diff --git a/工程/1.py b/工程/1.py
new file mode 100644
index 0000000..041e004
--- /dev/null
+++ b/工程/1.py
@@ -0,0 +1,54 @@
+import cv2
+import numpy as np
+
+
+# 视频源设置为电脑摄像头，0通常代表默认摄像头
+cap = cv2.VideoCapture(0)
+
+# 定义要追踪的颜色范围
+# 注意：根据实际情况调整HSV值以精确匹配想要追踪的颜色
+greenLower = np.array([(35, 46, 120)])
+greenUpper = np.array([60, 255, 255])
+
+while True:
+    # 从摄像头读取一帧
+    ret, frame = cap.read()
+    if not ret:
+        break
+
+    # 将BGR图像转换为HSV，因为HSV在颜色分割上更为直观
+    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+
+    # 根据定义的HSV范围创建掩码
+    mask = cv2.inRange(hsv, greenLower, greenUpper)
+
+    # 对原图像和掩码应用位运算，提取出指定颜色部分
+    result = cv2.bitwise_and(frame, frame, mask=mask)
+
+    # 使用开运算和闭运算去除噪声
+    kernel = np.ones((5, 5), np.uint8)
+    mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
+    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
+
+    # 查找轮廓
+    contours, _ = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    # 遍历轮廓，画出边界框
+    for contour in contours:
+        if cv2.contourArea(contour) > 100:  # 过滤小面积噪点
+            x, y, w, h = cv2.boundingRect(contour)
+            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
+
+    # 显示原图、掩码和结果图像
+    cv2.imshow('Original', frame)
+    cv2.imshow('Mask', mask)
+    cv2.imshow('Result', result)
+
+    # 按'q'键退出循环
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+# 释放资源并关闭所有窗口
+cap.release()
+cv2.destroyAllWindows()
+