import json
import os
from typing import List

from numpy import ndarray
from ultralytics.models import YOLO


def import_describe_model() -> YOLO:
    current_folder = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__)))
    neural_network_file = os.path.join(current_folder, "./yolov8n-fashionpedia-1.torchscript")
    return YOLO(neural_network_file, task='detect')


def describe_clothes_batch_opencv_bgr(yolo_model_loaded: YOLO,
                                      pictures_rgb: List[ndarray],
                                      threshold_to_save: float):
    results = yolo_model_loaded(pictures_rgb, verbose=False, conf=threshold_to_save)

    formatted_results = []
    for a_result in results:
        formatted_results.append(json.loads(a_result.tojson()))

    return formatted_results


def describe_single_clothes_opencv_rgb(yolo_model_loaded: YOLO,
                                       one_clothes_picture_rgb: ndarray,
                                       threshold_to_save: float):
    return describe_clothes_batch_opencv_bgr(yolo_model_loaded,
                                             [one_clothes_picture_rgb],
                                             threshold_to_save)[0]