.000000
+illum 2
+Ns 1.000000
+map_Kd aa.png
\ No newline at end of file
diff --git a/ObjBodyFile/Sample/aa.obj b/ObjBodyFile/Sample/aa.obj
new file mode 100644
index 0000000..fc95b36
--- /dev/null
+++ b/ObjBodyFile/Sample/aa.obj
@@ -0,0 +1,17 @@
+
+mtllib aa.mtl
+
+v 0 0 0 
+v 1 0 0
+v 1 1 0
+v 0 1 0 
+
+vt 0 0
+vt 2 0
+vt 2 1
+vt 0 1
+
+usemtl material_0
+
+f 1/1 2/2 3/3
+f 1/1 3/3 4/4
\ No newline at end of file
diff --git a/ObjBodyFile/Sample/aa.png b/ObjBodyFile/Sample/aa.png
new file mode 100644
index 0000000..179bf86
Binary files /dev/null and b/ObjBodyFile/Sample/aa.png differ
diff --git a/OpenCV/contours/blackBG.jpg b/OpenCV/contours/blackBG.jpg
new file mode 100644
index 0000000..fe77ab8
Binary files /dev/null and b/OpenCV/contours/blackBG.jpg differ
diff --git a/OpenCV/contours/image.jpg b/OpenCV/contours/image.jpg
new file mode 100644
index 0000000..86066e1
Binary files /dev/null and b/OpenCV/contours/image.jpg differ
diff --git a/OpenCV/contours/test.ipynb b/OpenCV/contours/test.ipynb
new file mode 100644
index 0000000..3421064
--- /dev/null
+++ b/OpenCV/contours/test.ipynb
@@ -0,0 +1,163 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import numpy as np\n",
+    "\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "img =cv2.imread(\"blackBG.jpg\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# grayscale \n",
+    "# https://docs.opencv.org/4.5.0/d7/d4d/tutorial_py_thresholding.html\n",
+    "gray_img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\n",
+    "ret,bin_img = cv2.threshold(gray_img,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-0.5, 972.5, 917.5, -0.5)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# RETR_EXTERNAL:仅外圈轮廓\n",
+    "contours, hierarchy = cv2.findContours(bin_img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n",
+    "\n",
+    "cv2.drawContours(img,contours,-1,(0,255,0),5)\n",
+    "plt.imshow(img[...,::-1])\n",
+    "plt.axis('off')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# RetrievalModes:https://docs.opencv.org/4.5.0/d3/dc0/group__imgproc__shape.html#ga819779b9857cc2f8601e6526a3a5bc71\n",
+    "#ContourApproximationModes:https://docs.opencv.org/4.5.0/d3/dc0/group__imgproc__shape.html#ga4303f45752694956374734a03c54d5ff\n",
+    "contours, hierarchy = cv2.findContours(bin_img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-0.5, 972.5, 917.5, -0.5)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cv2.drawContours(img,contours,-1,(0,255,0),5)\n",
+    "plt.imshow(img[...,::-1])\n",
+    "plt.axis('off')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/OpenCV/contours/whiteBG.jpg b/OpenCV/contours/whiteBG.jpg
new file mode 100644
index 0000000..91b4fee
Binary files /dev/null and b/OpenCV/contours/whiteBG.jpg differ
diff --git a/flaskfile/server.py b/flaskfile/server.py
index 8d46782..50e9463 100644
--- a/flaskfile/server.py
+++ b/flaskfile/server.py
@@ -1,5 +1,5 @@
 from werkzeug.utils import secure_filename
-from flask import Flask,render_template,jsonify,request,url_for,send_from_directory
+from flask import Flask,render_template,jsonify,request,url_for,send_from_directory,redirect
 import time
 import os
 import base64
@@ -30,7 +30,7 @@ def api_upload():
     fname = request.form["name"]
     if f and allowed_file(fname):  # 判断是否是允许上传的文件类型
         f.save(os.path.join(file_dir,fname))  #保存文件到upload目录 
-        print(url_for('uploaded_file',filename=fname))
+        #return redirect(url_for('uploaded_file',filename=fname))
         return jsonify({"succeed":'True',"msg":"upload succeed"})
     else:
         return jsonify({"succeed":'False',"msg":"upload failed"})
diff --git a/flaskfile/upload/1.jpg b/flaskfile/upload/1.jpg
deleted file mode 100644
index b38aad7..0000000
Binary files a/flaskfile/upload/1.jpg and /dev/null differ
diff --git a/flaskfile/upload/3.jpg b/flaskfile/upload/3.jpg
new file mode 100644
index 0000000..1d874e2
Binary files /dev/null and b/flaskfile/upload/3.jpg differ