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Merged
luandalmazo merged 1 commit into from
Aug 3, 2026
Merged

Remove deprecated code usage from notebooks (DAT-1041) #131

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40 changes: 2 additions & 38 deletions notebooks/01_getting_started/01_upload_data.ipynb
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Expand Up @@ -326,43 +326,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Get some resources to add to a project\n",
"tutorial_resources = list(api.resources.get_list(\n",
" tags=['tutorial'],\n",
" status='inbox'\n",
"))\n",
"\n",
"if tutorial_resources:\n",
" resource_ids_for_project = [r.id for r in tutorial_resources[:3]] # Take first 3 resources\n",
"\n",
" # Create a new project\n",
" try:\n",
" project_id = api.projects.create(\n",
" name=\"Tutorial Project\",\n",
" description=\"A project created for demonstration purposes\",\n",
" resources_ids=resource_ids_for_project\n",
" )\n",
" project = api.projects.get_by_id(project_id)\n",
"\n",
" print(f\"Created project: {project.name} (ID: {project.id})\")\n",
"\n",
" # List all projects\n",
" all_projects = api.projects.get_list()\n",
" print(f\"\\nAll projects ({len(all_projects)}):\")\n",
" for proj in all_projects:\n",
" print(f\" - {proj.name} (ID: {proj.id})\")\n",
"\n",
" except Exception as e:\n",
" print(f\"Error creating project (may already exist): {e}\")\n",
"\n",
" # Try to find existing project\n",
" existing_project = api.projects.get_by_name(\"Tutorial Project\")\n",
" if existing_project:\n",
" print(f\"Found existing project: {existing_project.name}\")\n",
"else:\n",
" print(\"No tutorial resources found to add to project\")"
]
"source": "# Get some resources to add to a project\ntutorial_resources = list(api.resources.get_list(\n tags=['tutorial'],\n status='inbox'\n))\n\nif tutorial_resources:\n resource_ids_for_project = [r.id for r in tutorial_resources[:3]] # Take first 3 resources\n\n # Create a new project (exists_ok returns the existing project instead of raising)\n project = api.projects.create(\n name=\"Tutorial Project\",\n description=\"A project created for demonstration purposes\",\n resource_ids=resource_ids_for_project,\n exists_ok=True\n )\n\n print(f\"Created project: {project.name} (ID: {project.id})\")\n\n # List all projects\n all_projects = api.projects.get_list()\n print(f\"\\nAll projects ({len(all_projects)}):\")\n for proj in all_projects:\n print(f\" - {proj.name} (ID: {proj.id})\")\nelse:\n print(\"No tutorial resources found to add to project\")"
},
{
"cell_type": "markdown",
Expand Down Expand Up @@ -437,4 +401,4 @@
},
"nbformat": 4,
"nbformat_minor": 2
}
}
31 changes: 2 additions & 29 deletions notebooks/01_getting_started/02_explore_data.ipynb
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Expand Up @@ -445,34 +445,7 @@
"id": "175ee2f9",
"metadata": {},
"outputs": [],
"source": [
"from datetime import date, timedelta\n",
"\n",
"# Filter by annotation type\n",
"category_annotations = api.annotations.get_list(\n",
" resource=selected_resource,\n",
" annotation_type='category'\n",
")\n",
"print(f\"Category annotations: {len(category_annotations)}\")\n",
"\n",
"# Filter by date range\n",
"date_to = date.today()\n",
"date_from = date_to - timedelta(days=30) # Last 30 days\n",
"\n",
"recent_annotations = api.annotations.get_list(\n",
" resource=selected_resource,\n",
" date_from=date_from,\n",
" date_to=date_to\n",
")\n",
"print(f\"Annotations from last 30 days: {len(recent_annotations)}\")\n",
"\n",
"# Filter by status\n",
"published_annotations = api.annotations.get_list(\n",
" resource=selected_resource,\n",
" status='published'\n",
")\n",
"print(f\"Published annotations: {len(published_annotations)}\")"
]
"source": "from datetime import date, timedelta\n\n# Filter by annotation type\ncategory_annotations = api.annotations.get_list(\n resource=selected_resource,\n annotation_type='category'\n)\nprint(f\"Category annotations: {len(category_annotations)}\")\n\n# Filter by date range\ndate_to = date.today()\ndate_from = date_to - timedelta(days=30) # Last 30 days\n\nrecent_annotations = api.annotations.get_list(\n resource=selected_resource,\n from_date=date_from,\n to_date=date_to\n)\nprint(f\"Annotations from last 30 days: {len(recent_annotations)}\")\n\n# Filter by status\npublished_annotations = api.annotations.get_list(\n resource=selected_resource,\n status='published'\n)\nprint(f\"Published annotations: {len(published_annotations)}\")"
},
{
"cell_type": "markdown",
Expand Down Expand Up @@ -516,4 +489,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
}
}
37 changes: 6 additions & 31 deletions notebooks/02_annotations/01_upload_annotations.ipynb
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Expand Up @@ -36,37 +36,21 @@
"id": "3f470fe9",
"metadata": {},
"outputs": [],
"source": [
"from datetime import date\n",
"from tqdm.auto import tqdm\n",
"from datamint import APIHandler\n",
"\n",
"api = APIHandler()\n",
"# resources = list(api.get_resources(project_name=\"Example Project\"))\n",
"# resource_id = resources[0][\"id\"]"
]
"source": "from datamint import Api\n\napi = Api()\n\nPROJECT_NAME = \"Example Project\"\nresources = list(api.resources.get_list(project_name=PROJECT_NAME))\nresource = resources[0]"
},
{
"cell_type": "code",
"execution_count": null,
"id": "cf9bf31f",
"metadata": {},
"outputs": [],
"source": [
"# Adds an annotation to a single resource, associated with a project.\n",
"api.add_annotations(resource_id=resource_id,\n",
" identifier='img-lb1',\n",
" project='Example Project' # You can pass None to use not associated with a project\n",
" )"
]
"source": "from datamint.api.dto import CreateAnnotationDto\nfrom datamint.entities.annotations import AnnotationType\n\n# Adds a label annotation to a single resource\nannotation = CreateAnnotationDto(type=AnnotationType.LABEL, identifier='img-lb1', scope='image')\napi.annotations.create(resource, annotation)\n\n# Associate the resource with a project. Resources aren't tied to a project\n# automatically anymore, so this is a separate, explicit step.\napi.projects.add_resources(resource, project=PROJECT_NAME)"
},
{
"cell_type": "markdown",
"id": "0db3307f",
"metadata": {},
"source": [
"See more details about the function parameter in the documentation [APIHandler.add_annotations](https://sonanceai.github.io/datamint-python-api/datamint.apihandler.html#datamint.apihandler.api_handler.APIHandler.add_annotations)."
]
"source": "See more details about the function parameters in the documentation [AnnotationsApi.create](https://sonanceai.github.io/datamint-python-api/datamint.api.endpoints.html#datamint.api.endpoints.annotations_api.AnnotationsApi.create)."
},
{
"cell_type": "markdown",
Expand All @@ -82,22 +66,13 @@
"id": "b2dc2320",
"metadata": {},
"outputs": [],
"source": [
"# Adds an annotation to a single resource, associated with a project.\n",
"api.add_image_category_annotation(resource_id,\n",
" identifier='img-cls',\n",
" value='cls1',\n",
" project='Example Project' # You can pass None to use not associated with a project\n",
" )"
]
"source": "# Adds an image classification annotation to a single resource\napi.annotations.create_image_classification(resource, identifier='img-cls', value='cls1')\n\n# Associate the resource with a project. Resources aren't tied to a project\n# automatically anymore, so this is a separate, explicit step.\napi.projects.add_resources(resource, project=PROJECT_NAME)"
},
{
"cell_type": "markdown",
"id": "b1746dae",
"metadata": {},
"source": [
"See more details about the function parameter in the documentation [APIHandler.add_image_category_annotation](https://sonanceai.github.io/datamint-python-api/datamint.apihandler.html#datamint.apihandler.api_handler.APIHandler.add_image_category_annotation)."
]
"source": "See more details about the function parameters in the documentation [AnnotationsApi.create_image_classification](https://sonanceai.github.io/datamint-python-api/datamint.api.endpoints.html#datamint.api.endpoints.annotations_api.AnnotationsApi.create_image_classification)."
}
],
"metadata": {
Expand All @@ -113,4 +88,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
}
}
37 changes: 4 additions & 33 deletions notebooks/02_annotations/02_geometry_annotations.ipynb
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Expand Up @@ -111,11 +111,7 @@
"cell_type": "markdown",
"id": "1ab6ebdc",
"metadata": {},
"source": [
"# Creating a Line annotation\n",
"\n",
"Reference: [APIHandler.add_line_annotation](https://sonanceai.github.io/datamint-python-api/datamint.apihandler.html#datamint.apihandler.api_handler.APIHandler.add_line_annotation)"
]
"source": "# Creating a Line annotation\n\nReference: [AnnotationsApi.add_line_annotation](https://sonanceai.github.io/datamint-python-api/datamint.api.endpoints.html#datamint.api.endpoints.annotations_api.AnnotationsApi.add_line_annotation)"
},
{
"cell_type": "code",
Expand Down Expand Up @@ -165,13 +161,7 @@
"cell_type": "markdown",
"id": "f8ba9aaf",
"metadata": {},
"source": [
"# Creating a Box annotation\n",
"\n",
"Reference: [APIHandler.add_box_annotation](https://sonanceai.github.io/datamint-python-api/datamint.apihandler.html#datamint.apihandler.api_handler.APIHandler.add_box_annotation)\n",
"\n",
"First, add a new box/rectangle shape named 'BoundingBox1' in your project settings (similar to the line shape setup above)."
]
"source": "# Creating a Box annotation\n\nReference: [AnnotationsApi.add_box_annotation](https://sonanceai.github.io/datamint-python-api/datamint.api.endpoints.html#datamint.api.endpoints.annotations_api.AnnotationsApi.add_box_annotation)\n\nFirst, add a new box/rectangle shape named 'BoundingBox1' in your project settings (similar to the line shape setup above)."
},
{
"cell_type": "code",
Expand All @@ -192,26 +182,7 @@
"cell_type": "markdown",
"id": "b0b73c10",
"metadata": {},
"source": [
"Both line and box annotations support:\n",
"- **DICOM coordinate conversion**: Automatically convert pixel coordinates to patient coordinates\n",
"- **Patient coordinates**: Direct specification of 3D patient coordinates\n",
"- **Model annotations**: Associate annotations with specific AI models\n",
"\n",
"### Example with DICOM metadata:\n",
"\n",
"```python\n",
"# Assuming you have DICOM metadata\n",
"dicom_path = \"/path/to/your/dicom/file.dcm\"\n",
"api.add_box_annotation((10, 10), (50, 50),\n",
" resource_id=res_id,\n",
" identifier='DicomBox',\n",
" frame_index=0,\n",
" dicom_metadata=dicom_path, # Automatically converts to patient coordinates\n",
" coords_system='pixel',\n",
" project=PROJECT_NAME)\n",
"```"
]
"source": "Both line and box annotations support:\n- **DICOM coordinate conversion**: Automatically convert pixel coordinates to patient coordinates\n- **Patient coordinates**: Direct specification of 3D patient coordinates\n- **Model annotations**: Associate annotations with specific AI models\n\n### Example with DICOM metadata:\n\n```python\n# Assuming you have DICOM metadata\nimport pydicom\n\ndicom_metadata = pydicom.dcmread(\"/path/to/your/dicom/file.dcm\")\napi.annotations.add_box_annotation((10, 10), (50, 50),\n resource=res,\n identifier='DicomBox',\n frame_index=0,\n metadata=dicom_metadata, # Required when coords_system='patient'\n coords_system='patient', # Automatically converts to patient coordinates\n worklist_id=proj.fetch_worklists()[0].id)\n```"
}
],
"metadata": {
Expand All @@ -235,4 +206,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
}
}
11 changes: 2 additions & 9 deletions notebooks/04_experiment_tracking/02_model_registry.ipynb
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Expand Up @@ -225,14 +225,7 @@
"cell_type": "markdown",
"id": "5edb693f",
"metadata": {},
"source": [
"## Next Steps",
"",
"Once you have a model version you're happy with, alias it and deploy it, see",
"`05_deployment/01_deploy_registered_model.ipynb`. Registered models are also created",
"automatically when you pass `--ai-model <name>` to `datamint-upload` with a name that doesn't",
"exist yet."
]
"source": "## Next Steps\n\nOnce you have a model version you're happy with, alias it and deploy it, see\n`05_deployment/01_deploy_registered_model.ipynb`. Registered models are also created\nautomatically when you pass `--ai-model <name>` to `datamint upload` with a name that doesn't\nexist yet."
}
],
"metadata": {
Expand All @@ -256,4 +249,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
}
}
20 changes: 3 additions & 17 deletions notebooks/05_deployment/03_validate_model.ipynb
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Expand Up @@ -65,25 +65,11 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": null,
"id": "e5f6a7b8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Resources : 364\n",
"Box labels: ['Platelets', 'RBC', 'WBC']\n"
]
}
],
"source": [
"dataset = build_dataset(project_name=PROJECT_NAME, allow_external_annotations=True)\n",
"\n",
"print(f\"Resources : {len(dataset.resources)}\")\n",
"print(f\"Box labels: {dataset.box_labels_set}\")"
]
"outputs": [],
"source": "dataset = build_dataset(project=PROJECT_NAME, allow_external_annotations=True)\n\nprint(f\"Resources : {len(dataset.resources)}\")\nprint(f\"Box labels: {dataset.box_labels_set}\")"
},
{
"cell_type": "markdown",
Expand Down
50 changes: 2 additions & 48 deletions notebooks/06_end_to_end/full_3d/02_synapse_nnunet.ipynb
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Expand Up @@ -901,53 +901,7 @@
"id": "315e1ad6",
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# Fetch CT volume\n",
"ct_nifti = r.fetch_file_data(use_cache=True, auto_convert=True)\n",
"ct_vol = ct_nifti.get_fdata()\n",
"\n",
"# Fetch the predicted segmentation (most recent annotation on this resource)\n",
"annotations = list(r.get_annotations())\n",
"pred_ann = annotations[-1]\n",
"pred_vol = pred_ann.fetch_file_data(auto_convert=True, use_cache=True)\n",
"\n",
"SYNAPSE_CLASSES = {\n",
" 1: 'aorta', 2: 'gallbladder', 3: 'spleen',\n",
" 4: 'left_kidney', 5: 'right_kidney', 6: 'liver',\n",
" 7: 'stomach', 8: 'pancreas',\n",
"}\n",
"num_classes = len(SYNAPSE_CLASSES)\n",
"CMAP = plt.get_cmap('tab10', num_classes + 1)\n",
"\n",
"# nnU-Net volumes are (H, W, D) — pick 3 axial slices\n",
"D = ct_vol.shape[2]\n",
"slice_indices = [D // 4, D // 2, 3 * D // 4]\n",
"\n",
"fig, axes = plt.subplots(len(slice_indices), 2, figsize=(10, 4 * len(slice_indices)))\n",
"fig.suptitle(f'nnU-Net inference result — {r.filename}', fontsize=13)\n",
"\n",
"for row, s in enumerate(slice_indices):\n",
" ct_slice = ct_vol[:, :, s]\n",
" pred_slice = pred_vol[:, :, s]\n",
"\n",
" axes[row, 0].imshow(ct_slice, cmap='gray')\n",
" axes[row, 0].set_title(f'CT — axial slice {s}')\n",
" axes[row, 0].axis('off')\n",
"\n",
" axes[row, 1].imshow(ct_slice, cmap='gray')\n",
" axes[row, 1].imshow(pred_slice, cmap=CMAP, alpha=0.5, vmin=0, vmax=num_classes)\n",
" axes[row, 1].set_title('nnU-Net Prediction')\n",
" axes[row, 1].axis('off')\n",
"\n",
"handles = [plt.Rectangle((0, 0), 1, 1, color=CMAP(i + 1)) for i in range(num_classes)]\n",
"fig.legend(handles, list(SYNAPSE_CLASSES.values()), loc='lower center', ncol=4, fontsize=9, title='Organ classes')\n",
"plt.tight_layout()\n",
"plt.show()"
]
"source": "%matplotlib inline\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n# Fetch CT volume\nct_nifti = r.fetch_file_data(use_cache=True, auto_convert=True)\nct_vol = ct_nifti.get_fdata()\n\n# Fetch the predicted segmentation (most recent annotation on this resource)\nannotations = list(r.fetch_annotations())\npred_ann = annotations[-1]\npred_vol = pred_ann.fetch_file_data(auto_convert=True, use_cache=True)\n\nSYNAPSE_CLASSES = {\n 1: 'aorta', 2: 'gallbladder', 3: 'spleen',\n 4: 'left_kidney', 5: 'right_kidney', 6: 'liver',\n 7: 'stomach', 8: 'pancreas',\n}\nnum_classes = len(SYNAPSE_CLASSES)\nCMAP = plt.get_cmap('tab10', num_classes + 1)\n\n# nnU-Net volumes are (H, W, D) — pick 3 axial slices\nD = ct_vol.shape[2]\nslice_indices = [D // 4, D // 2, 3 * D // 4]\n\nfig, axes = plt.subplots(len(slice_indices), 2, figsize=(10, 4 * len(slice_indices)))\nfig.suptitle(f'nnU-Net inference result — {r.filename}', fontsize=13)\n\nfor row, s in enumerate(slice_indices):\n ct_slice = ct_vol[:, :, s]\n pred_slice = pred_vol[:, :, s]\n\n axes[row, 0].imshow(ct_slice, cmap='gray')\n axes[row, 0].set_title(f'CT — axial slice {s}')\n axes[row, 0].axis('off')\n\n axes[row, 1].imshow(ct_slice, cmap='gray')\n axes[row, 1].imshow(pred_slice, cmap=CMAP, alpha=0.5, vmin=0, vmax=num_classes)\n axes[row, 1].set_title('nnU-Net Prediction')\n axes[row, 1].axis('off')\n\nhandles = [plt.Rectangle((0, 0), 1, 1, color=CMAP(i + 1)) for i in range(num_classes)]\nfig.legend(handles, list(SYNAPSE_CLASSES.values()), loc='lower center', ncol=4, fontsize=9, title='Organ classes')\nplt.tight_layout()\nplt.show()"
}
],
"metadata": {
Expand All @@ -971,4 +925,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
}
}
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