diff --git a/test.py b/test.py
index 3fb88cb..c38173f 100644
--- a/test.py
+++ b/test.py
@@ -1,4 +1,4 @@
-
+import numpy as np
 import cv2
 
 # 設定連接到 Android 手機的相機
@@ -6,48 +6,138 @@ cap = cv2.VideoCapture(0)  # 0 表示第一個相機（通常是後置相機）
 cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)  # 設定寬度
 cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)  # 設定高度
 
+object_points = np.array([[0, 0, 0], [26, 0, 0], [0, 18.5, 0], [26, 18.5, 0]], dtype=np.float32)
 
-while True:
-    ret, frame = cap.read()  # 讀取影片幀
+def get_new_approx(approx, previous_approx):
+    def distance(point, pre_point):
+        point = point[0]
+        pre_point = pre_point[0]
+        d = ((point[0]-pre_point[0]) ** 2) + ((point[1]-pre_point[1]) ** 2)
 
-    if not ret:
-        break
+        return np.sqrt(d)
 
-    # 預處理影像（例如：轉為灰度）
-    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    new_approx = []
+    for pre_point in previous_approx:
+        min_d, min_index = 1e9, -100
+        for index, point in enumerate(approx):
+            d = distance(point, pre_point)
+            if d < min_d and d<=500:
+                min_d = d
+                min_index = index
+            
+        if min_index != -100:
+            np.delete(approx, min_index)
+            new_approx.append(approx[min_index])
 
-    # 偵測邊緣
-    edges = cv2.Canny(gray, 100, 200)
+    if len(new_approx) == 4:
+        return new_approx
+    else:
+        return previous_approx
 
-    # 偵測輪廓
-    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+def initial_approx(approx):
+    distance = []
+    for point in approx:
+        x, y = point[0]
+        distance.append(x**2+y**2)
+    min_d, max_d = 1e9, -1
+    min_index, max_index = -100, -100
+    for index, d in enumerate(distance):
+        if d < min_d:
+            min_d = d
+            min_index = index
+        if d > max_d:
+            max_d = d
+            max_index = index
+    new_approx = []
 
-    # 找到最大的輪廓
-    max_contour = max(contours, key=cv2.contourArea)
+    remain_index = list(range(4))
+    remain_index.remove(max_index)
+    remain_index.remove(min_index)
 
-    # 找到輪廓的近似多邊形
-    epsilon = 0.05 * cv2.arcLength(max_contour, True)
-    approx = cv2.approxPolyDP(max_contour, epsilon, True)
+    if approx[remain_index[0]][0][0] > approx[remain_index[1]][0][0]:   # remain 的第一個點的 x 大於第二個點的，代表他在右上角
+        second_index = remain_index[0]
+        third_index = remain_index[1]
+    else:
+        second_index = remain_index[1]
+        third_index = remain_index[0]
 
-    # 繪製多邊形
-    if len(approx) == 4:  # 確保是四個角點
-        for point in approx:
-            print(point)
-            x, y = point[0]
-            cv2.circle(frame, (x, y), 5, (0, 0, 255), -1)  # 在角點位置畫紅色圓圈
-
-        cv2.drawContours(frame, [approx], -1, (0, 255, 0), 2)  # 繪製輪廓
-        print()
-
-    # 顯示結果
-    cv2.imshow('Paper Detection', frame)
-    # 按下 'q' 鍵退出迴圈
-    if cv2.waitKey(33) & 0xFF == ord('q'):  # 等待 33ms (1秒 = 1000ms, 1秒顯示30幀)
-        break
+    new_approx.append(approx[min_index])
+    new_approx.append(approx[second_index])
+    new_approx.append(approx[third_index])
+    new_approx.append(approx[max_index])
+    
+    return new_approx
 
 
+        
+if __name__ == '__main__':
 
-cap.release()
-cv2.destroyAllWindows()
+    previous_approx = []
+    
+    while True:
+        ret, frame = cap.read()  # 讀取影片幀
+
+        if not ret:
+            break
+
+        # 預處理影像（例如：轉為灰度）
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        gray = cv2.GaussianBlur(gray, (5, 5), 0)
+
+        # 偵測邊緣
+        edges = cv2.Canny(gray, 30, 90)
+        dilate_kernel = np.ones((5, 5), np.uint8)
+        dilate_edges = cv2.dilate(edges, dilate_kernel, iterations=1)
+
+        # 偵測輪廓
+        contours, _ = cv2.findContours(dilate_edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+        if contours != []:
+            # 找到最大的輪廓
+            max_contour = max(contours, key=cv2.contourArea)
+
+            # 找到輪廓的近似多邊形
+            epsilon = 0.05 * cv2.arcLength(max_contour, True)
+            approx = cv2.approxPolyDP(max_contour, epsilon, True)
+
+            # 繪製多邊形
+            if len(approx) == 4:  # 確保是四個角點
+                if previous_approx == []:
+                    print("INITIAL")
+                    previous_approx = initial_approx(approx)
+                new_approx = get_new_approx(approx, previous_approx)
+                previous_approx = new_approx
+
+                x, y = new_approx[0][0]
+                cv2.circle(frame, (x, y), 15, (0, 0, 255), -1)  # 在角點位置畫紅色圓圈
+                
+                x, y = new_approx[1][0]
+                cv2.circle(frame, (x, y), 30, (0, 0, 255), -1)  # 在角點位置畫紅色圓圈
+
+                x, y = new_approx[2][0]
+                cv2.circle(frame, (x, y), 15, (255, 0, 0), -1)  # 在角點位置畫紅色圓圈
+
+                x, y = new_approx[3][0]
+                cv2.circle(frame, (x, y), 30, (255, 0, 0), -1)  # 在角點位置畫紅色圓圈
+
+                cv2.drawContours(frame, [approx], -1, (0, 255, 0), 2)  # 繪製輪廓
+
+            # 顯示結果
+            cv2.namedWindow('Paper Detection(edge)', 0)
+            cv2.imshow('Paper Detection(edge)', edges)
+            cv2.namedWindow('Paper Detection(dilate edge)', 0)
+            cv2.imshow('Paper Detection(dilate edge)', dilate_edges)
+            cv2.namedWindow('Paper Detection', 0)
+            cv2.imshow('Paper Detection', frame)
+
+            # 按下 'q' 鍵退出迴圈
+            if cv2.waitKey(33) & 0xFF == ord('q'):  # 等待 33ms (1秒 = 1000ms, 1秒顯示幀)
+                break
+            if cv2.waitKey(33) & 0xFF == ord(' '):
+                print("Clear previous approxes")
+                previous_approx = []
+
+    cap.release()
+    cv2.destroyAllWindows()