import logging
import time

from fastapi import APIRouter
from app.schemas.outfit_matcher import OutfitMatcher
from app.service.outfit_matcher.dataset import FashionDataset
from app.service.outfit_matcher.outfit_evaluator import OutfitMaterTypeAware
from app.service.utils.decorator import RunTime

logger = logging.getLogger()
router = APIRouter()


@RunTime
@router.post("outfit_matcher")
def outfit_matcher(request_item: OutfitMatcher):
    request_item = dict(request_item)
    for i in range(len(request_item['query'])):
        request_item['query'][i] = dict(request_item['query'][i])
    for i in range(len(request_item['database'])):
        request_item['database'][i] = dict(request_item['database'][i])

    try:
        fashion_dataset = FashionDataset(request_item['database'])
        service = OutfitMaterTypeAware()
        result = []
        start_time = time.time()
        for item in request_item['query']:
            outfits = fashion_dataset.generate_outfit(item, request_item["topk"], request_item["max_outfits"])
            scores, features = service.get_result(outfits)
            # save features in databases

            if request_item['is_best']:
                best_outfits, best_scores = service.visualize(outfits, scores, request_item["topk"], best=True,
                                                              # output_path=os.path.join(r"E:\workspace\outfit_matcher\2024 SS Outfit", f"{item['item_name']}_best_{param['topk']}.png")
                                                              )
                result.append({"outfits": best_outfits, "scores": best_scores})
            else:
                bad_outfits, bad_scores = service.visualize(outfits, scores, request_item["topk"], best=False,
                                                            # output_path=os.path.join(r"E:\workspace\outfit_matcher\2024 SS Outfit", f"{item['item_name']}_worst_{param['topk']}.png")
                                                            )
                result.append({"outfits": bad_outfits, "scores": bad_scores})
        logger.info(f"run time is : {time.time() - start_time}")
        return {"message": "ok", "data": result}
    except Exception as e:
        return {"message": f"{e}", "data": e}