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# Scene Text Recognition Model Hub
# Copyright 2022 Darwin Bautista
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Optional, Sequence
from torch import Tensor
from pytorch_lightning.utilities.types import STEP_OUTPUT
from strhub.models.base import CTCSystem
from strhub.models.utils import init_weights
from .model import CRNN as Model
class CRNN(CTCSystem):
def __init__(
self,
charset_train: str,
charset_test: str,
max_label_length: int,
batch_size: int,
lr: float,
warmup_pct: float,
weight_decay: float,
img_size: Sequence[int],
hidden_size: int,
leaky_relu: bool,
**kwargs,
) -> None:
super().__init__(charset_train, charset_test, batch_size, lr, warmup_pct, weight_decay)
self.save_hyperparameters()
self.model = Model(img_size[0], 3, len(self.tokenizer), hidden_size, leaky_relu)
self.model.apply(init_weights)
def forward(self, images: Tensor, max_length: Optional[int] = None) -> Tensor:
return self.model.forward(images)
def training_step(self, batch, batch_idx) -> STEP_OUTPUT:
images, labels = batch
loss = self.forward_logits_loss(images, labels)[1]
self.log('loss', loss)
return loss
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