final upload

validation.ipynb

@@ -69,7 +69,7 @@
     "import torch.backends.cudnn as cudnn\n",
     "import torchvision.transforms as transforms\n",
     "\n",
-    "from data import cityscapes\n",
+    "from data import cityscapes, acdc, semantickitti, cadedgetune\n",
     "import util.misc as misc\n",
     "\n",
     "from models.vae import AutoencoderKL\n",
@@ -148,7 +148,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "id": "28d13453-a3ac-4d2e-8906-0c179e85c2f9",
    "metadata": {
     "tags": []
@@ -161,9 +161,9 @@
     "])\n",
     "\n",
     "dataset_train = cityscapes.CityScapes('dataset/CityScapes/vallist.txt', data_set= 'val', transform=transform_train, seed=args.seed, img_size=args.img_size)\n",
-    "# dataset_train = umbc.UMBC('dataset/UMBC/all.txt', data_set= 'val', transform=transform_train, seed=args.seed, img_size=args.img_size)\n",
     "# dataset_train = acdc.ACDC('dataset/ACDC/vallist_fog.txt', data_set= 'val', transform=transform_train, seed=args.seed, img_size=args.img_size)\n",
     "# dataset_train = semantickitti.SemanticKITTI('dataset/SemanticKitti/vallist.txt', data_set= 'val', transform=transform_train, seed=args.seed, img_size=args.img_size)\n",
+    "# dataset_train = cadedgetune.CADEdgeTune('dataset/CADEdgeTune/all.txt', data_set= 'val', transform=transform_train, seed=args.seed, img_size=args.img_size)\n",
     "\n",
     "\n",
     "sampler_train = torch.utils.data.DistributedSampler(dataset_train, num_replicas=1, rank=0, shuffle=False)\n",