diff --git a/datamint/dataset/base_dataset.py b/datamint/dataset/base_dataset.py
index 9e998c12..f9a70b11 100644
--- a/datamint/dataset/base_dataset.py
+++ b/datamint/dataset/base_dataset.py
@@ -225,26 +225,34 @@ def _handle_dataset_download_or_update(self, local_load_success: bool) -> None:
         else:
             self._check_version()
 
+    def _init_metainfo(self) -> None:
+        # get the server info
+        self.project_info = self.get_info()
+        self.metainfo = self._get_datasetinfo().asdict().copy()
+        self.metainfo['updated_at'] = None
+        self.metainfo['resources'] = []
+        self.metainfo['all_annotations'] = self.all_annotations
+        self.images_metainfo = self.metainfo['resources']
+
     def _load_metadata(self) -> bool:
         """Load and process dataset metadata."""
         if hasattr(self, 'metainfo'):
             _LOGGER.warning("Metadata already loaded.")
         metadata_path = os.path.join(self.dataset_dir, 'dataset.json')
         if not os.path.isfile(metadata_path):
-            # get the server info
-            self.project_info = self.get_info()
-            self.metainfo = self._get_datasetinfo().asdict().copy()
-            self.metainfo['updated_at'] = None
-            self.metainfo['resources'] = []
-            self.metainfo['all_annotations'] = self.all_annotations
-            self.images_metainfo = self.metainfo['resources']
+            self._init_metainfo()
             return False
         else:
             with open(metadata_path, 'r') as file:
                 self.metainfo = json.load(file)
         self.images_metainfo = self.metainfo['resources']
         # Convert annotations from dict to Annotation objects
-        self._convert_metainfo_to_clsobj()
+        try:
+            self._convert_metainfo_to_clsobj()
+        except Exception as e:
+            _LOGGER.warning(f"Failed to convert annotations. Redownloading dataset. {type(e)}")
+            self._init_metainfo()
+            return False
         return True
 
     def _convert_metainfo_to_clsobj(self):
@@ -552,13 +560,12 @@ def get_info(self) -> dict:
         """Get project information from API."""
         if hasattr(self, 'project_info') and self.project_info is not None:
             return self.project_info
-        project = self.api.projects.get_by_name(self.project_name).asdict()
-        if 'error' in project:
-            available_projects = project['all_projects']
+        project = self.api.projects.get_by_name(self.project_name)
+        if project is None:
             raise DatamintDatasetException(
-                f"Project with name '{self.project_name}' not found. "
-                f"Available projects: {available_projects}"
+                f"Project with name '{self.project_name}' not found."
             )
+        project = project.asdict()
         self.project_info = project
         self.dataset_id = project['dataset_id']
         return project
@@ -898,8 +905,8 @@ def _incremental_update(self) -> None:
         ################
 
         ### ANNOTATIONS ###
-        all_annotations = self.api.annotations.get_list(worklist_id=self.project_info['worklist_id'],
-                                                        status='published' if self.all_annotations else None)
+        all_annotations = self.api.annotations.get_list(worklist_id=None if self.all_annotations else self.project_info['worklist_id'],
+                                                        status=None if self.all_annotations else 'published')
 
         # group annotations by resource ID
         annotations_by_resource: dict[str, list[Annotation]] = {}
diff --git a/notebooks/dataset_loading.ipynb b/notebooks/dataset_loading.ipynb
index 5ccbe771..85d1bb5b 100644
--- a/notebooks/dataset_loading.ipynb
+++ b/notebooks/dataset_loading.ipynb
@@ -63,13 +63,10 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Setup-up example Project and data (optional)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
+    "## Setup-up example Project and data (optional)\n",
+    "\n",
+    "You can skip this step if you already have a project set up.\n",
+    "\n",
     "Creating the example project:"
    ]
   },
@@ -88,6 +85,32 @@
     "print(f\"Check your project at {proj.url}\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Get existing Project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datamint import Api\n",
+    "\n",
+    "PROJECT_NAME = 'My Project Name'  # change to your project name\n",
+    "\n",
+    "api = Api()\n",
+    "proj = api.projects.get_by_name(PROJECT_NAME)  # proj is a Project object with proper attributes and type hints\n",
+    "if proj is None:\n",
+    "    _LOGGER.error(f\"Project with name '{PROJECT_NAME}' not found.\")\n",
+    "else:\n",
+    "    # but you can convert to a dictionary if you want\n",
+    "    display(proj.asdict())"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -113,6 +136,7 @@
     "D = Dataset(\n",
     "    project_name=PROJECT_NAME,\n",
     "    return_as_semantic_segmentation=True,\n",
+    "    all_annotations=True\n",
     ") # This automatically downloads the dataset if needed\n",
     "print('Dataset length:', len(D))"
    ]
@@ -133,22 +157,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[09/18/25 16:57:44] </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Original image is uint16, converting to uint8                      <a href=\"file:///home/lhsmello/projects/Sonance/datamint-python-api/datamint/dataset/base_dataset.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">base_dataset.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/lhsmello/projects/Sonance/datamint-python-api/datamint/dataset/base_dataset.py#668\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">668</span></a>\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[2;36m[09/18/25 16:57:44]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Original image is uint16, converting to uint8                      \u001b]8;id=502300;file:///home/lhsmello/projects/Sonance/datamint-python-api/datamint/dataset/base_dataset.py\u001b\\\u001b[2mbase_dataset.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=369607;file:///home/lhsmello/projects/Sonance/datamint-python-api/datamint/dataset/base_dataset.py#668\u001b\\\u001b[2m668\u001b[0m\u001b]8;;\u001b\\\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -178,7 +189,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -187,7 +198,7 @@
        "dict_keys(['id', 'resource_uri', 'storage', 'location', 'upload_channel', 'filename', 'modality', 'mimetype', 'size', 'upload_mechanism', 'customer_id', 'status', 'created_at', 'created_by', 'published', 'deleted', 'source_filepath', 'metadata', 'projects', 'published_on', 'published_by', 'tags', 'publish_transforms', 'deleted_at', 'deleted_by', 'instance_uid', 'series_uid', 'study_uid', 'patient_id', 'segmentations', 'measurements', 'categories', 'user_info', 'labels', 'file'])"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -212,16 +223,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7fea1ae93e60>"
+       "<matplotlib.image.AxesImage at 0x7f1e50a87410>"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -251,16 +262,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'lucas@mail.com': torch.Size([10, 2, 64, 64])}"
+       "{}"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -295,18 +306,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
+       "{}"
       ]
      },
+     "execution_count": 8,
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "segmentations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "'lucas@mail.com'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[6], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m my_segs \u001b[38;5;241m=\u001b[39m \u001b[43msegmentations\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mlucas@mail.com\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m      2\u001b[0m seg_mask_i \u001b[38;5;241m=\u001b[39m my_segs[\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1\u001b[39m]  \u001b[38;5;66;03m# second frame, first label ([1,0] is background)\u001b[39;00m\n\u001b[1;32m      3\u001b[0m label_name \u001b[38;5;241m=\u001b[39m D\u001b[38;5;241m.\u001b[39msegmentation_labels_set[\u001b[38;5;241m0\u001b[39m]  \u001b[38;5;66;03m# Note: segmentation_labels_set does not include background.\u001b[39;00m\n",
+      "\u001b[0;31mKeyError\u001b[0m: 'lucas@mail.com'"
+     ]
     }
    ],
    "source": [
diff --git a/pyproject.toml b/pyproject.toml
index 34dfedef..51e90333 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 [project]
 name = "datamint"
 description = "A library for interacting with the Datamint API, designed for efficient data management, processing and Deep Learning workflows."
-version = "2.0.0"
+version = "2.0.1"
 dynamic = ["dependencies"]
 requires-python = ">=3.10"
 readme = "README.md"