Spaces:
Build error
Build error
File size: 8,626 Bytes
db9ef5e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 |
import numpy as np
def xy_points_to_slope_midpoint(xy_points):
"""
Given two points, return the slope and midpoint of the line
Args:
xy_points: list of two points, each point is a list of two elements
Points are in the form of [x, y], where x and y are normalized to [0, 1]
Returns:
slope: Slope of the line
midpoint : Midpoint is in the form of [x,y], and is also normalized to [0, 1]
"""
x1, y1, x2, y2 = xy_points[0][0], xy_points[0][1], xy_points[1][
0], xy_points[1][1]
slope = (y2 - y1) / (x2 - x1)
midpoint_x = 0.5
midpoint_y = slope * (0.5 - x1) + y1
midpoint = [midpoint_x, midpoint_y]
return slope, midpoint
def calculate_horizon_error(annotated_horizon, proposed_horizon):
"""
Calculate the error between the annotated horizon and the proposed horizon
Args:
annotated_horizon: list of two points, each point is a list of two elements
Points are in the form of [x, y], where x and y are normalized to [0, 1]
proposed_horizon: list of two points, each point is a list of two elements
Points are in the form of [x, y], where x and y are normalized to [0, 1]
Returns:
slope_error: Error in the slope of the lines
midpoint_error: Error in the midpoint_y of the lines
"""
slope_annotated, midpoint_annotated = xy_points_to_slope_midpoint(
annotated_horizon)
slope_proposed, midpoint_proposed = xy_points_to_slope_midpoint(
proposed_horizon)
slope_error = abs(slope_annotated - slope_proposed)
midpoint_error = abs(midpoint_annotated[1] - midpoint_proposed[1])
return slope_error, midpoint_error
def calculate_horizon_error_across_sequence(slope_error_list,
midpoint_error_list,
slope_error_jump_threshold,
midpoint_error_jump_threshold):
"""
Calculate the error statistics across a sequence of frames
Args:
slope_error_list: List of errors in the slope of the lines
midpoint_error_list: List of errors in the midpoint_y of the lines
Returns:
average_slope_error: Average error in the slope of the lines
average_midpoint_error: Average error in the midpoint_y of the lines
"""
# Calculate the average and standard deviation of the errors
average_slope_error = np.mean(slope_error_list)
average_midpoint_error = np.mean(midpoint_error_list)
stddev_slope_error = np.std(slope_error_list)
stddev_midpoint_error = np.std(midpoint_error_list)
# Calculate the maximum errors
max_slope_error = np.max(slope_error_list)
max_midpoint_error = np.max(midpoint_error_list)
# Calculate the differences between errors in successive frames
diff_slope_error = np.abs(np.diff(slope_error_list))
diff_midpoint_error = np.abs(np.diff(midpoint_error_list))
# Calculate the number of jumps in the errors
num_slope_error_jumps = np.sum(
diff_slope_error > slope_error_jump_threshold)
num_midpoint_error_jumps = np.sum(
diff_midpoint_error > midpoint_error_jump_threshold)
# Create a dictionary to store the results
sequence_results = {
'average_slope_error': average_slope_error,
'average_midpoint_error': average_midpoint_error,
'stddev_slope_error': stddev_slope_error,
'stddev_midpoint_error': stddev_midpoint_error,
'max_slope_error': max_slope_error,
'max_midpoint_error': max_midpoint_error,
'num_slope_error_jumps': num_slope_error_jumps,
'num_midpoint_error_jumps': num_midpoint_error_jumps
}
return sequence_results
import numpy as np
import cv2
import matplotlib.pyplot as plt
def xy_points_to_slope_midpoint(xy_points):
"""
Given two points, return the slope and midpoint of the line
Args:
xy_points: list of two points, each point is a list of two elements
Points are in the form of [x, y], where x and y are normalized to [0, 1]
Returns:
slope: Slope of the line
midpoint : Midpoint is in the form of [x,y], and is also normalized to [0, 1]
"""
x1, y1, x2, y2 = xy_points[0][0], xy_points[0][1], xy_points[1][
0], xy_points[1][1]
slope = (y2 - y1) / (x2 - x1)
midpoint_x = 0.5
midpoint_y = slope * (0.5 - x1) + y1
midpoint = [midpoint_x, midpoint_y]
return slope, midpoint
def calculate_horizon_error(annotated_horizon, proposed_horizon):
"""
Calculate the error between the annotated horizon and the proposed horizon
Args:
annotated_horizon: list of two points, each point is a list of two elements
Points are in the form of [x, y], where x and y are normalized to [0, 1]
proposed_horizon: list of two points, each point is a list of two elements
Points are in the form of [x, y], where x and y are normalized to [0, 1]
Returns:
slope_error: Error in the slope of the lines
midpoint_error: Error in the midpoint_y of the lines
"""
slope_annotated, midpoint_annotated = xy_points_to_slope_midpoint(
annotated_horizon)
slope_proposed, midpoint_proposed = xy_points_to_slope_midpoint(
proposed_horizon)
slope_error = abs(slope_annotated - slope_proposed)
midpoint_error = abs(midpoint_annotated[1] - midpoint_proposed[1])
return slope_error, midpoint_error
def calculate_horizon_error_across_sequence(slope_error_list,
midpoint_error_list,
slope_error_jump_threshold,
midpoint_error_jump_threshold):
"""
Calculate the error statistics across a sequence of frames
Args:
slope_error_list: List of errors in the slope of the lines
midpoint_error_list: List of errors in the midpoint_y of the lines
Returns:
average_slope_error: Average error in the slope of the lines
average_midpoint_error: Average error in the midpoint_y of the lines
"""
# Calculate the average and standard deviation of the errors
average_slope_error = np.mean(slope_error_list)
average_midpoint_error = np.mean(midpoint_error_list)
stddev_slope_error = np.std(slope_error_list)
stddev_midpoint_error = np.std(midpoint_error_list)
# Calculate the maximum errors
max_slope_error = np.max(slope_error_list)
max_midpoint_error = np.max(midpoint_error_list)
# Calculate the differences between errors in successive frames
diff_slope_error = np.abs(np.diff(slope_error_list))
diff_midpoint_error = np.abs(np.diff(midpoint_error_list))
# Calculate the number of jumps in the errors
num_slope_error_jumps = np.sum(
diff_slope_error > slope_error_jump_threshold)
num_midpoint_error_jumps = np.sum(
diff_midpoint_error > midpoint_error_jump_threshold)
# Create a dictionary to store the results
sequence_results = {
'average_slope_error': average_slope_error,
'average_midpoint_error': average_midpoint_error,
'stddev_slope_error': stddev_slope_error,
'stddev_midpoint_error': stddev_midpoint_error,
'max_slope_error': max_slope_error,
'max_midpoint_error': max_midpoint_error,
'num_slope_error_jumps': num_slope_error_jumps,
'num_midpoint_error_jumps': num_midpoint_error_jumps
}
return sequence_results
def slope_to_roll(slope):
"""
Convert the slope of the horizon to roll
Args:
slope: Slope of the horizon
Returns:
roll: Roll in degrees
"""
roll = np.arctan(slope) * 180 / np.pi
return roll
def roll_to_slope(roll):
"""
Convert the roll of the horizon to slope
Args:
roll: Roll of the horizon in degrees
Returns:
slope: Slope of the horizon
"""
slope = np.tan(roll * np.pi / 180)
return slope
def midpoint_to_pitch(midpoint, vertical_fov_degrees):
"""
Convert the midpoint of the horizon to pitch
Args:
midpoint: Midpoint of the horizon
vertical_fov_degrees: Vertical field of view of the camera in degrees
Returns:
pitch: Pitch in degrees
"""
pitch = midpoint * vertical_fov_degrees
return pitch
def pitch_to_midpoint(pitch, vertical_fov_degrees):
"""
Convert the pitch of the horizon to midpoint
Args:
pitch: Pitch of the horizon in degrees
vertical_fov_degrees: Vertical field of view of the camera in degrees
Returns:
midpoint: Midpoint of the horizon
"""
midpoint = pitch / vertical_fov_degrees
return midpoint
|