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torch model

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This commit is contained in:
Rick Lan
2020-11-10 09:32:17 +10:00
parent d6b3cb2e32
commit 8a8dfafa56
33 changed files with 786 additions and 492 deletions
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common/transformations/model.py
+57 -45
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@@ -1,34 +1,33 @@
import numpy as np
from common.transformations.camera import (FULL_FRAME_SIZE, eon_focal_length,
from common.transformations.camera import (FULL_FRAME_SIZE,
FOCAL,
get_view_frame_from_road_frame,
get_view_frame_from_calib_frame,
vp_from_ke)
# segnet
SEGNET_SIZE = (512, 384)
segnet_frame_from_camera_frame = np.array([
[float(SEGNET_SIZE[0])/FULL_FRAME_SIZE[0], 0., ],
[ 0., float(SEGNET_SIZE[1])/FULL_FRAME_SIZE[1]]])
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
# model
MODEL_INPUT_SIZE = (320, 160)
MODEL_YUV_SIZE = (MODEL_INPUT_SIZE[0], MODEL_INPUT_SIZE[1] * 3 // 2)
MODEL_CX = MODEL_INPUT_SIZE[0]/2.
MODEL_CX = MODEL_INPUT_SIZE[0] / 2.
MODEL_CY = 21.
model_zoom = 1.25
model_fl = 728.0
model_height = 1.22
# canonical model transform
model_intrinsics = np.array(
[[ eon_focal_length / model_zoom, 0. , MODEL_CX],
[ 0. , eon_focal_length / model_zoom, MODEL_CY],
[ 0. , 0. , 1.]])
model_intrinsics = np.array([
[model_fl, 0.0, MODEL_CX],
[0.0, model_fl, MODEL_CY],
[0.0, 0.0, 1.0]])
# MED model
@@ -36,64 +35,76 @@ MEDMODEL_INPUT_SIZE = (512, 256)
MEDMODEL_YUV_SIZE = (MEDMODEL_INPUT_SIZE[0], MEDMODEL_INPUT_SIZE[1] * 3 // 2)
MEDMODEL_CY = 47.6
medmodel_zoom = 1.
medmodel_intrinsics = np.array(
[[ eon_focal_length / medmodel_zoom, 0. , 0.5 * MEDMODEL_INPUT_SIZE[0]],
[ 0. , eon_focal_length / medmodel_zoom, MEDMODEL_CY],
[ 0. , 0. , 1.]])
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]])
# CAL model
CALMODEL_INPUT_SIZE = (512, 256)
CALMODEL_YUV_SIZE = (CALMODEL_INPUT_SIZE[0], CALMODEL_INPUT_SIZE[1] * 3 // 2)
CALMODEL_CY = 47.6
calmodel_zoom = 1.5
calmodel_intrinsics = np.array(
[[ eon_focal_length / calmodel_zoom, 0. , 0.5 * CALMODEL_INPUT_SIZE[0]],
[ 0. , eon_focal_length / calmodel_zoom, CALMODEL_CY],
[ 0. , 0. , 1.]])
calmodel_fl = 606.7
calmodel_intrinsics = np.array([
[calmodel_fl, 0.0, 0.5 * CALMODEL_INPUT_SIZE[0]],
[0.0, calmodel_fl, CALMODEL_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_zoom = 1.
bigmodel_intrinsics = np.array(
[[ eon_focal_length / bigmodel_zoom, 0. , 0.5 * BIGMODEL_INPUT_SIZE[0]],
[ 0. , eon_focal_length / bigmodel_zoom, 256+MEDMODEL_CY],
[ 0. , 0. , 1.]])
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]])
model_frame_from_road_frame = np.dot(model_intrinsics,
get_view_frame_from_road_frame(0, 0, 0, model_height))
get_view_frame_from_road_frame(0, 0, 0, model_height))
bigmodel_frame_from_road_frame = np.dot(bigmodel_intrinsics,
get_view_frame_from_road_frame(0, 0, 0, model_height))
get_view_frame_from_road_frame(0, 0, 0, model_height))
medmodel_frame_from_road_frame = np.dot(medmodel_intrinsics,
get_view_frame_from_road_frame(0, 0, 0, model_height))
get_view_frame_from_road_frame(0, 0, 0, model_height))
medmodel_frame_from_calib_frame = np.dot(medmodel_intrinsics,
get_view_frame_from_calib_frame(0, 0, 0, 0))
get_view_frame_from_calib_frame(0, 0, 0, 0))
model_frame_from_bigmodel_frame = np.dot(model_intrinsics, np.linalg.inv(bigmodel_intrinsics))
medmodel_frame_from_bigmodel_frame = np.dot(medmodel_intrinsics, np.linalg.inv(bigmodel_intrinsics))
# 'camera from model camera'
def get_model_height_transform(camera_frame_from_road_frame, height):
camera_frame_from_road_ground = np.dot(camera_frame_from_road_frame, np.array([
[1, 0, 0],
[0, 1, 0],
[0, 0, 0],
[0, 0, 1],
[1, 0, 0],
[0, 1, 0],
[0, 0, 0],
[0, 0, 1],
]))
camera_frame_from_road_high = np.dot(camera_frame_from_road_frame, np.array([
[1, 0, 0],
[0, 1, 0],
[0, 0, height - model_height],
[0, 0, 1],
[1, 0, 0],
[0, 1, 0],
[0, 0, height - model_height],
[0, 0, 1],
]))
road_high_from_camera_frame = np.linalg.inv(camera_frame_from_road_high)
@@ -104,13 +115,14 @@ def get_model_height_transform(camera_frame_from_road_frame, height):
# camera_frame_from_model_frame aka 'warp matrix'
# was: calibration.h/CalibrationTransform
def get_camera_frame_from_model_frame(camera_frame_from_road_frame, height=model_height):
def get_camera_frame_from_model_frame(camera_frame_from_road_frame, height=model_height, camera_fl=FOCAL):
vp = vp_from_ke(camera_frame_from_road_frame)
model_zoom = camera_fl / model_fl
model_camera_from_model_frame = np.array([
[model_zoom, 0., vp[0] - MODEL_CX * model_zoom],
[ 0., model_zoom, vp[1] - MODEL_CY * model_zoom],
[ 0., 0., 1.],
[model_zoom, 0.0, vp[0] - MODEL_CX * model_zoom],
[0.0, model_zoom, vp[1] - MODEL_CY * model_zoom],
[0.0, 0.0, 1.0],
])
# This function is super slow, so skip it if height is very close to canonical