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--- |
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library_name: transformers |
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metrics: |
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- cer |
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widget: |
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- src: "https://i.ibb.co/QXZFSNx/test7.png" |
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output: |
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text: รมว.ธรรมนัส ลงพื้นที่ |
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language: |
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- th |
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pipeline_tag: image-to-text |
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--- |
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# thai_trocr_thaigov_v2 |
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<!-- Provide a quick summary of what the model is/does. --> |
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Vision Encoder Decoder Models |
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- Use microsoft/trocr-base-handwritten as encoder. |
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- Use airesearch/wangchanberta-base-att-spm-uncased as decoder |
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- Fine-tune on 250k synthetic text images dataset using [ThaiGov V2 Corpus](https://github.com/PyThaiNLP/thaigov-v2-corpus) |
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- Use [SynthTIGER](https://github.com/clovaai/synthtiger) to generate synthetic text image. |
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- It is useful to fine-tune any Thai OCR task. |
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# Usage |
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``` python |
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from PIL import Image |
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from transformers import TrOCRProcessor, VisionEncoderDecoderModel |
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processor = TrOCRProcessor.from_pretrained("kkatiz/thai-trocr-thaigov-v2") |
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model = VisionEncoderDecoderModel.from_pretrained("kkatiz/thai-trocr-thaigov-v2") |
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image = Image.open("... your image path").convert("RGB") |
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pixel_values = processor(image, return_tensors="pt").pixel_values |
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generated_ids = model.generate(pixel_values) |
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generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] |
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print(generated_text) |
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``` |
