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openpilot v0.5.11 release

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Vehicle Researcher
2019-04-23 01:41:19 +00:00
parent 790732bea3
commit 2f92d577f9
99 changed files with 2744 additions and 1607 deletions
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common/transformations/camera.py
+48 -20
View File
@@ -1,6 +1,7 @@
import numpy as np
import common.transformations.orientation as orient
import cv2
import math
FULL_FRAME_SIZE = (1164, 874)
W, H = FULL_FRAME_SIZE[0], FULL_FRAME_SIZE[1]
@@ -12,6 +13,17 @@ eon_intrinsics = np.array([
[ 0., FOCAL, H/2.],
[ 0., 0., 1.]])
leon_dcam_intrinsics = np.array([
[650, 0, 816/2],
[ 0, 650, 612/2],
[ 0, 0, 1]])
eon_dcam_intrinsics = np.array([
[860, 0, 1152/2],
[ 0, 860, 864/2],
[ 0, 0, 1]])
# aka 'K_inv' aka view_frame_from_camera_frame
eon_intrinsics_inv = np.linalg.inv(eon_intrinsics)
@@ -147,28 +159,44 @@ def transform_img(base_img,
from_intr=eon_intrinsics,
to_intr=eon_intrinsics,
calib_rot_view=None,
output_size=None):
cy = from_intr[1,2]
output_size=None,
pretransform=None,
top_hacks=True):
size = base_img.shape[:2]
if not output_size:
output_size = size[::-1]
h = 1.22
quadrangle = np.array([[0, cy + 20],
[size[1]-1, cy + 20],
[0, size[0]-1],
[size[1]-1, size[0]-1]], dtype=np.float32)
quadrangle_norm = np.hstack((normalize(quadrangle, intrinsics=from_intr), np.ones((4,1))))
quadrangle_world = np.column_stack((h*quadrangle_norm[:,0]/quadrangle_norm[:,1],
h*np.ones(4),
h/quadrangle_norm[:,1]))
rot = orient.rot_from_euler(augment_eulers)
if calib_rot_view is not None:
rot = calib_rot_view.dot(rot)
to_extrinsics = np.hstack((rot.T, -augment_trans[:,None]))
to_KE = to_intr.dot(to_extrinsics)
warped_quadrangle_full = np.einsum('jk,ik->ij', to_KE, np.hstack((quadrangle_world, np.ones((4,1)))))
warped_quadrangle = np.column_stack((warped_quadrangle_full[:,0]/warped_quadrangle_full[:,2],
warped_quadrangle_full[:,1]/warped_quadrangle_full[:,2])).astype(np.float32)
M = cv2.getPerspectiveTransform(quadrangle, warped_quadrangle.astype(np.float32))
cy = from_intr[1,2]
def get_M(h=1.22):
quadrangle = np.array([[0, cy + 20],
[size[1]-1, cy + 20],
[0, size[0]-1],
[size[1]-1, size[0]-1]], dtype=np.float32)
quadrangle_norm = np.hstack((normalize(quadrangle, intrinsics=from_intr), np.ones((4,1))))
quadrangle_world = np.column_stack((h*quadrangle_norm[:,0]/quadrangle_norm[:,1],
h*np.ones(4),
h/quadrangle_norm[:,1]))
rot = orient.rot_from_euler(augment_eulers)
if calib_rot_view is not None:
rot = calib_rot_view.dot(rot)
to_extrinsics = np.hstack((rot.T, -augment_trans[:,None]))
to_KE = to_intr.dot(to_extrinsics)
warped_quadrangle_full = np.einsum('jk,ik->ij', to_KE, np.hstack((quadrangle_world, np.ones((4,1)))))
warped_quadrangle = np.column_stack((warped_quadrangle_full[:,0]/warped_quadrangle_full[:,2],
warped_quadrangle_full[:,1]/warped_quadrangle_full[:,2])).astype(np.float32)
M = cv2.getPerspectiveTransform(quadrangle, warped_quadrangle.astype(np.float32))
return M
M = get_M()
if pretransform is not None:
M = M.dot(pretransform)
augmented_rgb = cv2.warpPerspective(base_img, M, output_size, borderMode=cv2.BORDER_REPLICATE)
if top_hacks:
cyy = int(math.ceil(to_intr[1,2]))
M = get_M(1000)
if pretransform is not None:
M = M.dot(pretransform)
augmented_rgb[:cyy] = cv2.warpPerspective(base_img, M, (output_size[0], cyy), borderMode=cv2.BORDER_REPLICATE)
return augmented_rgb
common/transformations/model.py
+1 -1
View File
@@ -32,7 +32,7 @@ model_intrinsics = np.array(
# MED model
MEDMODEL_INPUT_SIZE = (640, 240)
MEDMODEL_INPUT_SIZE = (512, 256)
MEDMODEL_YUV_SIZE = (MEDMODEL_INPUT_SIZE[0], MEDMODEL_INPUT_SIZE[1] * 3 // 2)
MEDMODEL_CY = 47.6