Thai Image Captioning
Encoder-decoder style image captioning model using CLIP encoder and Wangchanberta. Trained on Thai language MSCOCO and IPU24 dataset.
Usage
Use AutoModel
to load it. Requires trust_remote_code=True
.
from transformers import AutoModel, AutoImageProcessor, AutoTokenizer
device = 'cuda'
gen_kwargs = {"max_length": 120, "num_beams": 4}
model_path = 'Natthaphon/thaicapgen-clip-gpt2'
feature_extractor = AutoImageProcessor.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModel.from_pretrained(model_path, trust_remote_code=True).to(device)
pixel_values = feature_extractor(images=[Image.open(image_path)], return_tensors="pt").pixel_values
pixel_values = pixel_values.to(device)
output_ids = model.generate(pixel_values, **gen_kwargs)
preds = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
Acknowledgement
This work is partially supported by the Program Management Unit for Human Resources & Institutional Development, Research and Innovation (PMU-B) [Grant number B04G640107]
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