fix tensor rt engine

exports.py

@@ -0,0 +1,95 @@
+import shutil
+from os import path, scandir, makedirs
+from pathlib import Path
+import random
+import netron
+import yaml
+from ultralytics import YOLO
+
+import constants
+from azaion_api import Api, ApiCredentials
+from cdn_manager import CDNManager, CDNCredentials
+from constants import datasets_dir, processed_images_dir
+from security import Security
+from utils import Dotdict
+
+
+def export_rknn(model_path):
+    model = YOLO(model_path)
+    model.export(format="rknn", name="rk3588", simplify=True)
+    model_stem = Path(model_path).stem
+    folder_name = f'{model_stem}_rknn_model'
+    shutil.move(path.join(folder_name, f'{Path(model_path).stem}-rk3588.rknn'), f'{model_stem}.rknn')
+    shutil.rmtree(folder_name)
+    pass
+
+
+def export_onnx(model_path):
+    model = YOLO(model_path)
+    model.export(
+        format="onnx",
+        imgsz=1280,
+        batch=2,
+        simplify=True,
+        nms=True)
+    return Path(model_path).stem + '.onnx'
+
+
+def export_tensorrt(model_path):
+    YOLO(model_path).export(
+        format='engine',
+        batch=4,
+        half=True,
+        simplify=True,
+        nms=True
+    )
+
+
+def form_data_sample(destination_path, size=500, write_txt_log=False):
+    images = []
+    with scandir(processed_images_dir) as imd:
+        for image_file in imd:
+            if not image_file.is_file():
+                continue
+            images.append(image_file)
+    print('shuffling images')
+    random.shuffle(images)
+    images = images[:size]
+
+    shutil.rmtree(destination_path, ignore_errors=True)
+    makedirs(destination_path, exist_ok=True)
+
+    lines = []
+    for image in images:
+        shutil.copy(image.path, path.join(destination_path, image.name))
+        lines.append(f'./{image.name}')
+    if write_txt_log:
+        with open(path.join(destination_path, 'azaion_subset.txt'), 'w', encoding='utf-8') as f:
+            f.writelines([f'{line}\n' for line in lines])
+
+
+def show_model(model: str = None):
+    netron.start(model)
+
+
+def upload_model(model_path: str, filename: str, size_small_in_kb: int=3):
+    with open(model_path, 'rb') as f_in:
+        model_bytes = f_in.read()
+
+    key = Security.get_model_encryption_key()
+    model_encrypted = Security.encrypt_to(model_bytes, key)
+
+    part1_size = min(size_small_in_kb * 1024, int(0.9 * len(model_encrypted)))
+    model_part_small = model_encrypted[:part1_size]  # slice bytes for part1
+    model_part_big = model_encrypted[part1_size:]
+
+    with open(constants.CONFIG_FILE, "r") as f:
+        config_dict = yaml.safe_load(f)
+        d_config = Dotdict(config_dict)
+        cdn_c = Dotdict(d_config.cdn)
+        api_c = Dotdict(d_config.api)
+    cdn_manager = CDNManager(CDNCredentials(cdn_c.host, cdn_c.access_key, cdn_c.secret_key))
+    cdn_manager.upload(cdn_c.bucket, f'{filename}.big', model_part_big)
+
+    api = Api(ApiCredentials(api_c.url, api_c.user, api_c.pw, api_c.folder))
+    api.upload_file(f'{filename}.small', model_part_small)