dataloader = create_val_dataloader(configs)
print('len val dataloader: {}'.format(len(dataloader)))
print('\n\nPress n to see the next sample >>> Press Esc to quit...')
for batch_i, (img_files, imgs, targets) in enumerate(dataloader):
if not (configs.mosaic and configs.show_train_data):
img_file = img_files[0]
img_rgb = cv2.imread(img_file)
calib = kitti_data_utils.Calibration(
img_file.replace(".png", ".txt").replace("image_2", "calib"))
objects_pred = invert_target(targets[:, 1:],
calib,
img_rgb.shape,
RGB_Map=None)
img_rgb = show_image_with_boxes(img_rgb, objects_pred, calib,
False)
# Rescale target
targets[:, 2:6] *= configs.img_size
# Get yaw angle
targets[:, 6] = torch.atan2(targets[:, 6], targets[:, 7])
img_bev = imgs.squeeze() * 255
img_bev = img_bev.permute(1, 2, 0).numpy().astype(np.uint8)
img_bev = cv2.resize(img_bev, (configs.img_size, configs.img_size))
for c, x, y, w, l, yaw in targets[:, 1:7].numpy():
# Draw rotated box
bev_utils.drawRotatedBox(img_bev, x, y, w, l, yaw,
cnf.colors[int(c)])
img_detections.extend(detections)
bev_maps = torch.squeeze(bev_maps).numpy()
RGB_Map = np.zeros((cnf.BEV_WIDTH, cnf.BEV_WIDTH, 3))
RGB_Map[:, :, 2] = bev_maps[0, :, :] # r_map
RGB_Map[:, :, 1] = bev_maps[1, :, :] # g_map
RGB_Map[:, :, 0] = bev_maps[2, :, :] # b_map
RGB_Map = (255 * RGB_Map).astype(np.uint8)
for detections in img_detections:
if detections is None:
continue
# Rescale boxes to original image
detections = np.array(detections)
print('detections shape: {}'.format(detections.shape))
detections = rescale_boxes(detections, configs.img_size, RGB_Map.shape[:2])
for x, y, w, l, im, re, cls_conf, cls_pred in detections:
yaw = np.arctan2(im, re)
# Draw rotated box
kitti_bev_utils.drawRotatedBox(RGB_Map, x, y, w, l, yaw, cnf.colors[int(cls_pred)])
img2d = cv2.imread(img_paths[0])
calib = kitti_data_utils.Calibration(img_paths[0].replace(".png", ".txt").replace("image_2", "calib"))
objects_pred = predictions_to_kitti_format(img_detections, calib, img2d.shape, configs.img_size)
img2d = show_image_with_boxes(img2d, objects_pred, calib, False)
cv2.imshow("bev img", RGB_Map)
cv2.imshow("img2d", img2d)
if cv2.waitKey(0) & 0xFF == 27:
break
