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import cv2 |
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import numpy as np |
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from navsim.common.extraction.helpers import transformation |
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def draw_pcs_on_images(pc, cam_infos, eps=1e-3): |
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for cam_type, cam_info in cam_infos.items(): |
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cur_img_path = cam_info["data_path"] |
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cur_img = cv2.imread(cur_img_path) |
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cur_img_h, cur_img_w = cur_img.shape[:2] |
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cur_pc_cam, cur_pc_in_fov = transformation.transform_pcs_to_images( |
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pc, |
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cam_info["sensor2lidar_rotation"], |
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cam_info["sensor2lidar_translation"], |
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cam_info["cam_intrinsic"], |
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img_shape=(cur_img_h, cur_img_w), |
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eps=eps, |
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) |
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cur_pc_cam = cur_pc_cam[cur_pc_in_fov] |
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for x, y in cur_pc_cam: |
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cv2.circle(cur_img, (int(x), int(y)), 3, (255, 0, 0), 3) |
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cv2.imwrite(f"dbg/{cam_type}.png", cur_img) |
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return None |
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def draw_pcs(points, labels, color_map): |
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"""Draw point cloud from BEV |
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Args: |
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points: A ndarray with shape as [-1, 3] |
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labels: the label of each point with shape [-1] |
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color_map: color of each label. |
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""" |
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import matplotlib.pyplot as plt |
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_, ax = plt.subplots(1, 1, figsize=(9, 9)) |
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axes_limit = 40 |
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viz_points = points |
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dists = np.sqrt(np.sum(viz_points[:, :2] ** 2, axis=1)) |
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colors = np.minimum(1, dists / axes_limit / np.sqrt(2)) |
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points_color = color_map[labels] / 255.0 |
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point_scale = 0.2 |
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scatter = ax.scatter(viz_points[:, 0], viz_points[:, 1], c=points_color, s=point_scale) |
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ax.plot(0, 0, "x", color="red") |
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ax.set_xlim(-axes_limit, axes_limit) |
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ax.set_ylim(-axes_limit, axes_limit) |
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ax.axis("off") |
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ax.set_aspect("equal") |
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plt.savefig("dbg/dbg.png", bbox_inches="tight", pad_inches=0, dpi=200) |
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def draw_sweep_pcs(info, sweeps): |
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cur_pc_file = info["lidar_path"] |
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cur_pc = transformation._load_points(cur_pc_file) |
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viz_pcs = [cur_pc[:, :3]] |
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viz_labels = [np.ones_like(cur_pc)[:, 0] * 0.0] |
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for idx, sweep in enumerate(sweeps): |
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sweep_pc_file = sweep["data_path"] |
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sweep_pc = transformation._load_points(sweep_pc_file) |
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sweep_pc = transformation.transform_sweep_pc_to_lidar_top( |
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sweep_pc, sweep["sensor2lidar_rotation"], sweep["sensor2lidar_translation"] |
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) |
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viz_pcs.append(sweep_pc) |
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viz_labels.append(np.ones_like(sweep_pc)[:, 0] * (idx + 1)) |
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viz_pcs = np.concatenate(viz_pcs, 0) |
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viz_labels = np.concatenate(viz_labels, 0).astype(np.int) |
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color_map = np.array( |
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[ |
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[245, 150, 100], |
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[245, 230, 100], |
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[250, 80, 100], |
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[150, 60, 30], |
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[255, 0, 0], |
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[180, 30, 80], |
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[255, 0, 0], |
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[30, 30, 255], |
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[200, 40, 255], |
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[90, 30, 150], |
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] |
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) |
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draw_pcs(viz_pcs, viz_labels, color_map) |
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return None |
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