diff --git "a/\345\265\214\345\205\245\345\274\217-\346\216\247\345\210\266\347\273\204/\344\272\221\345\217\260\350\247\206\350\247\211\346\250\241\345\235\227\344\273\243\347\240\201\357\274\210maixcam\357\274\211" "b/\345\265\214\345\205\245\345\274\217-\346\216\247\345\210\266\347\273\204/\344\272\221\345\217\260\350\247\206\350\247\211\346\250\241\345\235\227\344\273\243\347\240\201\357\274\210maixcam\357\274\211"
new file mode 100644
index 0000000000000000000000000000000000000000..55b16e2cbbea12cb0a1b7691aaca15d53e381c1f
--- /dev/null
+++ "b/\345\265\214\345\205\245\345\274\217-\346\216\247\345\210\266\347\273\204/\344\272\221\345\217\260\350\247\206\350\247\211\346\250\241\345\235\227\344\273\243\347\240\201\357\274\210maixcam\357\274\211"
@@ -0,0 +1,328 @@
+from maix import image, camera, display, app, uart, time
+ 
+import cv2
+ 
+import numpy as np
+ 
+from struct import pack
+ 
+ 
+ 
+# 初始化串口
+# 初始化串口，异常保护
+try:
+    serial = uart.UART("/dev/ttyS0", 115200)
+except Exception as e:
+    print("串口初始化失败，请检查设备:", e)
+    raise SystemExit
+ 
+ 
+# 初始化摄像头和显示器
+ 
+cam = camera.Camera(512, 320, fps=80)
+ 
+disp = display.Display()
+ 
+#红色在 RGB 空间容易受光照干扰，而在 LAB 色彩空间的 A 通道 中，红色数值范围更集中。
+ 
+# 红点检测阈值（LAB 色彩空间 A 通道）
+ 
+A_MIN = 150
+ 
+A_MAX = 255
+ 
+kernel_red = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
+ 
+ 
+ 
+MIN_AREA = 2000
+ 
+MAX_AREA = 80000
+ 
+ 
+ 
+pause_rect_detect = False  # 是否暂停矩形检测
+ 
+ 
+ 
+def sort_rect_points(pts):
+ 
+    pts = sorted(pts, key=lambda p: (p[1], p[0]))
+ 
+    top = sorted(pts[:2], key=lambda p: p[0])
+ 
+    bottom = sorted(pts[2:], key=lambda p: p[0], reverse=True)
+ 
+    return [top[0], top[1], bottom[0], bottom[1]]
+ 
+ 
+ 
+def match_corners_by_distance(ref_pts, target_pts):
+ 
+    matched = [None] * 4
+ 
+    used = [False] * 4
+ 
+    for i, p1 in enumerate(ref_pts):
+ 
+        min_dist = float("inf")
+ 
+        min_j = -1
+ 
+        for j, p2 in enumerate(target_pts):
+ 
+            if used[j]:
+ 
+                continue
+ 
+            dist = np.linalg.norm(np.array(p1) - np.array(p2))
+ 
+            if dist < min_dist:
+ 
+                min_dist = dist
+ 
+                min_j = j
+ 
+        matched[i] = target_pts[min_j]
+ 
+        used[min_j] = True
+ 
+    return matched
+ 
+ 
+ 
+def is_similar_rect(rect1, rect2, threshold=8, area_thresh=0.05):
+ 
+    try:
+ 
+        rect1 = sort_rect_points(rect1)
+ 
+        rect2 = sort_rect_points(rect2)
+ 
+        avg_dist = np.mean([np.linalg.norm(np.array(p1) - np.array(p2)) for p1, p2 in zip(rect1, rect2)])
+ 
+        area1 = cv2.contourArea(np.array(rect1, dtype=np.int32))
+ 
+        area2 = cv2.contourArea(np.array(rect2, dtype=np.int32))
+ 
+        area_diff_ratio = abs(area1 - area2) / max(area1, area2)
+ 
+        return avg_dist < threshold and area_diff_ratio < area_thresh
+ 
+    except Exception as e:
+ 
+        print("矩形比较异常:", e)
+ 
+        return False
+ 
+ 
+ 
+def is_rectangle(approx):
+ 
+    if approx is None or len(approx) != 4 or not cv2.isContourConvex(approx):
+ 
+        return False
+ 
+    pts = [point[0] for point in approx]
+ 
+    def angle(p1, p2, p3):
+ 
+        v1 = np.array(p1) - np.array(p2)
+ 
+        v2 = np.array(p3) - np.array(p2)
+ 
+        norm1 = np.linalg.norm(v1)
+ 
+        norm2 = np.linalg.norm(v2)
+ 
+        if norm1 == 0 or norm2 == 0:
+ 
+            return 0
+ 
+        cos_angle = np.clip(np.dot(v1, v2) / (norm1 * norm2), -1.0, 1.0)
+ 
+        return np.arccos(cos_angle) * 180 / np.pi
+ 
+    angles = [angle(pts[i - 1], pts[i], pts[(i + 1) % 4]) for i in range(4)]
+ 
+    return all(80 < ang < 100 for ang in angles)
+ 
+ 
+ 
+# 主循环
+ 
+while not app.need_exit():
+ 
+    try:
+ 
+        # 检查串口是否接收到 0x66
+ 
+        try:
+ 
+            data = serial.read()
+ 
+            if data and b'\x66' in data:
+ 
+                pause_rect_detect = True
+ 
+        except Exception as e:
+ 
+            print("串口读取异常:", e)
+ 
+ 
+ 
+        img = cam.read()
+ 
+        if img is None:
+ 
+            continue
+ 
+ 
+ 
+        try:
+ 
+            img_raw = image.image2cv(img, copy=True)
+ 
+        except Exception as e:
+ 
+            print("图像转换失败:", e)
+ 
+            continue
+ 
+ 
+ 
+        red_dot = (-1, -1)
+ 
+        midpoints = [(-1, -1)] * 4
+ 
+ 
+ 
+        # 红点检测（使用 LAB 色彩空间）
+ 
+        try:
+ 
+            lab = cv2.cvtColor(img_raw, cv2.COLOR_BGR2Lab)
+ 
+            _, A, _ = cv2.split(lab)
+ 
+            A = A.astype(np.uint8)
+ 
+            mask = cv2.inRange(A, np.array(A_MIN, dtype=np.uint8), np.array(A_MAX, dtype=np.uint8))
+ 
+            mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel_red)
+ 
+            mask = cv2.morphologyEx(mask, cv2.MORPH_DILATE, kernel_red)
+ 
+ 
+ 
+            contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+ 
+            if contours:
+ 
+                max_cnt = max(contours, key=cv2.contourArea)
+ 
+                if cv2.contourArea(max_cnt) > 20:
+ 
+                    M = cv2.moments(max_cnt)
+ 
+                    if M["m00"] != 0:
+ 
+                        cx = int(M["m10"] / M["m00"])
+ 
+                        cy = int(M["m01"] / M["m00"])
+ 
+                        red_dot = (cx, cy)
+ 
+                        cv2.circle(img_raw, (cx, cy), 5, (0, 255, 0), -1)
+ 
+        except Exception as e:
+ 
+            print("红点检测异常:", e)
+ 
+ 
+ 
+
+        # 初始化矩形中心坐标
+        rect_center = (-1, -1)
+
+        # 矩形检测与中点计算
+        if not pause_rect_detect:
+            try:
+                gray = cv2.cvtColor(img_raw, cv2.COLOR_BGR2GRAY)
+                bin_img = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C,
+                                                cv2.THRESH_BINARY, 11, 2)
+                closed = cv2.morphologyEx(bin_img, cv2.MORPH_CLOSE,
+                                        cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3)))
+
+                contours, _ = cv2.findContours(closed, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+                rectangles = []
+
+                for contour in contours:
+                    area = cv2.contourArea(contour)
+                    if not (MIN_AREA <= area <= MAX_AREA):
+                        continue
+
+                    x, y, w, h = cv2.boundingRect(contour)
+                    margin = 1
+                    if x < margin or y < margin or x + w > img_raw.shape[1] - margin or y + h > img_raw.shape[0] - margin:
+                        continue
+
+                    approx = cv2.approxPolyDP(contour, 0.02 * cv2.arcLength(contour, True), True)
+                    if is_rectangle(approx):
+                        rect = [tuple(pt[0]) for pt in approx]
+                        if not any(is_similar_rect(rect, r) for r in rectangles):
+                            rectangles.append(rect)
+                            cv2.drawContours(img_raw, [np.array(rect, dtype=np.int32)], -1, (0, 255, 0), 2)
+                            for x, y in rect:
+                                cv2.circle(img_raw, (x, y), 5, (0, 0, 255), -1)
+
+                if rectangles:
+                    # 取第一个矩形，计算中心点
+                    rect_pts = sort_rect_points(rectangles[0])
+                    cx = sum([pt[0] for pt in rect_pts]) // 4
+                    cy = sum([pt[1] for pt in rect_pts]) // 4
+                    rect_center = (cx, cy)
+                    cv2.circle(img_raw, rect_center, 6, (255, 255, 0), -1)  # 显示矩形中心
+                    
+                
+            except Exception as e:
+                print("矩形检测异常:", e)
+
+        # 数据打包并发送（只发送矩形中心）
+        try:
+            payload = b'\xAA\x55'
+            if rect_center[0] < 0 or rect_center[1] < 0:
+                payload += pack("<hh", 0, 0)
+            else:
+                payload += pack("<hh", *rect_center)
+
+            serial.write(payload)
+            print("发送坐标:", rect_center)  # 打印发送内容，调试用
+
+        except Exception as e:
+            print("串口发送异常:", e)
+        
+        # 显示图像
+ 
+        try:
+            if rect_center and rect_center[0] >= 0 and rect_center[1] >= 0:
+                target_x, target_y = rect_center
+                cv2.putText(img_raw, f"Target: ({target_x},{target_y})", (5, 25),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 255), 2)
+            else:
+                cv2.putText(img_raw, "No Target", (5, 25),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+            img_show = image.cv2image(img_raw, copy=False)
+            disp.show(img_show)
+ 
+        except Exception as e:
+ 
+            print("图像显示失败:", e)
+ 
+ 
+ 
+        time.sleep_ms(1)
+ 
+ 
+ 
+    except Exception as e:
+ 
+        print("主循环异常:", e)
\ No newline at end of file