"""
  rbs_train2
  Общая задача: web-service pipeline
  Реализуемая функция: обучение нейросетевой модели по заданному BOP-датасету

    python3 $PYTHON_EDUCATION --path /home/user/webservice/server/build/public/process/proc/inst_proc \
        --form /home/user/webservice/server/build/public/process/proc/inst_proc/form.json

  28.01.2025 @shalenikol release 0.1
  17.02.2025 @shalenikol release 0.2 addon_dir
"""
import argparse
import os
import json
from train_Yolo import train_YoloV8
from train_Dope import train_Dope_i

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--path", required=True, help="Output path for weights")
    parser.add_argument("--form", required=True, help="Json-file with training parameters")
    args = parser.parse_args()

    if not os.path.isdir(args.path):
        print(f"Invalid output path '{args.path}'")
        exit(-1)
    wname = os.path.basename(args.path)
    outpath = os.path.dirname(args.path)

    if not os.path.isfile(args.form):
        print(f"Error: no such file '{args.form}'")
        exit(-2)
    with open(args.form, "r") as f:
        j_data = f.read()
    try:
        cfg = json.loads(j_data)
    except json.JSONDecodeError as e:
        print(f"JSon error: {e}")
        exit(-3)

    cfg = cfg["output"] # edited params
    dataset_params = cfg["process"]["selectProcess"]["value"]
    dataset_type = dataset_params["type"]
    if dataset_type != "BOP_DATASET":
        print(f"Error: Invalid dataset type '{dataset_type}'")
        exit(-4)
    dataset_name = dataset_params["instanceName"]
    dataset_path = dataset_params["path"]
    dataset_path = dataset_path.replace("//", "/") # !!! TODO !!! Nikita

    epoch = cfg["n_epoch"]
    pretrain = (cfg["pretrain"] == "True") #False
    ttype = cfg["typeWeight"] #"ObjectDetection"

    addon_dir = ""
    if "addon" in cfg:
        addon = cfg["addon"].strip()
        if addon and os.path.isdir(addon):
            addon_dir = addon

    if ttype == "ObjectDetection":
        train_YoloV8(dataset_path, wname, dataset_name, outpath, epoch, pretrain, addon_dir)
    else:
        train_Dope_i(dataset_path, wname, dataset_name, outpath, epoch, pretrain)