model/src/main.py

@@ -21,6 +21,7 @@ if __name__ == '__main__':
     model.eval()
     # setup dataset
     dataset = VCDADataset(
+        minio_client=minio_client,
         data_name_list=[
             '02dbaf48d713e4e6d3a6b98fd2dc866e',
         ],

model/src/utils/vcda_dataset.py

@@ -2,6 +2,7 @@
 
 import random
 
+from minio import Minio
 from PIL import Image
 from torch import Tensor
 from torch.utils.data import Dataset
@@ -15,7 +16,7 @@ from torchvision.transforms.functional import (
     to_tensor,
 )
 
-from shared.data_store import connect, get_image
+from shared.data_store import get_image
 
 # resnet18 original normalization values
 RESNET_NORMALIZE_MEAN = [0.485, 0.456, 0.406]
@@ -27,11 +28,13 @@ class VCDADataset(Dataset):
 
     def __init__(
         self,
+        minio_client: Minio,
         data_name_list: list[str],
         do_augment: bool = False,
         random_annotations: bool = False,
     ):
         super().__init__()
+        self.minio_client = minio_client
         self.data_name_list = data_name_list
         self.do_augment = do_augment
         self.random_annotations = random_annotations
@@ -47,9 +50,6 @@ class VCDADataset(Dataset):
             contrast=8e-2,
             saturation=8e-2,
         )
-        # connect to minio
-        minio_client = connect()
-        self.minio_client = minio_client
 
     def __len__(self):
         return len(self.data_name_list)