def test_read_dataset():
print("===== start test_read_dataset")
dataset = TfrecordReader(op.join(cfg.Paths.TFRECORD,
"kitti_train")).get_dataset()
for i, x in enumerate(dataset):
print(
f"=== index: {i}, image={x['image'].shape}, bbox={x['bboxes'].shape}"
f", feature_l={x['feature_l'].shape}, feature_s={x['feature_s'].shape}"
)
image = uf.to_uint8_image(x['image'])
image = image[0].numpy()
bboxes = x['bboxes'][0].numpy()
image = tu.draw_boxes(image, bboxes, cfg.Tfrdata.CATEGORY_NAMES)
cv2.imshow("image with boxes", image)
features = []
for feat_name in cfg.Model.Output.FEATURE_ORDER:
feature = x[feat_name][0].numpy()
feature = feature[feature[..., 4] > 0]
features.append(feature)
feat_boxes = np.concatenate(features, axis=0)
image = tu.draw_boxes(image, feat_boxes, cfg.Tfrdata.CATEGORY_NAMES)
cv2.imshow("image with feature bboxes", image)
key = cv2.waitKey()
if key == ord('q'):
break
print("!!! test_read_dataset passed")
def show_example(self, example):
category_names = cfg.Tfrdata.CATEGORY_NAMES
image = tu.draw_boxes(example["image"], example["bboxes"], category_names)
cv2.imshow("image with bboxes", image)
features = []
for feat_name in cfg.Model.FEATURE_ORDER:
feature = example[feat_name]
feature = feature[feature[..., 4] > 0] # objectness == 1
features.append(feature)
feat_boxes = np.concatenate(features, axis=0)
image = tu.draw_boxes(example["image"], feat_boxes, category_names)
cv2.imshow("image with feature bboxes", image)
cv2.waitKey(100)
def test_kitti_reader():
print("===== start test_kitti_reader")
dataset_cfg = cfg.Datasets.Kitti
drive_mngr = KittiDriveManager(dataset_cfg.PATH, "train")
drive_paths = drive_mngr.get_drive_paths()
reader = KittiReader(drive_paths[0], "train", dataset_cfg)
for i in range(reader.num_frames()):
image = reader.get_image(i)
bboxes = reader.get_bboxes(i)
print(f"frame {i}, bboxes:\n", bboxes)
boxed_image = tu.draw_boxes(image, bboxes, dataset_cfg.CATEGORIES_TO_USE)
cv2.imshow("kitti", boxed_image)
key = cv2.waitKey()
if key == ord('q'):
break
print("!!! test_kitti_reader passed")