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| # import os | |
| # os.system("curl -L -o tensor.pt https://seyarabata.com/btfo_by_24mb_model; sleep 3") | |
| import gradio as gr | |
| import torch | |
| from PIL import Image | |
| from strhub.data.module import SceneTextDataModule | |
| # from strhub.models.utils import load_from_checkpoint, parse_model_args | |
| parseq = torch.load('tensor.pt', map_location=torch.device('cpu')).eval() | |
| img_transform = SceneTextDataModule.get_transform(parseq.hparams.img_size) | |
| examples = [ | |
| 'show1.png', | |
| 'show2.png', | |
| 'show3.png', | |
| 'show4.png', | |
| 'show5.png'] | |
| def captcha_solver(img): | |
| img = img.convert('RGB') | |
| img = img_transform(img).unsqueeze(0) | |
| logits = parseq(img) | |
| logits.shape | |
| # # Greedy decoding | |
| pred = logits.softmax(-1) | |
| label, confidence = parseq.tokenizer.decode(pred) | |
| print(label) | |
| print(confidence) | |
| return label[0] | |
| demo = gr.Interface(fn=captcha_solver, examples=examples, inputs=gr.inputs.Image(type="pil"), outputs=gr.outputs.Textbox()) | |
| demo.launch() |