示例#1
0
# is not the position of the rover but a bit in front of it
bottom_offset = 6
source = np.float32([[14, 140], [301, 140], [200, 96], [118, 96]])
destination = np.float32([
    [image.shape[1] / 2 - dst_size, image.shape[0] - bottom_offset],
    [image.shape[1] / 2 + dst_size, image.shape[0] - bottom_offset],
    [
        image.shape[1] / 2 + dst_size,
        image.shape[0] - 2 * dst_size - bottom_offset
    ],
    [
        image.shape[1] / 2 - dst_size,
        image.shape[0] - 2 * dst_size - bottom_offset
    ],
])
warped = perspect_transform(image, source, destination)
colorsel = color_thresh(warped, rgb_thresh=(160, 160, 160))
# Extract nabigable terrain pixels
xpix, ypix = rover_coords(colorsel)
# Generate 200x200 pixel worldmap
worldmap = np.zeros((200, 200))
scale = 10
# Get navigable pixel positions in world coords
x_world, y_world = pix_to_world(xpix, ypix, rover_xpos, rover_ypos, rover_yaw,
                                worldmap.shape[0], scale)
# Add pixel positions to worldmap
worldmap[y_world, x_world] += 1
print('Xpos = ', rover_xpos, 'Ypos = ', rover_ypos, 'Yaw = ', rover_yaw)
# Plot the map in rover-centric coords

f, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 7))
source = np.float32([[14, 140], [301, 140], [200, 96], [118, 96]])
destination = np.float32([
    [image.shape[1] / 2 - dst_size, image.shape[0] - bottom_offset],
    [image.shape[1] / 2 + dst_size, image.shape[0] - bottom_offset],
    [
        image.shape[1] / 2 + dst_size,
        image.shape[0] - 2 * dst_size - bottom_offset
    ],
    [
        image.shape[1] / 2 - dst_size,
        image.shape[0] - 2 * dst_size - bottom_offset
    ],
])

warped = perspect_transform(image, source,
                            destination)  # Perform perspective transform
colorsel = color_thresh(warped, rgb_thresh=(160, 160,
                                            160))  # threshold the warped image
xpix, ypix = rover_coords(colorsel)  # convert to rover-centric coordinates
distances, angles = to_polar_coords(xpix, ypix)  # Convert to polar coordinates
avg_angle = np.mean(angles)  # Compite the average angle

# Do some plotting
fig = plt.figure(figsize=(12, 9))
plt.subplot(221)
plt.imshow(image)
plt.subplot(222)
plt.imshow(warped)
plt.subplot(223)
plt.imshow(colorsel, cmap='gray')
plt.subplot(224)