import pyrealsense2 as rs

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.rgb8, 30)
pipeline.start(config)

time.sleep(1)
frames = pipeline.wait_for_frames()
# time.sleep(3)
depth_frame = frames.get_depth_frame()
color_frame = frames.get_color_frame()

    # Convert images to numpy arrays
depth_image = np.asanyarray(depth_frame.get_data())
color_image = np.asanyarray(color_frame.get_data())

# # Apply colormap on depth image (image must be converted to 8-bit per pixel first)
# depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
#
# # Stack both images horizontally
# images = np.hstack((color_image, depth_colormap))
#
# # Show images
# cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)
# cv2.imshow('RealSense', images)
# cv2.waitKey(1)

fig, axes = plt.subplots(1, 2)
for ax, im in zip(axes, [color_image, depth_image]):
    ax.imshow(im)
    ax.axis('off')
plt.show()
pipeline.stop()

import pyrealsense2 as rs

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.rgb8, 30)
pipeline.start(config)

time.sleep(1)
frames = pipeline.wait_for_frames()
# time.sleep(3)
depth_frame = frames.get_depth_frame()
color_frame = frames.get_color_frame()

    # Convert images to numpy arrays
depth_image = np.asanyarray(depth_frame.get_data())
color_image = np.asanyarray(color_frame.get_data())

# # Apply colormap on depth image (image must be converted to 8-bit per pixel first)
# depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
#
# # Stack both images horizontally
# images = np.hstack((color_image, depth_colormap))
#
# # Show images
# cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)
# cv2.imshow('RealSense', images)
# cv2.waitKey(1)

fig, axes = plt.subplots(1, 2)
for ax, im in zip(axes, [color_image, depth_image]):
    ax.imshow(im)
    ax.axis('off')
plt.show()
pipeline.stop()

# time.sleep(3) # Convert images to numpy arrays # # Apply colormap on depth image (image must be converted to 8-bit per pixel first) # depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET) # # # Stack both images horizontally # images = np.hstack((color_image, depth_colormap)) # # # Show images # cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE) # cv2.imshow('RealSense', images) # cv2.waitKey(1)