136 lines
4.8 KiB
Python
136 lines
4.8 KiB
Python
import pyrealsense2 as rs
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import numpy as np
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import cv2
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def init_realsense():
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"""
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初始化 RealSense 管道并返回 pipeline 和 align 对象
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"""
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pipeline = rs.pipeline()
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config = rs.config()
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config.enable_stream(rs.stream.depth, 848, 480, rs.format.z16, 30)
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config.enable_stream(rs.stream.color, 1280, 720, rs.format.bgr8, 30)
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profile = pipeline.start(config)
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align = rs.align(rs.stream.color)
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return pipeline, align
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def get_closest_red_point(pipeline, align, warmup=100):
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"""
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获取最近红色圆点的 3D 坐标。
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返回 (x, y, z) 或 None（如果没检测到）。
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"""
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# 丢掉前几帧，让相机稳定
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for _ in range(warmup):
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pipeline.wait_for_frames()
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frames = pipeline.wait_for_frames()
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aligned_frames = align.process(frames)
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depth_frame = aligned_frames.get_depth_frame()
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color_frame = aligned_frames.get_color_frame()
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if not depth_frame or not color_frame:
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return None
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depth_image = np.asanyarray(depth_frame.get_data())
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color_image = np.asanyarray(color_frame.get_data())
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depth_intrin = depth_frame.profile.as_video_stream_profile().intrinsics
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hsv = cv2.cvtColor(color_image, cv2.COLOR_BGR2HSV)
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lower_red1 = np.array([0, 100, 100])
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upper_red1 = np.array([10, 255, 255])
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lower_red2 = np.array([160, 100, 100])
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upper_red2 = np.array([179, 255, 255])
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mask1 = cv2.inRange(hsv, lower_red1, upper_red1)
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mask2 = cv2.inRange(hsv, lower_red2, upper_red2)
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mask = cv2.bitwise_or(mask1, mask2)
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mask_blur = cv2.GaussianBlur(mask, (9, 9), 2)
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circles = cv2.HoughCircles(mask_blur, cv2.HOUGH_GRADIENT, dp=1.2, minDist=20,
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param1=50, param2=15, minRadius=5, maxRadius=50)
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closest_point = None
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min_depth = float('inf')
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if circles is not None:
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circles = np.uint16(np.around(circles))
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for i in circles[0, :]:
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u, v, r = i
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depth = depth_frame.get_distance(u, v)
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if 0 < depth < min_depth:
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min_depth = depth
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closest_point = rs.rs2_deproject_pixel_to_point(depth_intrin, [u, v], depth)
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return closest_point
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def show_frames(pipeline, align):
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"""
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显示 RGB 和 Depth 图像，同时标记最近红点（实时窗口）。
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按 'q' 退出。
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"""
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while True:
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frames = pipeline.wait_for_frames()
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aligned_frames = align.process(frames)
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depth_frame = aligned_frames.get_depth_frame()
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color_frame = aligned_frames.get_color_frame()
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if not depth_frame or not color_frame:
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continue
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depth_image = np.asanyarray(depth_frame.get_data())
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color_image = np.asanyarray(color_frame.get_data())
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depth_intrin = depth_frame.profile.as_video_stream_profile().intrinsics
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hsv = cv2.cvtColor(color_image, cv2.COLOR_BGR2HSV)
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lower_red1 = np.array([0, 100, 100])
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upper_red1 = np.array([10, 255, 255])
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lower_red2 = np.array([160, 100, 100])
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upper_red2 = np.array([179, 255, 255])
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mask1 = cv2.inRange(hsv, lower_red1, upper_red1)
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mask2 = cv2.inRange(hsv, lower_red2, upper_red2)
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mask = cv2.bitwise_or(mask1, mask2)
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mask_blur = cv2.GaussianBlur(mask, (9, 9), 2)
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circles = cv2.HoughCircles(mask_blur, cv2.HOUGH_GRADIENT, dp=1.2, minDist=20,
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param1=50, param2=15, minRadius=5, maxRadius=50)
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closest_point = None
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closest_pixel = None
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closest_radius = 0
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min_depth = float('inf')
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if circles is not None:
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circles = np.uint16(np.around(circles))
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for i in circles[0, :]:
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u, v, r = i
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depth = depth_frame.get_distance(u, v)
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if 0 < depth < min_depth:
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min_depth = depth
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closest_point = rs.rs2_deproject_pixel_to_point(depth_intrin, [u, v], depth)
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closest_pixel = (u, v)
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closest_radius = r
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if closest_point is not None:
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cv2.circle(color_image, closest_pixel, closest_radius, (0, 255, 0), 2)
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cv2.circle(color_image, closest_pixel, 2, (255, 0, 0), 3)
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cv2.imshow("RGB Image with Closest Red Circle", color_image)
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depth_colormap = cv2.convertScaleAbs(depth_image, alpha=0.03)
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depth_colormap = cv2.applyColorMap(depth_colormap, cv2.COLORMAP_JET)
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cv2.imshow("Depth Image", depth_colormap)
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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if __name__ == "__main__":
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pipeline, align = init_realsense()
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try:
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# 调用获取最近红点
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point_3d = get_closest_red_point(pipeline, align)
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print("Closest red 3D point:", point_3d)
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# 调用显示函数（实时窗口显示）
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show_frames(pipeline, align)
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finally:
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pipeline.stop()
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cv2.destroyAllWindows()
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