def colorStream(self, pathDir:str):
color_stream = self.dev.create_color_stream()
color_stream.start()
color_stream.set_video_mode( c_api.OniVideoMode(pixelFormat = c_api.OniPixelFormat.ONI_PIXEL_FORMAT_RGB888, resolutionX = 640,
resolutionY = 480, fps = 30))
while True:
frame = color_stream.read_frame()
frame_data = frame.get_buffer_as_uint8()
img = np.frombuffer(frame_data, dtype=np.uint8)
img.shape = (307200, 3)
b = img[:, 0].reshape(480, 640)
g = img[:, 1].reshape(480, 640)
r = img[:, 2].reshape(480, 640)
rgb = (r[..., np.newaxis], g[..., np.newaxis], b[..., np.newaxis])
img = np.concatenate(rgb, axis=-1)
cv2.imshow("Color Image", img)
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
if key == ord("c"):
filename = pathDir + str(datetime.datetime.now()) + ".png"
cv2.imwrite(filename, img)
openni2.unload()
cv2.destroyAllWindows()
def __init__(self):
######### Register the device##################
openni2.initialize()
self.dev = openni2.Device.open_any()
########## create the streams ###########
#self.rgb_stream = self.dev.create_color_stream()
self.depth_stream = self.dev.create_depth_stream()
#self.color_stream = self.dev.create_color_stream()
self.dev.set_depth_color_sync_enabled(True) # synchronize the streams
self.dev.set_image_registration_mode(
openni2.IMAGE_REGISTRATION_DEPTH_TO_COLOR)
self.depth_stram = self.depth_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_1_MM,
resolutionX=640,
resolutionY=400,
fps=30))
# self.depth_stram = self.depth_stream.set_video_mode(c_api.OniVideoMode(pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_100_UM, resolutionX=640, resolutionY=480,fps=30))
#self.color_stream = self.color_stream.set_video_mode(c_api.OniVideoMode(pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_RGB888,resolutionX=640,resolutionY=480,fps=30))
######### strat the stream #############
self.depth_stream.start()
#self.rgb_stream.start()
###########################################
################Mouth###############
self.predictor = predictor_path = '/home/odroid/feeding20190221_Hui/shape_predictor_68_face_landmarks.dat' #Register land marks
self.detector = dlib.get_frontal_face_detector(
) # detector will get the frontal face
self.predictor = dlib.shape_predictor(
predictor_path) #Register land marks
self.mouth_status = 0
def depthStream(self):
depth_stream = self.dev.create_depth_stream()
depth_stream.start()
depth_stream.set_video_mode( c_api.OniVideoMode(pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_100_UM,
resolutionX=640, resolutionY=480, fps=30))
while True:
# Grab a new depth frame
frame = depth_stream.read_frame()
frame_data = frame.get_buffer_as_uint16()
# Put the depth frame into a numpy array and reshape it
img = np.frombuffer(frame_data, dtype=np.uint16)
img.shape = (1, 480, 640)
img = np.concatenate((img, img, img), axis=0)
img = np.swapaxes(img, 0, 2)
img = np.swapaxes(img, 0, 1)
# Display the reshaped depth frame using OpenCV
cv2.imshow("Depth Image", img)
key = cv2.waitKey(1) & 0xFF
# If the 'c' key is pressed, break the while loop
if key == ord("q"):
break
# Close all windows and unload the depth device
openni2.unload()
cv2.destroyAllWindows()
def __init__(self, cam_id="rtsp://admin:@192.168.52.52/h265/main/av_stream"):
self._cam_id = 0 # cam_id
self._fps = 30
try:
self._cap = cv2.VideoCapture(self._cam_id)
self._cap.set(cv2.CAP_PROP_FPS, self._fps)
self._height = self._cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
self._width = self._cap.get(cv2.CAP_PROP_FRAME_WIDTH)
self._cap.set(cv2.CAP_PROP_BRIGHTNESS, 0)
print self._cap.get(cv2.CAP_PROP_BRIGHTNESS)
print self._cap.set(cv2.CAP_PROP_BACKLIGHT, -64)
openni2.initialize()
self.device = openni2.Device.open_any()
print 'initialized'
self.depth_stream = self.device.create_depth_stream()
self.depth_stream.set_mirroring_enabled(False)
self.corlor_stream = self.device.create_color_stream()
self.corlor_stream.set_mirroring_enabled(False)
self.device.set_depth_color_sync_enabled(True)
self.depth_stream.start()
self.corlor_stream.start()
self.depth_stream.set_video_mode(c_api.OniVideoMode(pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_1_MM, resolutionX=640, resolutionY=480, fps=self._fps))
# self.corlor_stream.set_video_mode(c_api.OniVideoMode(pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_100_UM, resolutionX=640, resolutionY=480, fps=1))
except Exception as e:
print e
def __init__(self, debug=False):
self.debug = debug
self._scale_depth = True
self._scale_rgb_colors = False
openni2.initialize("/usr/lib")
dev = openni2.Device.open_any()
if debug:
print(dev.get_device_info())
dev.set_image_registration_mode(True)
dev.set_depth_color_sync_enabled(True)
# create depth stream
self.depth_stream = dev.create_depth_stream()
self.depth_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_1_MM,
resolutionX=Depth_ResX,
resolutionY=Depth_ResY,
fps=Depth_fps,
))
depth_sensor_info = self.depth_stream.get_sensor_info()
self.max_depth = self.depth_stream.get_max_pixel_value()
self.min_depth = 0
if self.debug:
for itm in depth_sensor_info.videoModes:
print(itm)
print("Min depth value: {}".format(self.min_depth))
print("Max depth value: {}".format(self.max_depth))
self.rgb_stream = dev.create_color_stream()
self.rgb_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_RGB888,
resolutionX=RGB_ResX,
resolutionY=RGB_ResY,
fps=RGB_fps,
))
if self.debug:
rgb_sensor_info = self.rgb_stream.get_sensor_info()
for itm in rgb_sensor_info.videoModes:
print(itm)
def main(args):
device = getOrbbec()
# 创建深度流
depth_stream = device.create_depth_stream()
depth_stream.set_mirroring_enabled(args.mirroring)
depth_stream.set_video_mode(
c_api.OniVideoMode(
resolutionX=args.width,
resolutionY=args.height,
fps=args.fps,
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_1_MM))
# 获取uvc
cap = cv2.VideoCapture(0)
# 设置 镜像 帧同步
device.set_image_registration_mode(True)
device.set_depth_color_sync_enabled(True)
depth_stream.start()
while True:
# 读取帧
frame_depth = depth_stream.read_frame()
frame_depth_data = frame_depth.get_buffer_as_uint16()
# 读取帧的深度信息 depth_array 也是可以用在后端处理的 numpy格式的
depth_array = np.ndarray((frame_depth.height, frame_depth.width),
dtype=np.uint16,
buffer=frame_depth_data)
# 变换格式用于 opencv 显示
depth_uint8 = 1 - 250 / (depth_array)
depth_uint8[depth_uint8 > 1] = 1
depth_uint8[depth_uint8 < 0] = 0
cv2.imshow('depth', depth_uint8)
# 读取 彩色图
_, color_array = cap.read()
cv2.imshow('color', color_array)
# 对彩色图 color_array 做处理
# 对深度图 depth_array 做处理
# 键盘监听
if cv2.waitKey(1) == ord('q'):
# 关闭窗口 和 相机
depth_stream.stop()
cap.release()
cv2.destroyAllWindows()
break
# 检测设备是否关闭（没什么用）
try:
openni2.unload()
print("Device unloaded \n")
except Exception as ex:
print("Device not unloaded: ", ex, "\n")
def initialize_color_stream(self):
self.color_stream = self.dev.create_color_stream()
self.color_stream.start()
self.color_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_RGB888,
resolutionX=640,
resolutionY=480,
fps=30))
if self.noMirror:
self.color_stream.set_mirroring_enabled(False)
def initialize_depth_stream(self):
self.depth_stream = self.dev.create_depth_stream()
self.depth_stream.start()
self.depth_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_100_UM,
resolutionX=640,
resolutionY=480,
fps=30))
if self.noMirror:
self.depth_stream.set_mirroring_enabled(False)
self.dev.set_image_registration_mode(
openni2.IMAGE_REGISTRATION_DEPTH_TO_COLOR)
def _start_depth_stream(self) -> openni2.VideoStream:
if self.dev is not None:
depth_stream = self.dev.create_depth_stream()
else:
raise Exception("Initialize AstraCamera using with statement.")
if depth_stream is None:
raise Exception("Current device has not a depth sensor.")
depth_stream.start()
depth_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_100_UM,
resolutionX=PROPERTIES["width"],
resolutionY=PROPERTIES["height"],
fps=PROPERTIES["fps"],
))
depth_stream.set_mirroring_enabled(False)
depth_stream.start()
self.depth_stream = depth_stream
return depth_stream
import numpy as np import cv2 import sys from openni import openni2 from openni import _openni2 as c_api # Initialize the depth device openni2.initialize() dev = openni2.Device.open_any() # Start the depth stream depth_stream = dev.create_depth_stream() depth_stream.start() depth_stream.set_video_mode(c_api.OniVideoMode(pixelFormat = c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_100_UM, resolutionX = 640, resolutionY = 480, fps = 30)) # Start the color stream color_stream = dev.create_color_stream() color_stream.start() color_stream.set_video_mode(c_api.OniVideoMode(pixelFormat = c_api.OniPixelFormat.ONI_PIXEL_FORMAT_RGB888, resolutionX = 640, resolutionY = 480, fps = 30)) #undistorted = Frame(640, 480, 4) #registered = Frame(640, 480, 4) #QT app app = QtGui.QApplication([]) w = gl.GLViewWidget() w.show() g = gl.GLGridItem() w.addItem(g)
def main():
# Init openni
openni_dir = "../OpenNI_2.3.0.55/Linux/OpenNI-Linux-x64-2.3.0.55/Redist"
openni2.initialize(openni_dir)
# Open astra color stream (using opencv)
color_capture = cv.VideoCapture(2)
color_capture.set(cv.CAP_PROP_FPS, 5)
# Open astra depth stream (using openni)
depth_device = openni2.Device.open_any()
depth_stream = depth_device.create_depth_stream()
depth_stream.start()
depth_stream.set_video_mode(
_openni2.OniVideoMode(
pixelFormat=_openni2.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_1_MM,
resolutionX=640,
resolutionY=480,
fps=5))
depth_device.set_image_registration_mode(
openni2.IMAGE_REGISTRATION_DEPTH_TO_COLOR)
# Create pointcloud visualizer
visualizer = open3d.visualization.Visualizer()
visualizer.create_window("Pointcloud", width=1000, height=700)
# Camera intrinsics of the astra pro
astra_camera_intrinsics = open3d.camera.PinholeCameraIntrinsic(width=640,
height=480,
fx=585,
fy=585,
cx=320,
cy=250)
# Create initial pointcloud
pointcloud = open3d.geometry.PointCloud()
visualizer.add_geometry(pointcloud)
first = True
prev_timestamp = 0
num_stored = 0
while True:
rgbd = get_rgbd(color_capture, depth_stream)
# Convert images to pointcloud
new_pointcloud = open3d.geometry.PointCloud.create_from_rgbd_image(
rgbd,
intrinsic=astra_camera_intrinsics,
)
# Flip pointcloud
new_pointcloud.transform([[1, 0, 0, 0], [0, -1, 0, 0], [0, 0, -1, 0],
[0, 0, 0, 1]])
# Set rendered pointcloud to recorded pointcloud
pointcloud.points = new_pointcloud.points
pointcloud.colors = new_pointcloud.colors
# Save pointcloud each n seconds
if SAVE_POINTCLOUDS and time.time() > prev_timestamp + 5:
filename = "pointcloud-%r.pcd" % num_stored
open3d.io.write_point_cloud(filename, new_pointcloud)
num_stored += 1
print("Stored: %s" % filename)
prev_timestamp = time.time()
# Reset viewpoint in first frame to look at the scene correctly
# (e.g. correct bounding box, direction, distance, etc.)
if first:
visualizer.reset_view_point(True)
first = False
# Update visualizer
visualizer.update_geometry()
visualizer.poll_events()
visualizer.update_renderer()
self.vtkPolyData.SetVerts(self.vtkCells)
self.vtkPolyData.GetPointData().SetScalars(self.vtkDepth)
self.vtkPolyData.GetPointData().SetActiveScalars('DepthArray')
# Initialize the depth device
openni2.initialize()
dev = openni2.Device.open_any()
# Start the depth stream
depth_stream = dev.create_depth_stream()
depth_stream.start()
depth_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_100_UM,
resolutionX=640,
resolutionY=480,
fps=30))
# Start the color stream
color_stream = dev.create_color_stream()
color_stream.start()
color_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_RGB888,
resolutionX=640,
resolutionY=480,
fps=30))
# Function to return some pixel information when the OpenCV window is clicked
refPt = []
def write_files(dev):
if debug:
import cv2
import numpy as np
depth_stream = dev.create_depth_stream()
color_stream = dev.create_color_stream()
depth_stream.set_mirroring_enabled(mirroring)
color_stream.set_mirroring_enabled(mirroring)
depth_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_1_MM,
resolutionX=width,
resolutionY=height,
fps=fps))
color_stream.set_video_mode(
c_api.OniVideoMode(
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_RGB888,
resolutionX=width,
resolutionY=height,
fps=fps))
dev.set_image_registration_mode(True)
dev.set_depth_color_sync_enabled(True)
depth_stream.start()
color_stream.start()
actual_date = datetime.now().strftime("%Y%m%d-%H%M%S%f")[:-3]
rec = openni2.Recorder((actual_date + ".oni").encode('utf-8'))
rec.attach(depth_stream, compression)
rec.attach(color_stream, compression)
rec.start()
print("Recording started.. press ctrl+C to stop or wait " + str(length) +
" seconds..")
start = time.time()
depth_scale_factor = 0.05
depth_scale_beta_factor = 0
try:
while True:
if (time.time() - start) > length:
break
if debug:
frame_color = color_stream.read_frame()
frame_depth = depth_stream.read_frame()
frame_color_data = frame_color.get_buffer_as_uint8()
frame_depth_data = frame_depth.get_buffer_as_uint16()
color_array = np.ndarray(
(frame_color.height, frame_color.width, 3),
dtype=np.uint8,
buffer=frame_color_data)
color_array = cv2.cvtColor(color_array, cv2.COLOR_BGR2RGB)
depth_array = np.ndarray(
(frame_depth.height, frame_depth.width),
dtype=np.uint16,
buffer=frame_depth_data)
depth_uint8 = depth_array * depth_scale_factor + depth_scale_beta_factor
depth_uint8[depth_uint8 > 255] = 255
depth_uint8[depth_uint8 < 0] = 0
depth_uint8 = depth_uint8.astype('uint8')
cv2.imshow('depth', depth_uint8)
cv2.imshow('color', color_array)
cv2.waitKey(1)
except KeyboardInterrupt:
pass
cv2.destroyAllWindows()
rec.stop()
depth_stream.stop()
color_stream.stop()
def main(args):
'''HYPER PARAMETER'''
os.environ["CUDA_VISIBLE_DEVICES"] = args.gpu
'''MODEL LOADING 加载模型'''
MODEL = importlib.import_module(args.model) # 导入模型所在的模块
classifier = MODEL.get_model(args.num_joint * 3,
normal_channel=args.normal).cuda()
experiment_dir = Path('./log/regression/pointnet2_reg_msg')
checkpoint = torch.load(
str(experiment_dir) + '/checkpoints/best_model.pth')
classifier.load_state_dict(checkpoint['model_state_dict'])
classifier.eval()
try:
''' 加载摄像机 '''
device = getOrbbec()
# 创建深度流
depth_stream = device.create_depth_stream()
depth_stream.set_mirroring_enabled(args.mirroring)
depth_stream.set_video_mode(
c_api.OniVideoMode(
resolutionX=args.width,
resolutionY=args.height,
fps=args.fps,
pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_DEPTH_1_MM))
# 获取uvc
cap = cv2.VideoCapture(0)
# 设置 镜像 帧同步
device.set_image_registration_mode(True)
device.set_depth_color_sync_enabled(True)
depth_stream.start()
while True:
# 读取帧
frame_depth = depth_stream.read_frame()
frame_depth_data = frame_depth.get_buffer_as_uint16()
# 读取帧的深度信息 depth_array 也是可以用在后端处理的 numpy格式的
depth_array = np.ndarray((frame_depth.height, frame_depth.width),
dtype=np.uint16,
buffer=frame_depth_data)
# 变换格式用于 opencv 显示
depth_uint8 = 1 - 250 / (depth_array)
depth_uint8[depth_uint8 > 1] = 1
depth_uint8[depth_uint8 < 0] = 0
cv2.imshow('depth', depth_uint8)
# 读取 彩色图
_, color_array = cap.read()
cv2.imshow('color', color_array)
# 对彩色图 color_array 做处理
# 对深度图 depth_array 做处理
# 键盘监听
if cv2.waitKey(1) == ord('q'):
# 关闭窗口 和 相机
depth_stream.stop()
cap.release()
cv2.destroyAllWindows()
break
# 检测设备是否关闭（没什么用）
try:
openni2.unload()
print("Device unloaded \n")
except Exception as ex:
print("Device not unloaded: ", ex, "\n")
except:
# 读取 depth
depth_array = matplotlib.image.imread('test_depth_1.tif').astype(
np.float32)
# depth to UVD
cloud_point = depth2uvd(depth_array)
# 将点云归一化
cloud_point_normal, scale, centroid = pc_normalize(cloud_point)
cloud_point_normal = np.reshape(cloud_point_normal, (1, -1, 3))
cloud_point_normal = cloud_point_normal.transpose(0, 2, 1)
# 对归一化的点云做预测
cloud_point_normal = torch.from_numpy(cloud_point_normal).cuda()
pred, _ = classifier(cloud_point_normal)
# 对预测结果做还原
pred_reduction = pred.cpu().data.numpy()
pred_reduction = pred_reduction * np.tile(
scale, (args.num_joint * 3, 1)).transpose(1, 0)
pred_reduction = pred_reduction + np.tile(centroid,
(1, args.num_joint))
pred_reduction = np.reshape(pred_reduction, (-1, 3))
displayPoint2(cloud_point, pred_reduction, 'bear')
anchors_path = os.path.join(src_path, 'keras_yolo3', 'model_data',
'yolo_anchors.txt')
FLAGS = None
frame_cache = np.zeros((1, 240, 320))
temperature = np.array([0])
path = 'C:/Users/ELLAB_TEST/Python Projects/orbecc viewer/Orbecmini_321'
openni2.initialize("C:\Program Files\OpenNI-Windows-x64-2.3\Redist")
dev = openni2.Device.open_any()
depth_stream = dev.create_color_stream()
depth_stream.start()
depth_stream.set_video_mode(
c_api.OniVideoMode(pixelFormat=c_api.OniPixelFormat.ONI_PIXEL_FORMAT_YUYV,
resolutionX=640,
resolutionY=480,
fps=30))
cx = 0
cy = 0
if __name__ == '__main__':
# Delete all default flags
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument(
"--input_path",
type=str,
default=image_test_folder,