Multimodal-GPT / mmgpt /datasets /ocr_vqa_dataset.py
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import os
import random
from PIL import Image
from .vqa_dataset import VQADataset
class OCRVQADataset(VQADataset):
def process_image(self, ann):
image_path = os.path.join(self.vis_root, ann["filename"])
image = Image.open(image_path).convert("RGB")
image = self.vis_processor(image)
return image
def process_text(self, ann):
index = random.choice(list(range(len(ann["questions"]))))
question = ann["questions"][index]
answer = ann["answers"][index]
instruction = self.prompter(question)
return dict(instruction=instruction, answer=answer)