RealSense OpenCV 深度图像太暗
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【中文标题】RealSense OpenCV 深度图像太暗【英文标题】:RealSense OpenCV Depth Image Too Dark 【发布时间】:2017-02-21 00:25:25 【问题描述】:伙计们,
我有一个 realsense SR300,但是当我在 opencv 窗口中显示我的深度图像时,它看起来太暗了。我怎样才能解决这个问题?当我运行 realsense 示例时,图像看起来不错,但示例使用 OpenGL。但我的项目需要 OpenCV。这是我的代码:
int main(int argc, char ** argv)
// realsense camera setup
rs::log_to_console(rs::log_severity::warn);
// Create a context object. This object owns the handles to all connected realsense devices
rs::context ctx;
if (ctx.get_device_count() == 0)
throw std::runtime_error("No device detected. Is it plugged in?");
// Access the first available RealSense device
rs::device * dev = ctx.get_device(0);
// Configure depth to run at VGA resolution at 30 frames per second
dev->enable_stream(rs::stream::depth, 640, 480, rs::format::z16, 30);
rs::intrinsics depth_intrin;
rs::format depth_format;
depth_intrin = dev->get_stream_intrinsics(rs::stream::depth);
depth_format = dev->get_stream_format(rs::stream::depth);
cv::namedWindow("Send Display Image", CV_WINDOW_AUTOSIZE);
/* Set callbacks prior to calling start(). */
auto depth_callback = [depth_intrin, depth_format](rs::frame f)
cv::Mat image(cv::Size(640, 480), CV_16UC1,
(void*)f.get_data(), cv::Mat::AUTO_STEP);
cv::imshow("Send Display Image", image);
cv::waitKey(1000/80);
;
/* callback to grab depth fream and publish it. */
dev->set_frame_callback(rs::stream::depth, depth_callback);
// Start streaming
dev->start();
While(1)
return 0;
我不知道为什么我的图像这么暗。当我从 ROS 运行 openni_launch 时,我希望它看起来像 kinect 或 Xtion
【问题讨论】:
【参考方案1】:编辑:
下面的归一化函数会产生一些闪烁:
我怀疑这是由于最大深度值闪烁。 最小深度值始终为0
,因为当深度无效并因此深度范围变为假时使用此值。
你应该使用这个:
void make_depth_histogram(const Mat &depth, Mat &normalized_depth)
normalized_depth = Mat(depth.size(), CV_8U);
int width = depth.cols, height = depth.rows;
static uint32_t histogram[0x10000];
memset(histogram, 0, sizeof(histogram));
for(int i = 0; i < height; ++i)
for (int j = 0; j < width; ++j)
++histogram[depth.at<ushort>(i,j)];
for(int i = 2; i < 0x10000; ++i) histogram[i] += histogram[i-1]; // Build a cumulative histogram for the indices in [1,0xFFFF]
for(int i = 0; i < height; ++i)
for (int j = 0; j < width; ++j)
if (uint16_t d = depth.at<ushort>(i,j))
int f = histogram[d] * 255 / histogram[0xFFFF]; // 0-255 based on histogram location
normalized_depth.at<uchar>(i,j) = static_cast<uchar>(f);
else
normalized_depth.at<uchar>(i,j) = 0;
您观察到的是因为深度流被编码为 16 位 (rs::stream::z16
),而显示时仅使用 8 位。
你可以标准化你的深度图:
double min, max;
minMaxLoc(depth, &min, &max);
Mat depth_normalized;
double alpha = 255.0/(max-min);
depth.convertTo(depth_normalized, CV_8U, alpha, -min*alpha);
或者使用一种颜色图来显示深度:make_depth_histogram()
。
完整的演示代码:
inline void make_depth_histogram(const Mat &depth, Mat &color_depth)
color_depth = Mat(depth.size(), CV_8UC3);
int width = depth.cols, height = depth.rows;
static uint32_t histogram[0x10000];
memset(histogram, 0, sizeof(histogram));
for(int i = 0; i < height; ++i)
for (int j = 0; j < width; ++j)
++histogram[depth.at<ushort>(i,j)];
for(int i = 2; i < 0x10000; ++i) histogram[i] += histogram[i-1]; // Build a cumulative histogram for the indices in [1,0xFFFF]
for(int i = 0; i < height; ++i)
for (int j = 0; j < width; ++j)
if (uint16_t d = depth.at<ushort>(i,j))
int f = histogram[d] * 255 / histogram[0xFFFF]; // 0-255 based on histogram location
color_depth.at<Vec3b>(i,j) = Vec3b(f, 0, 255 - f);
else
color_depth.at<Vec3b>(i,j) = Vec3b(0, 5, 20);
int main(int argc, char *argv[])
// Create a context object. This object owns the handles to all connected realsense devices
rs::context ctx;
// Access the first available RealSense device
rs::device * dev = ctx.get_device(0);
// Configure Infrared stream to run at VGA resolution at 30 frames per second
dev->enable_stream(rs::stream::depth, 640, 480, rs::format::z16, 30);
// Start streaming
dev->start();
// Camera warmup - Dropped several first frames to let auto-exposure stabilize
for(int i = 0; i < 30; i++)
dev->wait_for_frames();
// Creating OpenCV Matrix from a color image
Mat depth(Size(640, 480), CV_16U, (void*)dev->get_frame_data(rs::stream::depth), Mat::AUTO_STEP);
// Create a color depth
Mat color_depth;
make_depth_histogram(depth, color_depth);
// Create a normalized depth
double min, max;
minMaxLoc(depth, &min, &max);
Mat depth_normalized;
double alpha = 255.0/(max-min);
depth.convertTo(depth_normalized, CV_8U, alpha, -min*alpha);
// Display in a GUI
imshow("Display normalized depth", depth_normalized);
imshow("Display color depth", color_depth);
waitKey(0);
return 0;
【讨论】:
当我执行“标准化深度”步骤时,我的新 8 位图像出现脉动,这意味着图像中的所有像素变得非常亮,然后非常暗(所有像素的数量相同)。这有点奇怪。真正变亮大约需要一秒钟,然后再变暗,然后重复。你知道那可能是什么吗?可能是一些自动曝光问题或相机的问题? 当我将最大值和最小值设置为常数时,闪烁消失了。看静态物体时没有闪烁。当事物移动时,就会发生闪烁。这是有道理的,因为至少 alpha 总是在变化。 您应该使用make_depth_histogram()
来可视化深度图。这有点费时,但可视化应该只用于调试目的。【参考方案2】:
我发现这个问题的唯一解决方案是:
将图像保存为 PNG 文件。 (PNG支持保存16位图片)
使用matplotlib
在彩色地图中查看:
#!/usr/bin/python3
import numpy as np
import cv2
import sys
from matplotlib import pyplot as plt
def printCoordinates(event):
x,y = event.xdata,event.ydata
if x != None:
print("X : ",x," Y: ",y," Value = ",img[np.int(y),np.int(x)])
img = cv2.imread(sys.argv[1],cv2.CV_16UC1)
#img = img/65535
fig = plt.figure()
plt.imshow(img,cmap='nipy_spectral')
cid = fig.canvas.mpl_connect('button_press_event',printCoordinates)
plt.colorbar()
plt.show()
button_press_event
是在点击的像素上打印准确的像素值。
RGB 图像:
对应的深度图像:
【讨论】:
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