Deploy layer rework #97

.vscode/settings.json

@@ -1,30 +1,51 @@
 {
-	"files.exclude": {
-		"**/__pycache__": true,
-		"build": true,
-		"supervisely.egg-info": true,
-		".venv": true
-	},
-	"python.defaultInterpreterPath": ".venv/bin/python",
-	"editor.formatOnSave": true,
-	"editor.formatOnPaste": true,
-	"editor.formatOnType": true,
-	"black-formatter.args": ["--line-length", "100"],
-	"[html]": {
-		"editor.defaultFormatter": "esbenp.prettier-vscode"
-	},
-	"[json]": {
-		"editor.defaultFormatter": "esbenp.prettier-vscode"
-	},
-	"[python]": {
-		"editor.defaultFormatter": "ms-python.black-formatter"
-	},
-	"debug.inlineValues": "off",
-	"python.analysis.typeCheckingMode": "off",
-	"python.analysis.autoImportCompletions": false,
-	"autoDocstring.docstringFormat": "sphinx",
-	"autoDocstring.customTemplatePath": "docs/.mustache",
-	"python.testing.pytestArgs": ["tests/inference_cache"],
-	"python.testing.unittestEnabled": false,
-	"python.testing.pytestEnabled": true
-}
+    "files.exclude": {
+        "**/__pycache__": true,
+        "build": true,
+        "supervisely.egg-info": true,
+        ".venv": true
+    },
+    "python.defaultInterpreterPath": ".venv/bin/python",
+    "editor.formatOnSave": true,
+    "editor.formatOnPaste": true,
+    "editor.formatOnType": true,
+    "black-formatter.args": [
+        "--line-length",
+        "100"
+    ],
+    "[html]": {
+        "editor.defaultFormatter": "vscode.html-language-features"
+    },
+    "[json]": {
+        "editor.defaultFormatter": "esbenp.prettier-vscode"
+    },
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter",
+        "editor.formatOnSave": true,
+        "editor.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+        },
+    },
+    "isort.args": [
+        "--profile",
+        "black"
+    ],
+    "debug.inlineValues": "off",
+    "python.analysis.typeCheckingMode": "off",
+    "python.analysis.autoImportCompletions": false,
+    "autoDocstring.docstringFormat": "sphinx",
+    "autoDocstring.customTemplatePath": "docs/.mustache",
+    "python.testing.pytestArgs": [
+        "tests/inference_cache"
+    ],
+    "python.testing.unittestEnabled": false,
+    "python.testing.pytestEnabled": true,
+    "workbench.colorCustomizations": {
+        "minimap.errorHighlight": "#ff0000",
+        "editorOverviewRuler.errorForeground": "#ff0000",
+        "editorOverviewRuler.warningForeground": "#ff9900",
+        "minimap.warningHighlight": "#ff9900",
+        "minimap.infoHighlight": "#00a8aa",
+        "editorOverviewRuler.infoForeground": "#00a8aa"        
+    }
+}

README.md

@@ -94,6 +94,7 @@ This application is a versatile tool designed for data transformation tasks (lik
 | [Deploy MMDetection](https://github.com/supervisely-ecosystem/data-nodes/blob/master/src/ui/dtl/actions/neural_networks/deploy/mmdetection.md)                                                                              | Deploy pretrained or custom MMDetection model.                                             | +      | -      |
 | [Deploy MMSegmentation](https://github.com/supervisely-ecosystem/data-nodes/blob/master/src/ui/dtl/actions/neural_networks/deploy/mmsegmentation.md)                                                                        | Deploy pretrained or custom MMSegmentation model.                                          | +      | -      |
 | [Deploy RT-DETR](https://github.com/supervisely-ecosystem/data-nodes/blob/master/src/ui/dtl/actions/neural_networks/deploy/rtdetr.md)                                                                                       | Deploy pretrained or custom RT-DETR model.                                                 | +      | -      |
+| [Deploy RT-DETRv2](https://github.com/supervisely-ecosystem/data-nodes/blob/master/src/ui/dtl/actions/neural_networks/deploy/rtdetrv2.md)                                                                                   | Deploy pretrained or custom RT-DETRv2 model.                                               | +      | -      |
 | **Other**                                                                                                                                                                                                                   |                                                                                            |        |        |
 | [Dummy](https://github.com/supervisely-ecosystem/data-nodes/blob/master/src/ui/dtl/actions/other/dummy/README.md#dummy)                                                                                                     | Dummy node. Do nothing. Can be used to merge layers.                                       | +      | -      |
 | [Dataset](https://github.com/supervisely-ecosystem/data-nodes/blob/master/src/ui/dtl/actions/other/dataset/README.md#dataset)                                                                                               | All data will be put into a single dataset.                                                | +      | -      |

config.json

@@ -4,7 +4,7 @@
 	"description": "[Beta] Drag and drop interface for building custom DataOps pipelines",
 	"entrypoint": "python -m uvicorn src.main:app --host 0.0.0.0 --port 8000",
 	"headless": false,
-	"docker_image": "supervisely/data-nodes:1.0.26",
+	"docker_image": "supervisely/data-nodes:1.0.27",
 	"modal_template": "src/modal.html",
 	"modal_template_state": {
 		"modalityType": "images"

src/compute/layers/processing/DeployLayer.py

@@ -237,3 +237,38 @@ class DeployRTDETRLayer(DeployLayer):
             },
         },
     }
+
+
+class DeployRTDETRv2Layer(DeployLayer):
+    action = "deploy_rtdetrv2"
+    title = "Deploy RT-DETRv2"
+
+    layer_settings = {
+        "required": ["settings"],
+        "properties": {
+            "settings": {
+                "type": "object",
+                "required": [
+                    "session_id",
+                    "agent_id",
+                    "device",
+                    "model_source",
+                    "checkpoint_name",
+                    "task_type",
+                    "checkpoint_url",
+                    "stop_model_session",
+                ],
+                "properties": {
+                    "session_id": {"type": "integer"},
+                    "agent_id": {"type": "integer"},
+                    "device": {"type": "string"},
+                    "model_source": {"type": "string"},
+                    "task_type": {"type": "string"},
+                    "checkpoint_name": {"type": "string"},
+                    "checkpoint_url": {"oneOf": [{"type": "string"}, {"type": "null"}]},
+                    "runtime": {"type": "string"},
+                    "stop_model_session": {"type": "boolean"},
+                },
+            },
+        },
+    }

src/ui/dtl/__init__.py

@@ -83,7 +83,8 @@
     DeployYOLOV8Action,
     DeployMMDetectionAction,
     DeployMMSegmentationAction,
-    DeployRTETRAction,
+    DeployRTDETRAction,
+    DeployRTDETRv2Action,
 )
 from .actions.neural_networks.apply_nn_inference.apply_nn_inference import ApplyNNInferenceAction
 
@@ -224,7 +225,8 @@
         DeployYOLOV8Action.name,
         DeployMMDetectionAction.name,
         DeployMMSegmentationAction.name,
-        DeployRTETRAction.name,
+        DeployRTDETRAction.name,
+        DeployRTDETRv2Action.name,
         ApplyNNInferenceAction.name,
     ],
     OTHER: [
@@ -307,7 +309,8 @@
     DeployYOLOV8Action.name: DeployYOLOV8Action,
     DeployMMDetectionAction.name: DeployMMDetectionAction,
     DeployMMSegmentationAction.name: DeployMMSegmentationAction,
-    DeployRTETRAction.name: DeployRTETRAction,
+    DeployRTDETRAction.name: DeployRTDETRAction,
+    DeployRTDETRv2Action.name: DeployRTDETRv2Action,
     ApplyNNInferenceAction.name: ApplyNNInferenceAction,
     # Other layers
     DatasetAction.name: DatasetAction,

src/ui/dtl/actions/neural_networks/deploy/deploy.py

@@ -2,6 +2,7 @@
 from os.path import realpath, dirname
 from supervisely import logger
 from supervisely.nn.inference.session import Session
+from supervisely.nn.experiments import get_experiment_infos
 
 from src.ui.dtl.Layer import Layer
 
@@ -39,6 +40,10 @@
     rtdetr as pretrained_rtdetr,
 )
 
+from src.ui.dtl.actions.neural_networks.deploy.layout.pretrained_models import (
+    rtdetrv2 as pretrained_rtdetrv2,
+)
+
 
 class DeployBaseAction(DeployNNAction):
     name = "deploy_base"
@@ -124,7 +129,11 @@ def agent_selector_sidebar_save_btn_cb():
         # -----------------------------
 
         # MODEL SELECTOR
-        custom_models = cls.artifacts.get_list()
+
+        if cls.train_version == "v2":
+            custom_models = get_experiment_infos(g.api, g.TEAM_ID, cls.framework_name)
+        else:
+            custom_models = cls.artifacts.get_list_experiment_info()
         (
             # sidebar
             # custom options
@@ -146,7 +155,9 @@ def agent_selector_sidebar_save_btn_cb():
             model_selector_layout_container,
             model_selector_stop_model_after_pipeline_checkbox,
         ) = create_model_selector_widgets(
-            cls.framework_name, cls.pretrained_models, custom_models, cls.custom_task_types
+            cls.framework_name,
+            cls.pretrained_models,
+            custom_models,
         )
         if cls.need_runtime_selector is False:
             model_selector_runtime_field.hide()
@@ -163,9 +174,13 @@ def model_selector_sidebar_save_btn_cb():
                 model_selector_runtime_selector_sidebar,
                 model_selector_sidebar_custom_model_table,
                 model_selector_stop_model_after_pipeline_checkbox,
+                cls.train_version,
             )
             utils.set_model_selector_preview(
-                saved_settings, model_selector_preview, model_selector_preview_type
+                saved_settings,
+                model_selector_preview,
+                model_selector_preview_type,
+                cls.train_version,
             )
 
         # -----------------------------
@@ -211,8 +226,7 @@ def model_serve_btn_cb():
             utils.set_model_serve_preview("", model_serve_preview)
             # add validation
             success = utils.validate_settings(
-                saved_settings,
-                model_serve_preview,
+                saved_settings, model_serve_preview, cls.train_version
             )
             if not success:
                 agent_selector_layout_edit_btn.enable()
@@ -228,7 +242,7 @@ def model_serve_btn_cb():
             g.api.app.wait_until_ready_for_api_calls(session.task_id, 10, 10)
             try:
                 utils.set_model_serve_preview("Deploying model...", model_serve_preview)
-                utils.deploy_model(g.api, session.task_id, saved_settings)
+                utils.deploy_model(g.api, session.task_id, saved_settings, cls.train_version)
                 logger.info(f"Session ID: {session.task_id} has been deployed")
 
                 app_link_message = (
@@ -274,6 +288,7 @@ def _save_settings() -> dict:
                 model_selector_runtime_selector_sidebar,
                 model_selector_sidebar_custom_model_table,
                 model_selector_stop_model_after_pipeline_checkbox,
+                cls.train_version,
             )
 
         def get_settings(options_json: dict) -> dict:
@@ -342,13 +357,13 @@ class DeployYOLOV5Action(DeployBaseAction):
     title = "Deploy YOLOv5"
     description = "Deploy YOLOv5 models."
     md_description = DeployBaseAction.read_md_file(dirname(realpath(__file__)) + "/yolov5.md")
+    train_version = "v1"
 
     # Framework settings
     framework = "yolov5"
     framework_name = "YOLOv5"
     slug = "supervisely-ecosystem/yolov5_2.0/serve"
     artifacts = YOLOv5v2(g.TEAM_ID)
-    custom_task_types = ["object detection"]
     pretrained_models = pretrained_yolov5
 
 
@@ -358,13 +373,13 @@ class DeployYOLOV8Action(DeployBaseAction):
     description = "Deploy YOLO v8 | v9 | v10 | v11 models."
     md_description = DeployBaseAction.read_md_file(dirname(realpath(__file__)) + "/yolov8.md")
     need_runtime_selector = True
+    train_version = "v1"
 
     # Framework settings
     framework = "yolov8"
     framework_name = "YOLOv8"
     slug = "supervisely-ecosystem/yolov8/serve"
     artifacts = YOLOv8(g.TEAM_ID)
-    custom_task_types = ["object detection", "instance segmentation", "pose estimation"]
     pretrained_models = pretrained_yolov8
 
 
@@ -373,13 +388,13 @@ class DeployMMDetectionAction(DeployBaseAction):
     title = "Deploy MMDetection"
     description = "Deploy MMDetection models."
     md_description = DeployBaseAction.read_md_file(dirname(realpath(__file__)) + "/mmdetection.md")
+    train_version = "v1"
 
     # Framework settings
     framework = "mmdetection3"
     framework_name = "MMDetection"
     slug = "supervisely-ecosystem/serve-mmdetection-v3"
     artifacts = MMDetection3(g.TEAM_ID)
-    custom_task_types = ["object detection", "instance segmentation"]
     pretrained_models = pretrained_mmdetection3
 
 
@@ -390,27 +405,43 @@ class DeployMMSegmentationAction(DeployBaseAction):
     md_description = DeployBaseAction.read_md_file(
         dirname(realpath(__file__)) + "/mmsegmentation.md"
     )
+    train_version = "v1"
 
     # Framework settings
     framework = "mmsegmentation"
     framework_name = "MMSegmentation"
     slug = "supervisely-ecosystem/mmsegmentation/serve"
     artifacts = MMSegmentation(g.TEAM_ID)
-    custom_task_types = ["semantic segmentation"]
     pretrained_models = pretrained_mmsegmentation
 
 
-class DeployRTETRAction(DeployBaseAction):
+class DeployRTDETRAction(DeployBaseAction):
     name = "deploy_rtdetr"
     title = "Deploy RT-DETR"
     description = "Deploy RT-DETR models."
     md_description = DeployBaseAction.read_md_file(dirname(realpath(__file__)) + "/rtdetr.md")
+    train_version = "v1"
 
     # Framework settings
     framework = "rtdetr"
     framework_name = "RT-DETR"
     slug = "supervisely-ecosystem/rt-detr/supervisely_integration/serve"
     artifacts = RTDETR(g.TEAM_ID)
-    custom_task_types = ["object detection"]
     pretrained_models = pretrained_rtdetr
     need_runtime_selector = True
+
+
+class DeployRTDETRv2Action(DeployBaseAction):
+    name = "deploy_rtdetrv2"
+    title = "Deploy RT-DETRv2"
+    description = "Deploy RT-DETRv2 models."
+    md_description = DeployBaseAction.read_md_file(dirname(realpath(__file__)) + "/rtdetrv2.md")
+    train_version = "v2"
+
+    # Framework settings
+    framework = "rtdetrv2"
+    framework_name = "RT-DETRv2"
+    slug = "supervisely-ecosystem/rt-detrv2/supervisely_integration/serve"
+    artifacts = None
+    pretrained_models = pretrained_rtdetrv2
+    need_runtime_selector = True

src/ui/dtl/actions/neural_networks/deploy/layout/model_selector.py

@@ -3,13 +3,14 @@
     Button,
     Container,
     RadioTabs,
-    CustomModelsSelector,
+    ExperimentSelector,
     PretrainedModelsSelector,
     Checkbox,
     Select,
     Field,
 )
 from supervisely.nn.inference import RuntimeType
+from supervisely.nn.utils import ModelSource
 import src.globals as g
 from src.ui.dtl.utils import (
     get_text_font_size,
@@ -25,23 +26,14 @@ def get_available_runtimes():
 
 
 def create_model_selector_widgets(
-    framework_name: str, pretrained_models: list, custom_models: list, custom_task_types: list = []
+    framework_name: str,
+    pretrained_models: list,
+    custom_models: list,
 ):
     # SIDEBAR
 
     # CUSTOM MODEL OPTION SUPERVISELY
-    need_custom_task_types = len(custom_task_types) > 0
-
-    model_selector_sidebar_custom_model_table = CustomModelsSelector(
-        g.TEAM_ID,
-        custom_models,
-        need_custom_task_types,
-        custom_task_types,
-    )
-
-    custom_models_task_types = model_selector_sidebar_custom_model_table.get_available_task_types()
-    if "object detection" in custom_models_task_types:
-        model_selector_sidebar_custom_model_table.set_active_task_type("object detection")
+    model_selector_sidebar_custom_model_table = ExperimentSelector(g.TEAM_ID, custom_models)
     # ------------------------------
 
     # PUBLIC MODEL OPTIONS
@@ -66,7 +58,7 @@ def create_model_selector_widgets(
 
     # CUSTOM /PUBLIC TABS
     model_selector_sidebar_model_source_tabs = RadioTabs(
-        titles=["Custom models", "Pretrained public models"],
+        titles=[ModelSource.CUSTOM, ModelSource.PRETRAINED],
         descriptions=["Models trained by you", f"Models trained by {framework_name} team"],
         contents=[
             model_selector_sidebar_custom_model_table,