mirror of
https://github.com/opencv/opencv.git
synced 2024-12-14 08:59:11 +08:00
112 lines
3.3 KiB
Python
112 lines
3.3 KiB
Python
import numpy as np
|
|
from scipy.spatial.transform import Rotation
|
|
from PIL import Image
|
|
import os
|
|
|
|
depthFactor = 5000
|
|
psize = (640, 480)
|
|
fx = 525.0
|
|
fy = 525.0
|
|
cx = psize[0]/2-0.5
|
|
cy = psize[1]/2-0.5
|
|
K = np.array([[fx, 0, cx],
|
|
[ 0, fy, cy],
|
|
[ 0, 0, 1]])
|
|
|
|
# some random transform
|
|
rmat = Rotation.from_rotvec(np.array([0.1, 0.2, 0.3])).as_dcm()
|
|
tmat = np.array([[-0.04, 0.05, 0.6]]).T
|
|
rtmat = np.vstack((np.hstack((rmat, tmat)), np.array([[0, 0, 0, 1]])))
|
|
|
|
testDataPath = os.getenv("OPENCV_TEST_DATA_PATH", default=None)
|
|
srcDepth = np.asarray(Image.open(testDataPath + "/cv/rgbd/depth.png"))
|
|
srcRgb = np.asarray(Image.open(testDataPath + "/cv/rgbd/rgb.png"))
|
|
|
|
def reproject(image, df, K):
|
|
Kinv = np.linalg.inv(K)
|
|
xsz, ysz = image.shape[1], image.shape[0]
|
|
reprojected = np.zeros((ysz, xsz, 3))
|
|
for y in range(ysz):
|
|
for x in range(xsz):
|
|
z = image[y, x]/df
|
|
|
|
v = Kinv @ np.array([x*z, y*z, z]).T
|
|
|
|
#xv = (x - cx)/fx * z
|
|
#yv = (y - cy)/fy * z
|
|
#zv = z
|
|
|
|
reprojected[y, x, :] = v[:]
|
|
return reprojected
|
|
|
|
def reprojectRtProject(image, K, depthFactor, rmat, tmat):
|
|
Kinv = np.linalg.inv(K)
|
|
xsz, ysz = image.shape[1], image.shape[0]
|
|
projected = np.zeros((ysz, xsz, 3))
|
|
for y in range(ysz):
|
|
for x in range(xsz):
|
|
z = image[y, x]/depthFactor
|
|
|
|
v = K @ (rmat @ Kinv @ np.array([x*z, y*z, z]).T + tmat[:, 0])
|
|
|
|
if z > 0:
|
|
projected[y, x, :] = v[:]
|
|
|
|
return projected
|
|
|
|
def reprojectRt(image, K, depthFactor, rmat, tmat):
|
|
Kinv = np.linalg.inv(K)
|
|
xsz, ysz = image.shape[1], image.shape[0]
|
|
rotated = np.zeros((ysz, xsz, 3))
|
|
for y in range(ysz):
|
|
for x in range(xsz):
|
|
z = image[y, x]/depthFactor
|
|
|
|
v = rmat @ Kinv @ np.array([x*z, y*z, z]).T + tmat[:, 0]
|
|
|
|
rotated[y, x, :] = v[:]
|
|
|
|
return rotated
|
|
|
|
# put projected points on a depth map
|
|
def splat(projected, maxv, rgb):
|
|
xsz, ysz = projected.shape[1], projected.shape[0]
|
|
depth = np.full((ysz, xsz), maxv, np.float32)
|
|
colors = np.full((ysz, xsz, 3), 0, np.uint8)
|
|
for y in range(ysz):
|
|
for x in range(xsz):
|
|
p = projected[y, x, :]
|
|
z = p[2]
|
|
if z > 0:
|
|
u, v = int(p[0]/z), int(p[1]/z)
|
|
okuv = (u >= 0 and v >= 0 and u < xsz and v < ysz)
|
|
if okuv and depth[v, u] > z:
|
|
depth[v, u] = z
|
|
colors[v, u, :] = rgb[y, x, :]
|
|
return depth, colors
|
|
|
|
maxv = depthFactor
|
|
dstDepth, dstRgb = splat(reprojectRtProject(srcDepth, K, depthFactor, rmat, tmat), maxv, srcRgb)
|
|
dstDepth[dstDepth >= maxv] = 0
|
|
dstDepth = (dstDepth*depthFactor).astype(np.uint16)
|
|
|
|
Image.fromarray(dstDepth).save(testDataPath + "/cv/rgbd/warpedDepth.png")
|
|
Image.fromarray(dstRgb ).save(testDataPath + "/cv/rgbd/warpedRgb.png")
|
|
|
|
# debug
|
|
def outFile(path, ptsimg):
|
|
f = open(path, "w")
|
|
for y in range(ptsimg.shape[0]):
|
|
for x in range(ptsimg.shape[1]):
|
|
v = ptsimg[y, x, :]
|
|
if v[2] > 0:
|
|
f.write(f"v {v[0]} {v[1]} {v[2]}\n")
|
|
f.close()
|
|
|
|
outObj = False
|
|
if outObj:
|
|
objdir = "/path/to/objdir/"
|
|
outFile(objdir + "reproj_rot_proj.obj", reproject(dstDepth, depthFactor, K))
|
|
outFile(objdir + "rotated.obj", reprojectRt(srcDepth, K, depthFactor, rmat, tmat))
|
|
|