You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
117 lines
4.4 KiB
117 lines
4.4 KiB
import numpy as np
|
|
|
|
from common.transformations.camera import (FULL_FRAME_SIZE,
|
|
get_view_frame_from_calib_frame)
|
|
|
|
# segnet
|
|
SEGNET_SIZE = (512, 384)
|
|
|
|
def get_segnet_frame_from_camera_frame(segnet_size=SEGNET_SIZE, full_frame_size=FULL_FRAME_SIZE):
|
|
return np.array([[float(segnet_size[0]) / full_frame_size[0], 0.0],
|
|
[0.0, float(segnet_size[1]) / full_frame_size[1]]])
|
|
segnet_frame_from_camera_frame = get_segnet_frame_from_camera_frame() # xx
|
|
|
|
|
|
# MED model
|
|
MEDMODEL_INPUT_SIZE = (512, 256)
|
|
MEDMODEL_YUV_SIZE = (MEDMODEL_INPUT_SIZE[0], MEDMODEL_INPUT_SIZE[1] * 3 // 2)
|
|
MEDMODEL_CY = 47.6
|
|
|
|
medmodel_fl = 910.0
|
|
medmodel_intrinsics = np.array([
|
|
[medmodel_fl, 0.0, 0.5 * MEDMODEL_INPUT_SIZE[0]],
|
|
[0.0, medmodel_fl, MEDMODEL_CY],
|
|
[0.0, 0.0, 1.0]])
|
|
|
|
|
|
# BIG model
|
|
BIGMODEL_INPUT_SIZE = (1024, 512)
|
|
BIGMODEL_YUV_SIZE = (BIGMODEL_INPUT_SIZE[0], BIGMODEL_INPUT_SIZE[1] * 3 // 2)
|
|
|
|
bigmodel_fl = 910.0
|
|
bigmodel_intrinsics = np.array([
|
|
[bigmodel_fl, 0.0, 0.5 * BIGMODEL_INPUT_SIZE[0]],
|
|
[0.0, bigmodel_fl, 256 + MEDMODEL_CY],
|
|
[0.0, 0.0, 1.0]])
|
|
|
|
|
|
# SBIG model (big model with the size of small model)
|
|
SBIGMODEL_INPUT_SIZE = (512, 256)
|
|
SBIGMODEL_YUV_SIZE = (SBIGMODEL_INPUT_SIZE[0], SBIGMODEL_INPUT_SIZE[1] * 3 // 2)
|
|
|
|
sbigmodel_fl = 455.0
|
|
sbigmodel_intrinsics = np.array([
|
|
[sbigmodel_fl, 0.0, 0.5 * SBIGMODEL_INPUT_SIZE[0]],
|
|
[0.0, sbigmodel_fl, 0.5 * (256 + MEDMODEL_CY)],
|
|
[0.0, 0.0, 1.0]])
|
|
|
|
bigmodel_frame_from_calib_frame = np.dot(bigmodel_intrinsics,
|
|
get_view_frame_from_calib_frame(0, 0, 0, 0))
|
|
|
|
|
|
sbigmodel_frame_from_calib_frame = np.dot(sbigmodel_intrinsics,
|
|
get_view_frame_from_calib_frame(0, 0, 0, 0))
|
|
|
|
medmodel_frame_from_calib_frame = np.dot(medmodel_intrinsics,
|
|
get_view_frame_from_calib_frame(0, 0, 0, 0))
|
|
|
|
medmodel_frame_from_bigmodel_frame = np.dot(medmodel_intrinsics, np.linalg.inv(bigmodel_intrinsics))
|
|
|
|
|
|
### This function mimics the update_calibration logic in modeld.cc
|
|
### Manually verified to give similar results to xx.uncommon.utils.transform_img
|
|
def get_warp_matrix(rpy_calib, wide_cam=False, big_model=False, tici=True):
|
|
from common.transformations.orientation import rot_from_euler
|
|
from common.transformations.camera import view_frame_from_device_frame, eon_fcam_intrinsics, tici_ecam_intrinsics, tici_fcam_intrinsics
|
|
|
|
if tici and wide_cam:
|
|
intrinsics = tici_ecam_intrinsics
|
|
elif tici:
|
|
intrinsics = tici_fcam_intrinsics
|
|
else:
|
|
intrinsics = eon_fcam_intrinsics
|
|
|
|
if big_model:
|
|
sbigmodel_from_calib = sbigmodel_frame_from_calib_frame[:, (0,1,2)]
|
|
calib_from_model = np.linalg.inv(sbigmodel_from_calib)
|
|
else:
|
|
medmodel_from_calib = medmodel_frame_from_calib_frame[:, (0,1,2)]
|
|
calib_from_model = np.linalg.inv(medmodel_from_calib)
|
|
device_from_calib = rot_from_euler(rpy_calib)
|
|
camera_from_calib = intrinsics.dot(view_frame_from_device_frame.dot(device_from_calib))
|
|
warp_matrix = camera_from_calib.dot(calib_from_model)
|
|
return warp_matrix
|
|
|
|
|
|
### This is old, just for debugging
|
|
def get_warp_matrix_old(rpy_calib, wide_cam=False, big_model=False, tici=True):
|
|
from common.transformations.orientation import rot_from_euler
|
|
from common.transformations.camera import view_frame_from_device_frame, eon_fcam_intrinsics, tici_ecam_intrinsics, tici_fcam_intrinsics
|
|
|
|
|
|
def get_view_frame_from_road_frame(roll, pitch, yaw, height):
|
|
device_from_road = rot_from_euler([roll, pitch, yaw]).dot(np.diag([1, -1, -1]))
|
|
view_from_road = view_frame_from_device_frame.dot(device_from_road)
|
|
return np.hstack((view_from_road, [[0], [height], [0]]))
|
|
|
|
if tici and wide_cam:
|
|
intrinsics = tici_ecam_intrinsics
|
|
elif tici:
|
|
intrinsics = tici_fcam_intrinsics
|
|
else:
|
|
intrinsics = eon_fcam_intrinsics
|
|
|
|
model_height = 1.22
|
|
if big_model:
|
|
model_from_road = np.dot(sbigmodel_intrinsics,
|
|
get_view_frame_from_road_frame(0, 0, 0, model_height))
|
|
else:
|
|
model_from_road = np.dot(medmodel_intrinsics,
|
|
get_view_frame_from_road_frame(0, 0, 0, model_height))
|
|
ground_from_model = np.linalg.inv(model_from_road[:, (0, 1, 3)])
|
|
|
|
E = get_view_frame_from_road_frame(*rpy_calib, 1.22)
|
|
camera_frame_from_road_frame = intrinsics.dot(E)
|
|
camera_frame_from_ground = camera_frame_from_road_frame[:,(0,1,3)]
|
|
warp_matrix = camera_frame_from_ground .dot(ground_from_model)
|
|
return warp_matrix
|
|
|