How to use the pyrealsense2.disparity_transform function in pyrealsense2

To help you get started, we’ve selected a few pyrealsense2 examples, based on popular ways it is used in public projects.

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AoLyu / 3D-Object-Reconstruction-with-RealSense-D435 / MutiView3DReconstruction(paper) / interfaceVersion.py View on Github

while True:
        # Pt2 = []
        Point2 = o3d.geometry.PointCloud()

        frames = pipeline.wait_for_frames()
        aligned_frames = align.process(frames)

        color_frame = aligned_frames.get_color_frame()
        color_image = np.asanyarray(color_frame.get_data())
        depth_frame = aligned_frames.get_depth_frame()

        depth_frame = rs.decimation_filter(1).process(depth_frame)
        depth_frame = rs.disparity_transform(True).process(depth_frame)
        depth_frame = rs.spatial_filter().process(depth_frame)
        depth_frame = rs.temporal_filter().process(depth_frame)
        depth_frame = rs.disparity_transform(False).process(depth_frame)

        depth_image = np.asanyarray(depth_frame.get_data())
        color_image1 = cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR)

        xl,yl,rl = keyPoints.getCircles(color_image1)
        old_xyr = []
        currentImage = color_image1.copy()

        if i == 0:
            for ind,x in enumerate(xl):
                cv2.circle(currentImage, (xl[ind],yl[ind]), rl[ind], (0, 255, 0), -1)

        elif i == 1:
            a,b,c,d = keyPoints.calculatePlane(RealSense,depth_image,xl,yl,rl)
            TablePlane.getParam(a,b,c,d)
            print('calculating plane done!')

AoLyu / 3D-Object-Reconstruction-with-RealSense-D435 / Python / captureRGBDpt.py View on Github

i = 0

    try:
        while True:
            time_start = time.time()
            pointcloud.clear()

            frames = pipeline.wait_for_frames()
            aligned_frames = align.process(frames)

            color_frame = aligned_frames.get_color_frame()
            color_image = np.asanyarray(color_frame.get_data())
            depth_frame = aligned_frames.get_depth_frame()

            depth_frame = rs.decimation_filter(1).process(depth_frame)
            depth_frame = rs.disparity_transform(True).process(depth_frame)
            depth_frame = rs.spatial_filter().process(depth_frame)
            depth_frame = rs.temporal_filter().process(depth_frame)
            depth_frame = rs.disparity_transform(False).process(depth_frame)
            # depth_frame = rs.hole_filling_filter().process(depth_frame)
            

            depth_image = np.asanyarray(depth_frame.get_data())
            color_image1 = cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR)

            cv2.namedWindow('color image', cv2.WINDOW_AUTOSIZE)
            cv2.imshow('color image', cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR))
            cv2.namedWindow('depth image', cv2.WINDOW_AUTOSIZE)
            cv2.imshow('depth image', depth_image )

            depth = Image(depth_image)
            color = Image(color_image)

AoLyu / 3D-Object-Reconstruction-with-RealSense-D435 / Basic / recordBag.py View on Github

vis.register_key_callback(ord("Q"), breakLoop)
    vis.register_key_callback(ord("K"), change_background_color)

    try:
        while True:
            dt0 = time.time()
            frames = pipeline.wait_for_frames()
            aligned_frames = align.process(frames)
            color_frame = aligned_frames.get_color_frame()
            color_image = np.asanyarray(color_frame.get_data())
            depth_frame = aligned_frames.get_depth_frame()
            depth_frame = rs.decimation_filter(1).process(depth_frame)
            depth_frame = rs.disparity_transform(True).process(depth_frame)
            depth_frame = rs.spatial_filter().process(depth_frame)
            depth_frame = rs.temporal_filter().process(depth_frame)
            depth_frame = rs.disparity_transform(False).process(depth_frame)
            # depth_frame = rs.hole_filling_filter().process(depth_frame)

            depth_image = np.asanyarray(depth_frame.get_data())
            color_image1 = cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR)
            depth_color_frame = rs.colorizer().colorize(depth_frame)
            depth_color_image = np.asanyarray(depth_color_frame.get_data())

            cv2.imshow('Color Stream', color_image1)
            cv2.imshow('Depth Stream', depth_color_image )

            depth = o3d.geometry.Image(depth_image)
            color = o3d.geometry.Image(color_image)

            rgbd = o3d.geometry.RGBDImage.create_rgbd_image_from_color_and_depth(color, depth, convert_rgb_to_intensity = False)
            pcd = o3d.geometry.PointCloud.create_point_cloud_from_rgbd_image(rgbd, pinhole_camera_intrinsic)

thien94 / vision_to_mavros / scripts / opencv_depth_filtering.py View on Github

PRESET_FILE  = "../cfg/d4xx-default.json"

# List of filters to be applied, in this order.
# Depth Frame                       (input)
# &gt;&gt; Decimation Filter              (reduces depth frame density) 
# &gt;&gt; Threshold Filter               (removes values outside recommended range)
# &gt;&gt; Depth2Disparity Transform**    (transform the scene into disparity domain)
# &gt;&gt; Spatial Filter                 (edge-preserving spatial smoothing)
# &gt;&gt; Temporal Filter                (reduces temporal noise)
# &gt;&gt; Hole Filling Filter            (rectify missing data in the resulting image)
# &gt;&gt; Disparity2Depth Transform**    (revert the results back to depth)
# &gt;&gt; Filtered Depth                 (output)
filters = [
    [True, "Decimation Filter",     rs.decimation_filter()],
    [True, "Threshold Filter",      rs.threshold_filter()],
    [True, "Depth to Disparity",    rs.disparity_transform(True)],
    [True, "Spatial Filter",        rs.spatial_filter()],
    [True, "Temporal Filter",       rs.temporal_filter()],
    [True, "Hole Filling Filter",   rs.hole_filling_filter()],
    [True, "Disparity to Depth",    rs.disparity_transform(False)]
]

######################################################
##   Functions to change filtering options online   ##
##   Description for each option can be found at:   ##
## https://github.com/IntelRealSense/librealsense/blob/master/doc/post-processing-filters.md
######################################################
decimation_magnitude_min = 2
decimation_magnitude_max = 8
def on_trackbar_decimation(val):
    # Sanity check
    if val &lt; decimation_magnitude_min:

thien94 / vision_to_mavros / scripts / d4xx_to_mavlink.py View on Github

FPS         = 30               # Defines the rate of frames per second
DEPTH_RANGE = [0.1, 8.0]       # Replace with your sensor's specifics, in meter

USE_PRESET_FILE = True
PRESET_FILE  = "../cfg/d4xx-default.json"

# List of filters to be applied, in this order.
# https://github.com/IntelRealSense/librealsense/blob/master/doc/post-processing-filters.md
filters = [
    [True, "Decimation Filter",     rs.decimation_filter()],
    [True, "Threshold Filter",      rs.threshold_filter()],
    [True, "Depth to Disparity",    rs.disparity_transform(True)],
    [True, "Spatial Filter",        rs.spatial_filter()],
    [True, "Temporal Filter",       rs.temporal_filter()],
    [False, "Hole Filling Filter",   rs.hole_filling_filter()],
    [True, "Disparity to Depth",    rs.disparity_transform(False)]
]

######################################################
##  ArduPilot-related parameters - reconfigurable   ##
######################################################

# Default configurations for connection to the FCU
connection_string_default = '/dev/ttyUSB0'
connection_baudrate_default = 921600
connection_timeout_sec_default = 5

# Use this to rotate all processed data
camera_facing_angle_degree = 0

# Enable/disable each message/function individually
enable_msg_obstacle_distance = True

AoLyu / 3D-Object-Reconstruction-with-RealSense-D435 / Python / captureRGBDpt.py View on Github

while True:
            time_start = time.time()
            pointcloud.clear()

            frames = pipeline.wait_for_frames()
            aligned_frames = align.process(frames)

            color_frame = aligned_frames.get_color_frame()
            color_image = np.asanyarray(color_frame.get_data())
            depth_frame = aligned_frames.get_depth_frame()

            depth_frame = rs.decimation_filter(1).process(depth_frame)
            depth_frame = rs.disparity_transform(True).process(depth_frame)
            depth_frame = rs.spatial_filter().process(depth_frame)
            depth_frame = rs.temporal_filter().process(depth_frame)
            depth_frame = rs.disparity_transform(False).process(depth_frame)
            # depth_frame = rs.hole_filling_filter().process(depth_frame)
            

            depth_image = np.asanyarray(depth_frame.get_data())
            color_image1 = cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR)

            cv2.namedWindow('color image', cv2.WINDOW_AUTOSIZE)
            cv2.imshow('color image', cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR))
            cv2.namedWindow('depth image', cv2.WINDOW_AUTOSIZE)
            cv2.imshow('depth image', depth_image )

            depth = Image(depth_image)
            color = Image(color_image)

            rgbd = create_rgbd_image_from_color_and_depth(color, depth, convert_rgb_to_intensity = False)
            pcd = create_point_cloud_from_rgbd_image(rgbd, pinhole_camera_intrinsic)

AoLyu / 3D-Object-Reconstruction-with-RealSense-D435 / Python / recordBag.py View on Github

pointcloud = PointCloud()
    i = 0

    try:
        while True:
            dt0 = datetime.now()
            frames = pipeline.wait_for_frames()
            aligned_frames = align.process(frames)
            color_frame = aligned_frames.get_color_frame()
            color_image = np.asanyarray(color_frame.get_data())
            depth_frame = aligned_frames.get_depth_frame()
            depth_frame = rs.decimation_filter(1).process(depth_frame)
            depth_frame = rs.disparity_transform(True).process(depth_frame)
            depth_frame = rs.spatial_filter().process(depth_frame)
            depth_frame = rs.temporal_filter().process(depth_frame)
            depth_frame = rs.disparity_transform(False).process(depth_frame)
            # depth_frame = rs.hole_filling_filter().process(depth_frame)

            depth_image = np.asanyarray(depth_frame.get_data())
            color_image1 = cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR)
            depth_color_frame = rs.colorizer().colorize(depth_frame)
            depth_color_image = np.asanyarray(depth_color_frame.get_data())

            cv2.imshow('Color Stream', color_image1)
            cv2.imshow('Depth Stream', depth_color_image )

            depth = Image(depth_image)
            color = Image(color_image)

            rgbd = create_rgbd_image_from_color_and_depth(color, depth, convert_rgb_to_intensity = False)
            pcd = create_point_cloud_from_rgbd_image(rgbd, pinhole_camera_intrinsic)

AoLyu / 3D-Object-Reconstruction-with-RealSense-D435 / capt_pt.py View on Github

pointcloud = PointCloud()
    i = 0

    while True:
        dt0 = datetime.now()
        pointcloud.clear()

        frames = pipeline.wait_for_frames()
        aligned_frames = align.process(frames)

        color_frame = aligned_frames.get_color_frame()
        color_image = np.asanyarray(color_frame.get_data())
        depth_frame = aligned_frames.get_depth_frame()

        depth_frame = rs.decimation_filter(1).process(depth_frame)
        depth_frame = rs.disparity_transform(True).process(depth_frame)
        depth_frame = rs.spatial_filter().process(depth_frame)
        depth_frame = rs.temporal_filter().process(depth_frame)
        depth_frame = rs.disparity_transform(False).process(depth_frame)
        # depth_frame = rs.hole_filling_filter().process(depth_frame)
        

        depth_image = np.asanyarray(depth_frame.get_data())
        color_image1 = cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR)

        cv2.namedWindow('color image', cv2.WINDOW_AUTOSIZE)
        cv2.imshow('color image', cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR))
        cv2.namedWindow('depth image', cv2.WINDOW_AUTOSIZE)
        cv2.imshow('depth image', depth_image )

        depth = Image(depth_image)
        color = Image(color_image)

AoLyu / 3D-Object-Reconstruction-with-RealSense-D435 / ObjectRecognitionUsingPointNet / client.py View on Github

z_min = None
    z_max = None
    x_min = None
    x_max = None

    while True:
        dt0 = datetime.now()
        frames = pipeline.wait_for_frames()
        aligned_frames = align.process(frames)

        color_frame = aligned_frames.get_color_frame()
        color_image = np.asanyarray(color_frame.get_data())
        depth_frame = aligned_frames.get_depth_frame()

        depth_frame = rs.decimation_filter(1).process(depth_frame)
        depth_frame = rs.disparity_transform(True).process(depth_frame)
        depth_frame = rs.spatial_filter().process(depth_frame)
        depth_frame = rs.temporal_filter().process(depth_frame)
        depth_frame = rs.disparity_transform(False).process(depth_frame)
        # depth_frame = rs.hole_filling_filter().process(depth_frame)


        depth_image = np.asanyarray(depth_frame.get_data())
        color_image1 = cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR)


        if plane_flag == 0:
            chessboard_found1, corners1 = cv2.findChessboardCorners(color_image1, (9, 6))
            corners = np.asanyarray(corners1).squeeze()
            if chessboard_found1:
                # cv2.drawChessboardCorners(color_image1,(9,6),corners1,chessboard_found1)
                Points = []

How to use the pyrealsense2.disparity_transform function in pyrealsense2

To help you get started, we’ve selected a few pyrealsense2 examples, based on popular ways it is used in public projects.

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