import pathlib
from vlmeval.dataset.utils.mmdocbench_eval import update_data_format, eval_mmdocbench

from .image_base import ImageBaseDataset
from ..smp import *


class MMDocBench(ImageBaseDataset):
    TYPE = 'MMDoc'
    DATASET_URL = {
        'MMDocBench': ''
    }
    DATASET_MD5 = {'MMDocBench': None}

    @classmethod
    def evaluate(self, eval_file, **judge_kwargs):
        data = load(eval_file)
        data2 = update_data_format(data)
        data2.drop("task", axis=1, inplace=True)
        data2.drop("sub_task", axis=1, inplace=True)
        data2.drop("image_path", axis=1, inplace=True)
        data2.drop("full_prediction", axis=1, inplace=True)
        data2.drop("raw_question", axis=1, inplace=True)
        data2.drop("question", axis=1, inplace=True)
        data2 = json.loads(data2.to_json(orient="records"))
        accs = {"Visual Perception": 0, "Visual Reasoning": 0}
        cnts = {"Visual Perception": 0, "Visual Reasoning": 0}
        for r in data2:
            cnts[r["category"]] += 1
            accs[r["category"]] += eval_mmdocbench("" if r["prediction"] is None else r["prediction"], r["answer"], strict=False)
        for k in accs:
            accs[k] = accs[k] / cnts[k]
        accs["Overall"] = (accs["Visual Perception"] + accs["Visual Reasoning"]) / 2
        df_score = pd.DataFrame.from_dict(accs, orient='index', columns=['accuracy'])
        # save df_score to xlsx
        df_score.to_excel(eval_file.replace('.xlsx', '_score.xlsx'), index=True)
        return df_score

    def build_prompt(self, line):
        if isinstance(line, int):
            line = self.data.iloc[line]

        if self.meta_only:
            tgt_path = toliststr(line['image_path'])
        else:
            tgt_path = self.dump_image(line)

        question = line['question']
        msgs = []
        if isinstance(tgt_path, list):
            msgs.extend([dict(type='image', value=p) for p in tgt_path])
        else:
            msgs = [dict(type='image', value=tgt_path)]
        msgs.append(dict(type='text', value=question))

        return msgs