add prompt; ggb process script

template/agent_prompt.py

@@ -85,6 +85,8 @@ Tips for you to finish task in the most efficient way:
 4. Getting entities nearby do not always effective. You have only limited sensor range. Using /targets API to get targets and /obstacles API to get obstacles is more effective.
 5. If battery is below 30, find the nerest waypoint, go there and land, then charge to 100.
 6. Reaching to a higher latitude can help you see targets, but do not exceed the drone's limit.
+7. We put your answer to langchain, so if you want to return {{ or }}, return double of the characters.
+8. Cannot move from current status: DroneStatus.IDLE means you need to take off first then move.
 
 Begin!
 

template/maps/process.py

@@ -0,0 +1,76 @@
+import cv2
+import numpy as np
+
+def extract_green_polygons(image_path):
+    # 1. 读取图片
+    img = cv2.imread(image_path)
+    if img is None:
+        print("无法读取图片")
+        return []
+
+    # 获取图片尺寸
+    height, width = img.shape[:2]
+    
+    # 定义目标坐标系范围
+    target_w, target_h = 1465, 715
+
+    # 2. 转换颜色空间到 HSV 以便提取绿色
+    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+
+    # 定义绿色的 HSV 范围
+    lower_green = np.array([35, 20, 200]) 
+    upper_green = np.array([85, 255, 255])
+
+    # 3. 创建掩膜 (Mask)
+    mask = cv2.inRange(hsv, lower_green, upper_green)
+
+    # 4. 图像形态学处理
+    kernel = np.ones((3,3), np.uint8)
+    mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
+    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
+
+    # 5. 查找轮廓
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    polygons = []
+
+    for i, contour in enumerate(contours):
+        # 过滤掉太小的区域
+        if cv2.contourArea(contour) < 100: 
+            continue
+
+        points = []
+        # 6. 坐标转换
+        for point in contour:
+            px, py = point[0]
+            
+            # 【修改点1】：这里显式转换成 float()，去除 numpy 类型包裹
+            # X 轴转换: 线性缩放
+            new_x = float((px / width) * target_w)
+            
+            # Y 轴转换: 图像坐标系 -> 笛卡尔坐标系
+            new_y = float(((height - py) / height) * target_h)
+            
+            # 保留两位小数
+            points.append((round(new_x, 2), round(new_y, 2)))
+        
+        polygons.append({
+            "id": i,
+            "vertex_count": len(points),
+            "coordinates": points
+        })
+
+    return polygons
+
+# --- 使用说明 ---
+results = extract_green_polygons("golden_gate_bridge.png")
+
+if not results:
+    print("未找到多边形或图片读取失败")
+else:
+    for poly in results:
+        print(f"--- 多边形 ID: {poly['id']} (顶点数: {poly['vertex_count']}) ---")
+        # 【修改点2】：遍历坐标列表，每行输出两个数字 (x y)
+        for x, y in poly['coordinates']:
+            print(f"{x}, {y}")
+        print("") # 每个多边形之间空一行，方便区分