我使用来自Intel Real Sense相机的彩色和深度图像生成点 Cloud .
使用 pyRealSense 库捕获图像 .
要将深度图像转换为 Cloud ，我使用以下基于 numpy 的函数：
def point_cloud(depth, cx=320.0, cy=240.0, fx=463.889, fy=463.889):
"""Transform a depth image into a point cloud with one point for each
pixel in the image, using the camera transform for a camera
centred at cx, cy with field of view fx, fy.
depth is a 2-D ndarray with shape (rows, cols) containing
depths from 1 to 254 inclusive. The result is a 3-D array with
shape (rows, cols, 3). Pixels with invalid depth in the input have
NaN for the z-coordinate in the result.
My Changes:
* Author had divided depth by 256 to normalize, I hadn't done that so I removed it.
* Output coordinates are in units of 1m. There is a factor of 500 applied at image capture.
* Author had returned a 3 * 480 * 640 np array. I changed to 3 flat arrays
"""
rows, cols = depth.shape
print fx, fy, cx, cy
c, r = np.meshgrid(np.arange(cols), np.arange(rows), sparse=True)
valid = (depth >= 0) & (depth <= 255)
z = np.where(valid, depth, np.nan)
x = np.where(valid, z * (c - cx) / fx, 0)
y = np.where(valid, z * (r - cy) / fy, 0)
return x.flatten(), y.flatten(), z.flatten()
这是一张显示我正在谈论的山脊的图像：
图像是坐在光滑的 table 上的物体 .
我看不出那些山脊会存在的原因，在那个区域没有等于零的深度值 .
这仅仅是 x 和 y 的输入是整数这一事实的遗产吗？