Workflow

annotation-tool/config.json

@@ -11,16 +11,14 @@
     "labeling"
   ],
   "description": "Use deployed neural network in labeling interface",
-  "docker_image": "supervisely/labeling:6.73.104",
+  "docker_image": "supervisely/labeling:6.73.123",
   "min_instance_version": "6.9.22",
   "main_script": "annotation-tool/src/main.py",
   "gui_template": "annotation-tool/src/gui.html",
   "task_location": "application_sessions",
   "isolate": true,
   "headless": false,
-  "integrated_into": [
-    "image_annotation_tool"
-  ],
+  "integrated_into": ["image_annotation_tool"],
   "icon": "https://i.imgur.com/nnB2BqW.png",
   "icon_background": "#FFFFFF",
   "hotkeys": [

annotation-tool/src/main.py

@@ -1,22 +1,26 @@
 import os
-import yaml
 import pathlib
 import sys
 from collections import defaultdict
+
 import supervisely as sly
-from supervisely.imaging.color import random_rgb, generate_rgb
+import yaml
+from supervisely.imaging.color import generate_rgb, random_rgb
+from workflow import Workflow
 
 root_source_path = str(pathlib.Path(sys.argv[0]).parents[2])
 sly.logger.info(f"Root source directory: {root_source_path}")
 sys.path.append(root_source_path)
 
+import io
+
+import ruamel.yaml
+from dotenv import load_dotenv
 from init_ui import init_ui
+
 from shared_utils.connect import get_model_info
 from shared_utils.inference import postprocess
 from shared_utils.ui2 import set_error
-from dotenv import load_dotenv
-import ruamel.yaml
-import io
 
 if sly.is_development():
     load_dotenv(os.path.expanduser("~/supervisely.env"))
@@ -125,6 +129,11 @@ def inference(api: sly.Api, task_id, context, state, app_logger):
 
     project_meta = sly.ProjectMeta.from_json(api.project.get_meta(project_id))
 
+    # -------------------------------------- Add Workflow Input -------------------------------------- #
+    nn_workflow = Workflow(api)
+    nn_workflow.add_input(project_id, state)
+    # ----------------------------------------------- - ---------------------------------------------- #
+
     if image_id not in ann_cache:
         # keep only current image for simplicity
         ann_cache.clear()
@@ -448,6 +457,10 @@ def inference(api: sly.Api, task_id, context, state, app_logger):
     ]
     api.task.set_fields(task_id, fields)
 
+    # -------------------------------------- Add Workflow Output ------------------------------------- #
+    nn_workflow.add_output(project_id)
+    # ----------------------------------------------- - ---------------------------------------------- #
+
 
 @my_app.callback("undo")
 @sly.timeit
@@ -464,6 +477,7 @@ def undo(api: sly.Api, task_id, context, state, app_logger):
         {"field": "state.processing", "payload": False},
     ]
     api.task.set_fields(task_id, fields)
+    # ? do we need to add output project here, cuz undo will be for the same project
 
 
 def main():

annotation-tool/src/workflow.py

@@ -0,0 +1,45 @@
+import supervisely as sly
+
+
+def check_compatibility(func):
+    def wrapper(self, *args, **kwargs):
+        if self.is_compatible is None:
+            self.is_compatible = self.check_instance_ver_compatibility()
+        if not self.is_compatible:
+            return
+        return func(self, *args, **kwargs)
+
+    return wrapper
+
+
+class Workflow:
+    def __init__(self, api: sly.Api, min_instance_version: str = None):
+        self.is_compatible = None
+        self.api = api
+        self._min_instance_version = (
+            "6.9.31" if min_instance_version is None else min_instance_version
+        )
+
+    def check_instance_ver_compatibility(self):
+        if not self.api.is_version_supported(self._min_instance_version):
+            sly.logger.info(
+                f"Supervisely instance version {self.api.instance_version} does not support workflow features."
+            )
+            if not sly.is_community():
+                sly.logger.info(
+                    f"To use them, please update your instance to version {self._min_instance_version} or higher."
+                )
+            return False
+        return True
+
+    @check_compatibility
+    def add_input(self, project_id: int, state: dict):
+        if self.api.project.get_info_by_id(project_id).version:  # to prevent cycled workflow
+            self.api.app.workflow.add_input_project(project_id)
+        self.api.app.workflow.add_input_task(int(state["sessionId"]))
+        sly.logger.debug(f"Workflow Input: Project ID - {project_id}, Session ID - {int(state["sessionId"])}")
+
+    @check_compatibility
+    def add_output(self, project_id: int):
+        self.api.app.workflow.add_output_project(project_id)
+        sly.logger.debug(f"Workflow Output: Project ID - {project_id}")

dev_requirements.txt

@@ -1,3 +1,3 @@
-supervisely==6.73.104
+supervisely==6.73.123
 matplotlib>=3.3.2, <4.0.0
 imgaug>=0.4.0, <1.0.0

project-dataset/config.json

@@ -12,7 +12,7 @@
     "labeling"
   ],
   "description": "NN Inference on images in project or dataset",
-  "docker_image": "supervisely/labeling:6.73.104",
+  "docker_image": "supervisely/labeling:6.73.123",
   "min_instance_version": "6.9.22",
   "entrypoint": "python -m uvicorn project-dataset.src.main:app --host 0.0.0.0 --port 8000",
   "task_location": "workspace_tasks",
@@ -21,10 +21,7 @@
   "icon": "https://i.imgur.com/KdCigmp.png",
   "icon_background": "#FFFFFF",
   "context_menu": {
-    "target": [
-      "images_project",
-      "images_dataset"
-    ],
+    "target": ["images_project", "images_dataset"],
     "context_root": "Neural Networks"
   },
   "poster": "https://user-images.githubusercontent.com/106374579/187227957-ea4fd452-35ef-4969-9e55-cd7a5a4873ee.png"

project-dataset/src/globals.py

@@ -1,8 +1,11 @@
+import importlib
 import os
 
 import supervisely as sly
 from dotenv import load_dotenv
 
+w = importlib.import_module("project-dataset.src.workflow")
+
 ABSOLUTE_PATH = os.path.dirname(os.path.abspath(__file__))
 PARENT_DIR = os.path.dirname(ABSOLUTE_PATH)
 STATIC_DIR = os.path.join(PARENT_DIR, "temp")
@@ -22,6 +25,9 @@
 )
 
 api = sly.Api.from_env()
+
+workflow = w.Workflow(api)
+
 if dataset_id:
     dataset_info = api.dataset.get_info_by_id(dataset_id)
     project_id = dataset_info.project_id

project-dataset/src/ui/output_data.py

@@ -168,6 +168,10 @@ def apply_model():
     )
     g.api.project.update_meta(res_project.id, res_project_meta.to_json())
 
+    # -------------------------------------- Add Workflow Input -------------------------------------- #
+    g.workflow.add_input(project_id=g.selected_project, session_id=g.model_session_id)
+    # ----------------------------------------------- - ---------------------------------------------- #
+
     try:
         apply_model_ds(g.selected_project, res_project, inference_settings, res_project_meta)
     except Exception as e:
@@ -249,10 +253,11 @@ def apply_model():
                                 )
                                 continue
                     pbar.update(len(batched_image_infos))
-
     output_project_thumbnail.set(g.api.project.get_info_by_id(res_project.id))
     output_project_thumbnail.show()
-
+    # -------------------------------------- Add Workflow Output ------------------------------------- #
+    g.workflow.add_output(project_id=res_project.id)
+    # ----------------------------------------------- - ---------------------------------------------- #
     main = importlib.import_module("project-dataset.src.main")
 
     main.app.stop()

project-dataset/src/workflow.py

@@ -0,0 +1,47 @@
+import supervisely as sly
+
+
+def check_compatibility(func):
+    def wrapper(self, *args, **kwargs):
+        if self.is_compatible is None:
+            self.is_compatible = self.check_instance_ver_compatibility()
+        if not self.is_compatible:
+            return
+        return func(self, *args, **kwargs)
+
+    return wrapper
+
+
+class Workflow:
+    def __init__(self, api: sly.Api, min_instance_version: str = None):
+        self.is_compatible = None
+        self.api = api
+        self._min_instance_version = (
+            "6.9.31" if min_instance_version is None else min_instance_version
+        )
+
+    def check_instance_ver_compatibility(self):
+        if not self.api.is_version_supported(self._min_instance_version):
+            sly.logger.info(
+                f"Supervisely instance version {self.api.instance_version} does not support workflow features."
+            )
+            if not sly.is_community():
+                sly.logger.info(
+                    f"To use them, please update your instance to version {self._min_instance_version} or higher."
+                )
+            return False
+        return True
+
+    @check_compatibility
+    def add_input(self, project_id: int = None, session_id: int = None):
+        if session_id is not None:
+            sly.logger.debug(f"Workflow Input: Session ID - {session_id}")
+            self.api.app.workflow.add_input_task(int(session_id))
+        if project_id is not None:
+            sly.logger.debug(f"Workflow Input: Project ID - {project_id}")
+            self.api.app.workflow.add_input_project(project_id)
+
+    @check_compatibility
+    def add_output(self, project_id: int):
+        sly.logger.debug(f"Workflow Output: Project ID - {project_id}")
+        self.api.app.workflow.add_output_project(project_id)