add download big engine file to cdn manager

revise onnx export process
fixes

train.py

@@ -7,12 +7,13 @@ from datetime import datetime
 from os import path, replace, listdir, makedirs, scandir
 from os.path import abspath
 from pathlib import Path
+from time import sleep
 
 import yaml
 from ultralytics import YOLO
 
 import constants
-from azaion_api import ApiCredentials, Api
+from api_client import ApiCredentials, ApiClient
 from cdn_manager import CDNCredentials, CDNManager
 from constants import (processed_images_dir,
                        processed_labels_dir,
@@ -20,10 +21,11 @@ from constants import (processed_images_dir,
                        datasets_dir, models_dir,
                        corrupted_images_dir, corrupted_labels_dir, sample_dir)
 from dto.annotationClass import AnnotationClass
+from inference.onnx_engine import OnnxEngine
 
 from security import Security
 from utils import Dotdict
-from exports import export_tensorrt, upload_model
+from exports import export_tensorrt, upload_model, export_onnx
 
 today_folder = f'{prefix}{datetime.now():{date_format}}'
 today_dataset = path.join(datasets_dir, today_folder)
@@ -224,10 +226,11 @@ if __name__ == '__main__':
     # validate(path.join('runs', 'detect', 'train7', 'weights', 'best.pt'))
     # form_data_sample(500)
     # convert2rknn()
-    model_path = 'azaion.pt'
-    export_tensorrt(model_path)
-    engine_model_path = f'{Path(model_path).stem}.engine'
-    upload_model(engine_model_path, engine_model_path)
+    api_client = ApiClient()
+    onnx_path = export_onnx('azaion.pt')
 
-    onnx_model_path = f'{Path(model_path).stem}.onnx'
-    upload_model(onnx_model_path, onnx_model_path)
+    with open(onnx_path, 'rb') as binary_file:
+        onnx_bytes = binary_file.read()
+
+    key = Security.get_model_encryption_key()
+    api_client.upload_big_small_resource(onnx_bytes, onnx_path, constants.MODELS_FOLDER, key)