Initial commit

src/models/ocr_model/utils/inference.py

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+import torch
+
+from transformers import RobertaTokenizerFast, GenerationConfig
+from typing import List
+
+from models.ocr_model.model.TexTeller import TexTeller
+from models.ocr_model.utils.transforms import inference_transform
+from models.ocr_model.utils.helpers import convert2rgb
+from models.globals import MAX_TOKEN_SIZE
+
+
+def inference(
+    model: TexTeller, 
+    tokenizer: RobertaTokenizerFast,
+    imgs_path: List[str], 
+    use_cuda: bool,
+    num_beams: int = 1,
+) -> List[str]:
+    model.eval()
+    imgs = convert2rgb(imgs_path)
+    imgs = inference_transform(imgs)
+    pixel_values = torch.stack(imgs)
+
+    if use_cuda:
+        model = model.to('cuda')
+        pixel_values = pixel_values.to('cuda')
+
+    generate_config = GenerationConfig(
+        max_new_tokens=MAX_TOKEN_SIZE,
+        num_beams=num_beams,
+        do_sample=False,
+        pad_token_id=tokenizer.pad_token_id,
+        eos_token_id=tokenizer.eos_token_id,
+        bos_token_id=tokenizer.bos_token_id,
+    )
+    pred = model.generate(pixel_values, generation_config=generate_config)
+    res = tokenizer.batch_decode(pred, skip_special_tokens=True)
+    return res