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Deep Learning toolkit for Computer Vision.
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Reduction axis 0 is empty in shape [0,2] error while training object detection using frcnn #247

Open annusrcm opened 5 years ago

annusrcm commented 5 years ago

I am training object detection with 3159 images and got this error while training.

INFO:tensorflow:Training 279 vars from pretrained module; from "truncated_base_network/resnet_v1_101/block2/unit_1/bottleneck_v1/shortcut/weights:0" to "truncated_base_network/resnet_v1_101/block4/unit_3/bottleneck_v1/conv3/BatchNorm/beta:0". /iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/ops/gradients_impl.py:108: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory. "Converting sparse IndexedSlices to a dense Tensor of unknown shape. " INFO:tensorflow:Starting training for <luminoth.models.fasterrcnn.fasterrcnn.FasterRCNN object at 0x7fd080d9ca58> WARNING:tensorflow:From /iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py:118: initialize_local_variables (from tensorflow.python.ops.variables) is deprecated and will be removed after 2017-03-02. Instructions for updating: Use tf.local_variables_initializer instead. INFO:tensorflow:ImageVisHook was created with mode = "train" INFO:tensorflow:Create CheckpointSaverHook. INFO:tensorflow:Graph was finalized. 2018-11-23 14:51:27.574463: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 AVX512F FMA INFO:tensorflow:Restoring parameters from /iq_storage/table_detection/uq_data/all_uq_tables/6/jobs/table-area-detection-0.1/model.ckpt-718 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Saving checkpoints for 718 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:Saving checkpoints for 719 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 719, file: b'LSE_HTO_2013_Original_203.png', train_loss: 4.515841484069824, in 21.23s INFO:tensorflow:Saving checkpoints for 720 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 720, file: b'LSE_HTO_2014_Original_250.png', train_loss: 4.2614898681640625, in 19.90s INFO:tensorflow:Saving checkpoints for 721 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 721, file: b'LSE_HSP_2014_Original_57.png', train_loss: 5.102310657501221, in 19.99s INFO:tensorflow:Saving checkpoints for 722 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 722, file: b'LSE_HSV_2006_Original_90.png', train_loss: 4.3329644203186035, in 15.97s INFO:tensorflow:Saving checkpoints for 723 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 723, file: b'LSE_HTO_2014_Original_252.png', train_loss: 4.909831523895264, in 16.07s INFO:tensorflow:Saving checkpoints for 724 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 724, file: b'LSE_BSY_2012_Original_120.png', train_loss: 6.184804439544678, in 16.49s INFO:tensorflow:Saving checkpoints for 725 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 725, file: b'LSE_HL_2015_Original_16.png', train_loss: 7.809842109680176, in 16.19s INFO:tensorflow:Saving checkpoints for 726 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 726, file: b'LSE_ADN_2008_Original_74.png', train_loss: 4.301699638366699, in 16.22s INFO:tensorflow:Saving checkpoints for 727 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 727, file: b'Appendix_HSI_32200_Call_Termsheet_Original_1.png', train_loss: 5.701766014099121, in 16.12s INFO:tensorflow:Saving checkpoints for 728 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 728, file: b'LSE_ABF_2010_Original_12.png', train_loss: 7.281338691711426, in 16.34s INFO:tensorflow:Saving checkpoints for 729 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 729, file: b'LSE_MCB_2012_Original_71.png', train_loss: 4.783441543579102, in 16.38s INFO:tensorflow:Saving checkpoints for 730 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 730, file: b'LSE_ADN_2008_Original_47.png', train_loss: 5.152769565582275, in 16.12s INFO:tensorflow:Saving checkpoints for 731 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 731, file: b'LSE_LGEN_2016_Original_116.png', train_loss: 4.426446914672852, in 16.19s INFO:tensorflow:Saving checkpoints for 732 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epochmodel/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 732, file: b'Appendix.HSI_25600_Put_Termsheet_Original_4.png', train_loss: 5.287724494934082, in 16.12s INFO:tensorflow:Saving checkpoints for 733 into /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/table-area-detection-0.1/model.ckpt. INFO:tensorflow:step: 733, file: b'LSE_ADN_2010_Original_101.png', train_loss: nan, in 17.80s Traceback (most recent call last): File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1278, in _do_call return fn(*args) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1263, in _run_fn options, feed_dict, fetch_list, target_list, run_metadata) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1350, in _call_tf_sessionrun run_metadata) tensorflow.python.framework.errors_impl.InvalidArgumentError: Reduction axis 0 is empty in shape [0,2]

 [[Node: fasterrcnn/rcnn/rcnn_proposal/ArgMax_1 = ArgMax[T=DT_FLOAT, Tidx=DT_INT32, output_type=DT_INT64, _device="/job:localhost/replica:0/task:0/device:CPU:0"](fasterrcnn/rcnn/rcnn_proposal/bbox_overlap/Maximum_4, gradients/gradients/losses/RPNLoss/boolean_mask_1/GatherV2_grad/concat/axis)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/iq_storage/virtualenv/table_detection/bin/lumi", line 11, in sys.exit(cli()) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 722, in call return self.main(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 697, in main rv = self.invoke(ctx) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 1066, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 895, in invoke return ctx.invoke(self.callback, ctx.params) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 535, in invoke return callback(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/luminoth/train.py", line 307, in train config, environment=environment File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/luminoth/train.py", line 239, in run ], options=run_options) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/training/monitored_session.py", line 583, in run run_metadata=run_metadata) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/training/monitored_session.py", line 1059, in run run_metadata=run_metadata) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/training/monitored_session.py", line 1150, in run raise six.reraise(original_exc_info) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/six.py", line 693, in reraise raise value File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/training/monitored_session.py", line 1135, in run return self._sess.run(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/training/monitored_session.py", line 1207, in run run_metadata=run_metadata) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/training/monitored_session.py", line 987, in run return self._sess.run(*args, **kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 877, in run run_metadata_ptr) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1100, in _run feed_dict_tensor, options, run_metadata) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1272, in _do_run run_metadata) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1291, in _do_call raise type(e)(node_def, op, message) tensorflow.python.framework.errors_impl.InvalidArgumentError: Reduction axis 0 is empty in shape [0,2]

 [[Node: fasterrcnn/rcnn/rcnn_proposal/ArgMax_1 = ArgMax[T=DT_FLOAT, Tidx=DT_INT32, output_type=DT_INT64, _device="/job:localhost/replica:0/task:0/device:CPU:0"](fasterrcnn/rcnn/rcnn_proposal/bbox_overlap/Maximum_4, gradients/gradients/losses/RPNLoss/boolean_mask_1/GatherV2_grad/concat/axis)]]

Caused by op 'fasterrcnn/rcnn/rcnn_proposal/ArgMax_1', defined at: File "/iq_storage/virtualenv/table_detection/bin/lumi", line 11, in sys.exit(cli()) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 722, in call return self.main(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 697, in main rv = self.invoke(ctx) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 1066, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 895, in invoke return ctx.invoke(self.callback, ctx.params) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/click/core.py", line 535, in invoke return callback(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/luminoth/train.py", line 307, in train config, environment=environment File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/luminoth/train.py", line 66, in run prediction_dict = model(train_image, train_bboxes, is_training=True) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/sonnet/python/modules/base.py", line 389, in call outputs, subgraph_name_scope = self._template(*args, *kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/ops/template.py", line 359, in call return self._call_func(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/ops/template.py", line 310, in _call_func result = self._func(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/sonnet/python/modules/base.py", line 246, in _build_wrapper output = self._build(*args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/luminoth/models/fasterrcnn/fasterrcnn.py", line 151, in _build gt_boxes=gt_boxes, is_training=is_training File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/sonnet/python/modules/base.py", line 389, in call outputs, subgraph_name_scope = self._template(*args, *kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/ops/template.py", line 359, in call return self._call_func(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/ops/template.py", line 310, in _call_func result = self._func(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/sonnet/python/modules/base.py", line 246, in _build_wrapper output = self._build(*args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/luminoth/models/fasterrcnn/rcnn.py", line 154, in _build proposals, gt_boxes) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/sonnet/python/modules/base.py", line 389, in call outputs, subgraph_name_scope = self._template(*args, *kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/ops/template.py", line 359, in call return self._call_func(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/ops/template.py", line 310, in _call_func result = self._func(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/sonnet/python/modules/base.py", line 246, in _build_wrapper output = self._build(*args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/luminoth/models/fasterrcnn/rcnn_target.py", line 116, in _build best_proposals_idxs = tf.argmax(overlaps, axis=0) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py", line 454, in new_func return func(*args, *kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/ops/math_ops.py", line 88, in argmax return gen_math_ops.arg_max(input, axis, name=name, output_type=output_type) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/ops/gen_math_ops.py", line 783, in arg_max name=name) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper op_def=op_def) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py", line 454, in new_func return func(args, kwargs) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3155, in create_op op_def=op_def) File "/iq_storage/virtualenv/table_detection/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1717, in init self._traceback = tf_stack.extract_stack()

InvalidArgumentError (see above for traceback): Reduction axis 0 is empty in shape [0,2]

 [[Node: fasterrcnn/rcnn/rcnn_proposal/ArgMax_1 = ArgMax[T=DT_FLOAT, Tidx=DT_INT32, output_type=DT_INT64, _device="/job:localhost/replica:0/task:0/device:CPU:0"](fasterrcnn/rcnn/rcnn_proposal/bbox_overlap/Maximum_4, gradients/gradients/losses/RPNLoss/boolean_mask_1/GatherV2_grad/concat/axis)]]
ghost commented 5 years ago

I think you can give your configuration file(.yml) and the commands you use so that contributors might be more likely to give you some advice.

Refer to the tips in the documentation, I use lumi to train on VOC2007 dataset , it performed well during training.

https://luminoth.readthedocs.io/en/latest/usage/training.html

annusrcm commented 5 years ago

Hi @LarT2P , Thank you for your advice.

  1. First of all I am using the image pre processing techniques described in this paper.
  2. Then I create tfrecords using the command: lumi dataset transform --type csv --data-dir data/ --output-dir tfdata/ --split train --split val --only-classes=table
  3. And finally I train using following command: lumi train -c config.yml

I used the following configuration file (config.yml).

train: run_name: table-area-detection-0.1 learning_rate: decay_method: exponential_decay decay_rate: 0.5 decay_steps: 5000 learning_rate: 0.0003 job_dir: /iq_storage/table_detection/uq_data/folder6_7_9_11_one_epoch_model/jobs/ save_checkpoint_secs: 10 save_summaries_secs: 10

num_epochs: 1

dataset: type: object_detection dir: /iq_storage/table_detection/uq_data/all_uq_tables/9/tfdata/ image_preprocessing: min_size: 600 max_size: 1024 data_augmentation:

model: type: fasterrcnn network: num_classes: 1

shahmustafa commented 5 years ago

Hi, I am also in the same problem. did you find any solution @annusrcm?

sbhavani commented 5 years ago

I'm also having the same problem. The MS COCO format was not working so I converted to CSV and now I'm getting the same error.

guuswinkelmolen commented 5 years ago

I'm suffering a similar issue. For me it is not crashing when using this first config, but when wanting more customization there is some parameter which causes the following error:

tensorflow.python.framework.errors_impl.InvalidArgumentError: Reduction axis 0 is empty in shape [0,1] [[{{node fasterrcnn/rcnn/rcnn_proposal/ArgMax_1}} = ArgMax[T=DT_FLOAT, Tidx=DT_INT32, output_type=DT_INT64, _device="/job:localhost/replica:0/task:0/device:GPU:0"](fasterrcnn/rcnn/rcnn_proposal/bbox_overlap/Maximum_4, gradients/gradients/losses/RCNNLoss/cls_score_labeled/GatherV2_grad/concat/axis)]] [[{{node fasterrcnn/rcnn/rcnn_proposal/GreaterEqual_2/_7295}} = _HostRecv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_7064_fasterrcnn/rcnn/rcnn_proposal/GreaterEqual_2", tensor_type=DT_BOOL, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

I have tried changing the foreground and background thresholds for both the rpn and rcnn, the anchor scales and ratios as well as some of the nms settings, but nothing seems to help. First, more limited config: (which doesn't crash)

train: run_name: DTD_full_data_5 job_dir: jobs/

save_checkpoint_secs: 60 save_summaries_secs: 60

num_epochs: 40000

batch_size: 1

random_shuffle: True

learning_rate: _replace: True learning_rate: 0.0003

optimizer: _replace: True type: momentum momentum: 0.9

eval: image_vis: eval

dataset: type: object_detection

dir: tfdata

image_preprocessing: min_size: 600 data_augmentation:

model: type: fasterrcnn network: num_classes: 1 with_rcnn: True

batch_norm: False

base_network: architecture: resnet_v2_152 trainable: True

weights:
download: True
fine_tune_from:

loss: rpn_cls_loss_weight: 1.0 rpn_reg_loss_weights: 1.0 rcnn_cls_loss_weight: 1.0 rcnn_reg_loss_weights: 1.0

anchors: base_size: 256 scales: [0.5,1,2] ratios: [0.5,1,2,3] stride:

Second, more custom config (which causes the crash after training for a bit):

train: run_name: DTD_full_data_4

job_dir: jobs/

save_checkpoint_secs: 60 save_summaries_secs: 60

num_epochs: 40000

batch_size: 1

random_shuffle: True

learning_rate: _replace: True decay_method: piecewise_constant boundaries: [25000, 45000, 60000] values: [0.0003, 0.0001, 0.00003, 0.00001]

optimizer: _replace: True type: momentum momentum: 0.9

eval: image_vis: eval

dataset: type: object_detection

dir: tfdata

image_preprocessing: min_size: 600 data_augmentation:

model: type: fasterrcnn network:

Total number of classes to predict.

num_classes: 1
with_rcnn: True

batch_norm: False

base_network: architecture: resnet_v2_152 trainable: True

weights:
download: True

fine_tune_from:

output_stride: 16

arg_scope:
  weight_decay: 0.0005

loss: rpn_cls_loss_weight: 1.0 rpn_reg_loss_weights: 1.0 rcnn_cls_loss_weight: 1.0 rcnn_reg_loss_weights: 1.0

anchors: base_size: 256 scales: [0.5,1,2] ratios: [0.5,1,2,3]

rpn: activation_function: relu6 l2_regularization_scale: 0.0005 # Disable using 0. l1_sigma: 3.0 num_channels: 512 kernel_shape: [3, 3] rpn_initializer: _replace: True type: random_normal_initializer mean: 0.0 stddev: 0.01 cls_initializer: _replace: True type: random_normal_initializer mean: 0.0 stddev: 0.01 bbox_initializer: _replace: True type: random_normal_initializer mean: 0.0 stddev: 0.001

proposals:
  pre_nms_top_n: 12000
  post_nms_top_n: 2000
  apply_nms: True
  nms_threshold: 0.2
  min_size: 0  # Disable using 0.
  clip_after_nms: False
  filter_outside_anchors: True
  min_prob_threshold: 0.0

target:
  allowed_border: 0
  clobber_positives: False
  foreground_threshold: 0.7
  background_threshold_high: 0.3
  background_threshold_low: 0.0
  foreground_fraction: 0.5
  minibatch_size: 256

rcnn:

layer_sizes: []

dropout_keep_prob: 1.0
activation_function: relu6
l2_regularization_scale: 0.0005
l1_sigma: 1.0
use_mean: True
target_normalization_variances: [0.1, 0.2]

rcnn_initializer:
  _replace: True
  type: variance_scaling_initializer
  factor: 1.0
  uniform: True
  mode: FAN_AVG
cls_initializer:
  _replace: True
  type: random_normal_initializer
  mean: 0.0
  stddev: 0.01
bbox_initializer:
  _replace: True
  type: random_normal_initializer
  mean: 0.0
  stddev: 0.001

roi:
  pooling_mode: crop
  pooled_width: 7
  pooled_height: 7
  padding: VALID

proposals:
  class_max_detections: 100
  class_nms_threshold: 0.5
  total_max_detections: 300
  min_prob_threshold: 0.5

target:
  foreground_fraction: 0.3
  minibatch_size: 512
  foreground_threshold: 0.7
  background_threshold_high: 0.3
  background_threshold_low: 0.0

(Sorry for the odd formatting, I tried making stuff pretty, but somehow it does not appreciate my effort 😅)