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#!/usr/bin/env python3
# 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.
import argparse
from PIL import Image
import torch
from strhub.data.module import SceneTextDataModule
from strhub.models.utils import load_from_checkpoint, parse_model_args
@torch.inference_mode()
def main():
parser = argparse.ArgumentParser()
parser.add_argument('checkpoint', help="Model checkpoint (or 'pretrained=<model_id>')")
parser.add_argument('--images', nargs='+', help='Images to read')
parser.add_argument('--device', default='cuda')
args, unknown = parser.parse_known_args()
kwargs = parse_model_args(unknown)
print(f'Additional keyword arguments: {kwargs}')
model = load_from_checkpoint(args.checkpoint, **kwargs).eval().to(args.device)
img_transform = SceneTextDataModule.get_transform(model.hparams.img_size)
for fname in args.images:
# Load image and prepare for input
image = Image.open(fname).convert('RGB')
image = img_transform(image).unsqueeze(0).to(args.device)
p = model(image).softmax(-1)
pred, p = model.tokenizer.decode(p)
print(f'{fname}: {pred[0]}')
if __name__ == '__main__':
main()
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