feat: YOLO vision 640x480 + 1s throttle, camera snapshot, Nav2 fast, explore tuning, autorun

.gitignore

@@ -13,5 +13,3 @@ __pycache__/
 *.pyc
 *.pyo
 
-# YOLO model (auto-downloaded on first run)
-yolov8n.pt

run_all.sh

@@ -1,6 +1,11 @@
 #!/usr/bin/env bash
 set -euo pipefail
-export PYTHONPATH="/workspace/.site-packages:$PYTHONPATH"
+# Link pip deps from EFS vendor if /workspace/.site-packages is missing
+if [[ ! -d "${ROOT}/.site-packages" && -d "/opt/vendor/yolov8" ]]; then
+  ln -sf /opt/vendor/yolov8 "${ROOT}/.site-packages"
+fi
+
+export PYTHONPATH="${ROOT}/.site-packages:$PYTHONPATH"
 export DISPLAY=:1
 
 # Auto-download YOLO model if not present

src/vision_yolo/vision_yolo/detector.py

@@ -5,34 +5,42 @@ from vision_msgs.msg import Detection2DArray, Detection2D, ObjectHypothesisWithP
 from cv_bridge import CvBridge
 from ultralytics import YOLO
 import cv2
+import time
 
 class YoloDetector(Node):
     def __init__(self):
-        super().__init__('yolo_detector')
+        super().__init__("yolo_detector")
         self.bridge = CvBridge()
-        self.get_logger().info('Loading YOLOv8n model...')
+        self.get_logger().info("Loading YOLOv8n model...")
-        self.model = YOLO('yolov8n.pt')
+        self.model = YOLO("yolov8n.pt")
-        self.get_logger().info('YOLOv8n model loaded')
+        self.get_logger().info("YOLOv8n model loaded")
 
         self.sub = self.create_subscription(
-            Image, '/camera/image_raw', self.on_image, 10)
+            Image, "/camera/image_raw", self.on_image, 10)
         self.pub = self.create_publisher(
-            Detection2DArray, '/vision/detections', 10)
+            Detection2DArray, "/vision/detections", 10)
         self.pub_vis = self.create_publisher(
-            Image, '/vision/image_annotated', 10)
+            Image, "/vision/image_annotated", 10)
 
-        self.get_logger().info('YOLO detector node started, subscribing to /camera/image_raw')
+        self.last_infer_time = 0.0
+        self.infer_interval = 1.0
+        self.get_logger().info("YOLO detector node started, subscribing to /camera/image_raw")
 
     def on_image(self, msg):
+        now = time.time()
+        if now - self.last_infer_time < self.infer_interval:
+            return
+        self.last_infer_time = now
+
         try:
-            cv_img = self.bridge.imgmsg_to_cv2(msg, 'bgr8')
+            cv_img = self.bridge.imgmsg_to_cv2(msg, "bgr8")
-            # CPU 降采样加速
+            cv_img = cv2.resize(cv_img, (640, 480))
-            cv_img = cv2.resize(cv_img, (320, 240))
+            cv2.imwrite("/workspace/camera_latest.jpg", cv_img)
         except Exception as e:
-            self.get_logger().error(f'cv_bridge failed: {e}')
+            self.get_logger().error(f"cv_bridge failed: {e}")
             return
 
-        results = self.model(cv_img, verbose=False, imgsz=320)
+        results = self.model(cv_img, verbose=False, imgsz=640)
         dets = Detection2DArray()
         dets.header = msg.header
 
@@ -41,7 +49,6 @@ class YoloDetector(Node):
                 cls_id = int(box.cls[0])
                 conf = float(box.conf[0])
                 label = self.model.names[cls_id]
-
                 x1, y1, x2, y2 = map(float, box.xyxy[0])
 
                 det = Detection2D()
@@ -58,14 +65,15 @@ class YoloDetector(Node):
                 dets.detections.append(det)
 
                 cv2.rectangle(cv_img, (int(x1), int(y1)), (int(x2), int(y2)), (0, 255, 0), 2)
-                cv2.putText(cv_img, f'{label} {conf:.2f}', (int(x1), int(y1) - 10),
+                cv2.putText(cv_img, f"{label} {conf:.2f}", (int(x1), int(y1) - 10),
                             cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
 
         self.pub.publish(dets)
         if dets.detections:
-            self.get_logger().info(f'Detected: {[d.results[0].hypothesis.class_id for d in dets.detections]}')
+            classes = [d.results[0].hypothesis.class_id for d in dets.detections]
+            self.get_logger().info(f"Detected: {classes}")
 
-        vis_msg = self.bridge.cv2_to_imgmsg(cv_img, 'bgr8')
+        vis_msg = self.bridge.cv2_to_imgmsg(cv_img, "bgr8")
         vis_msg.header = msg.header
         self.pub_vis.publish(vis_msg)
 
@@ -79,5 +87,5 @@ def main(args=None):
     node.destroy_node()
     rclpy.shutdown()
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()