diff options
Diffstat (limited to 'src/text_recognizer')
| -rw-r--r-- | src/text_recognizer/datasets/emnist_lines_dataset.py | 9 | ||||
| -rw-r--r-- | src/text_recognizer/datasets/iam_paragraphs_dataset.py | 7 | ||||
| -rw-r--r-- | src/text_recognizer/datasets/util.py | 2 | ||||
| -rw-r--r-- | src/text_recognizer/models/base.py | 10 | ||||
| -rw-r--r-- | src/text_recognizer/tests/support/create_emnist_support_files.py | 13 |
5 files changed, 23 insertions, 18 deletions
diff --git a/src/text_recognizer/datasets/emnist_lines_dataset.py b/src/text_recognizer/datasets/emnist_lines_dataset.py index 6268a01..beb5343 100644 --- a/src/text_recognizer/datasets/emnist_lines_dataset.py +++ b/src/text_recognizer/datasets/emnist_lines_dataset.py @@ -149,6 +149,7 @@ class EmnistLinesDataset(Dataset): # Load emnist dataset. emnist = EmnistDataset(train=self.train, sample_to_balance=True) + emnist.load_or_generate_data() samples_by_character = get_samples_by_character( emnist.data.numpy(), emnist.targets.numpy(), self.mapper.mapping, @@ -306,17 +307,13 @@ def create_datasets( num_test: int = 1000, ) -> None: """Creates a training an validation dataset of Emnist lines.""" - emnist_train = EmnistDataset(train=True, sample_to_balance=True) - emnist_test = EmnistDataset(train=False, sample_to_balance=True) - datasets = [emnist_train, emnist_test] num_samples = [num_train, num_test] - for num, train, dataset in zip(num_samples, [True, False], datasets): + for num, train in zip(num_samples, [True, False]): emnist_lines = EmnistLinesDataset( train=train, - emnist=dataset, max_length=max_length, min_overlap=min_overlap, max_overlap=max_overlap, num_samples=num, ) - emnist_lines._load_or_generate_data() + emnist_lines.load_or_generate_data() diff --git a/src/text_recognizer/datasets/iam_paragraphs_dataset.py b/src/text_recognizer/datasets/iam_paragraphs_dataset.py index 4b34bd1..c1e8fe2 100644 --- a/src/text_recognizer/datasets/iam_paragraphs_dataset.py +++ b/src/text_recognizer/datasets/iam_paragraphs_dataset.py @@ -266,11 +266,16 @@ def _load_iam_paragraphs() -> None: @click.option( "--subsample_fraction", type=float, - default=0.0, + default=None, help="The subsampling factor of the dataset.", ) def main(subsample_fraction: float) -> None: """Load dataset and print info.""" + logger.info("Creating train set...") + dataset = IamParagraphsDataset(train=True, subsample_fraction=subsample_fraction) + dataset.load_or_generate_data() + print(dataset) + logger.info("Creating test set...") dataset = IamParagraphsDataset(subsample_fraction=subsample_fraction) dataset.load_or_generate_data() print(dataset) diff --git a/src/text_recognizer/datasets/util.py b/src/text_recognizer/datasets/util.py index 73968a1..125f05a 100644 --- a/src/text_recognizer/datasets/util.py +++ b/src/text_recognizer/datasets/util.py @@ -26,7 +26,7 @@ def save_emnist_essentials(emnsit_dataset: type = EMNIST) -> None: mapping = [(i, str(label)) for i, label in enumerate(labels)] essentials = { "mapping": mapping, - "input_shape": tuple(emnsit_dataset[0][0].shape[:]), + "input_shape": tuple(np.array(emnsit_dataset[0][0]).shape[:]), } logger.info("Saving emnist essentials...") with open(ESSENTIALS_FILENAME, "w") as f: diff --git a/src/text_recognizer/models/base.py b/src/text_recognizer/models/base.py index caf8065..e89b670 100644 --- a/src/text_recognizer/models/base.py +++ b/src/text_recognizer/models/base.py @@ -356,7 +356,8 @@ class Model(ABC): state["optimizer_state"] = self._optimizer.state_dict() if self._lr_scheduler is not None: - state["scheduler_state"] = self._lr_scheduler.state_dict() + state["scheduler_state"] = self._lr_scheduler["lr_scheduler"].state_dict() + state["scheduler_interval"] = self._lr_scheduler["interval"] if self._swa_network is not None: state["swa_network"] = self._swa_network.state_dict() @@ -383,8 +384,11 @@ class Model(ABC): if self._lr_scheduler is not None: # Does not work when loadning from previous checkpoint and trying to train beyond the last max epochs # with OneCycleLR. - if self._lr_scheduler.__class__.__name__ != "OneCycleLR": - self._lr_scheduler.load_state_dict(checkpoint["scheduler_state"]) + if self._lr_scheduler["lr_scheduler"].__class__.__name__ != "OneCycleLR": + self._lr_scheduler["lr_scheduler"].load_state_dict( + checkpoint["scheduler_state"] + ) + self._lr_scheduler["interval"] = checkpoint["scheduler_interval"] if self._swa_network is not None: self._swa_network.load_state_dict(checkpoint["swa_network"]) diff --git a/src/text_recognizer/tests/support/create_emnist_support_files.py b/src/text_recognizer/tests/support/create_emnist_support_files.py index 5dd1a81..c04860d 100644 --- a/src/text_recognizer/tests/support/create_emnist_support_files.py +++ b/src/text_recognizer/tests/support/create_emnist_support_files.py @@ -2,10 +2,8 @@ from pathlib import Path import shutil -from text_recognizer.datasets.emnist_dataset import ( - fetch_emnist_dataset, - load_emnist_mapping, -) +from text_recognizer.datasets.emnist_dataset import EmnistDataset +from text_recognizer.datasets.util import EmnistMapper from text_recognizer.util import write_image SUPPORT_DIRNAME = Path(__file__).parents[0].resolve() / "emnist" @@ -16,15 +14,16 @@ def create_emnist_support_files() -> None: shutil.rmtree(SUPPORT_DIRNAME, ignore_errors=True) SUPPORT_DIRNAME.mkdir() - dataset = fetch_emnist_dataset(split="byclass", train=False) - mapping = load_emnist_mapping() + dataset = EmnistDataset(train=False) + dataset.load_or_generate_data() + mapping = EmnistMapper() for index in [5, 7, 9]: image, label = dataset[index] if len(image.shape) == 3: image = image.squeeze(0) image = image.numpy() - label = mapping[int(label)] + label = mapping(int(label)) print(index, label) write_image(image, str(SUPPORT_DIRNAME / f"{label}.png")) |