上傳檔案到 ''

l515_distance.py

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+import pyrealsense2 as rs
+import numpy as np
+import cv2
+import supervision as sv
+from ultralytics import YOLO
+import time
+
+# 啟動 RealSense 相機
+pipeline = rs.pipeline()
+config = rs.config()
+config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
+config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)
+pipeline.start(config)
+# profile = config.resolve(pipeline)
+# # Declare sensor object and set options
+# depth_sensor = profile.get_device().first_depth_sensor()
+# depth_sensor.set_option(rs.option.visual_preset, 5) # 5 is short range, 3 is low ambient light
+
+# 初始化 YOLO 模型
+model = YOLO('yolov8n-seg.pt')
+byte_tracker = sv.ByteTrack()
+
+align_to = rs.stream.color
+align = rs.align(align_to)
+
+try:
+    while True:
+        # 讀取 RealSense 相機影像
+        frames = pipeline.wait_for_frames()
+        aligned_frames = align.process(frames)
+        depth_frame = aligned_frames.get_depth_frame()
+        color_frame = aligned_frames.get_color_frame()
+
+        if not depth_frame or not color_frame:
+            continue
+
+        depth_image = np.asanyarray(depth_frame.get_data())
+        color_image = np.asanyarray(color_frame.get_data())
+        depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_WINTER)
+
+        # 進行物體檢測
+        result = model(color_image)[0]
+        detections = sv.Detections.from_ultralytics(result)
+        detections_tracker = byte_tracker.update_with_detections(detections=detections)
+
+        polygon_annotator = sv.PolygonAnnotator()
+        annotated_frame = polygon_annotator.annotate(
+            scene=color_image.copy(), detections=detections)
+
+        mask_annotator = sv.MaskAnnotator()
+        annotated_frame = mask_annotator.annotate(
+            scene=annotated_frame, detections=detections
+        )
+
+        labels = [
+            f"#{tracker_id} {result.names[class_id]} {confidence:.2f}"
+            for class_id, tracker_id, confidence
+            in zip(detections_tracker.class_id, detections_tracker.tracker_id, detections_tracker.confidence)
+        ]
+
+        label_annotator = sv.LabelAnnotator()
+        annotated_frame = label_annotator.annotate(
+            scene=annotated_frame,
+            detections=detections_tracker,
+            labels=labels
+        )
+
+        if detections:
+            position = sv.Position.CENTER_OF_MASS
+            xy = detections.get_anchors_coordinates(anchor=position)
+            #print('postion',xy)
+            for detection_idx in range(len(detections)):
+                #print(xy)
+                center = (int(xy[detection_idx,0]), int(xy[detection_idx,1]))
+                cv2.circle(annotated_frame, center,radius=3, color=(255,255,0), thickness=-1)
+                #print(center[0],center[1])
+
+                # 在畫面上顯示距離信息和檢測結果
+                text_depth = "Depth value at ({x},{y}): {:.2f} meters".format(
+                    depth_frame.get_distance(int(xy[detection_idx,0]), int(xy[detection_idx,1])),x = int(xy[detection_idx,0]),y=int(xy[detection_idx,1]))
+                annotated_frame = cv2.putText(annotated_frame, text_depth, (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.8,
+                                              (0, 0, 255), 2)
+                print("距離:",depth_frame.get_distance(int(xy[detection_idx,0]), int(xy[detection_idx,1])))
+
+                #annotated_frame = cv2.circle(annotated_frame, (320, 240), 4, (0, 0, 255), -1)
+
+        annotated_frame = np.hstack((annotated_frame, depth_colormap))
+
+        # 顯示畫面
+        cv2.imshow('RealSense', annotated_frame)
+
+        key = cv2.waitKey(1)
+        if key & 0xFF == ord('q') or key == 27:
+            cv2.destroyAllWindows()
+            break
+
+finally:
+    pipeline.stop()