Moved Apply NN to images project to a engine 2.0

.flake8

@@ -0,0 +1,3 @@
+[flake8]
+max-line-length = 100
+ignore = E203, E501, W503, E722, W605

.github/workflows/publish.yml

@@ -16,4 +16,4 @@ jobs:
       RELEASE_VERSION: ""
       RELEASE_DESCRIPTION: ""
       RELEASE_TYPE: "publish"
-      SUBAPP_PATHS: "annotation-tool, project-dataset"
+      SUBAPP_PATHS: "annotation-tool, project_dataset"

.github/workflows/release.yml

@@ -22,4 +22,4 @@ jobs:
       RELEASE_VERSION: "${{ github.event.release.tag_name }}"
       RELEASE_DESCRIPTION: "${{ github.event.release.name }}"
       RELEASE_TYPE: "release"
-      SUBAPP_PATHS: "annotation-tool, project-dataset"
+      SUBAPP_PATHS: "annotation-tool, project_dataset"

.github/workflows/release_branch.yml

@@ -20,4 +20,4 @@ jobs:
       RELEASE_VERSION: "${{ github.ref_name }}"
       RELEASE_DESCRIPTION: "'${{ github.ref_name }}' branch release"
       RELEASE_TYPE: "release-branch"
-      SUBAPP_PATHS: "annotation-tool, project-dataset"
+      SUBAPP_PATHS: "annotation-tool, project_dataset"

.gitignore

@@ -7,3 +7,4 @@ shared_utils/__pycache__
 project-dataset/src/__pycache__
 .DS_Store
 debug
+__pycache__/

.vscode/launch.json

@@ -11,6 +11,28 @@
             "env": {
                 "PYTHONPATH": "${workspaceFolder}${pathSeparator}${env:PYTHONPATH}"
             }
-        }
+        },
+        {
+            "name": "UI app",
+            "type": "python",
+            "request": "launch",
+            "module": "uvicorn",
+            "args": [
+                "project_dataset.src.main:app",
+                "--host",
+                "0.0.0.0",
+                "--port",
+                "8000",
+                "--ws",
+                "websockets",
+                "--reload"
+            ],
+            "jinja": true,
+            "justMyCode": true,
+            "env": {
+                "PYTHONPATH": "${workspaceFolder}:${PYTHONPATH}",
+                "LOG_LEVEL": "DEBUG"
+            }
+        },
     ]
 }

.vscode/settings.json

@@ -19,6 +19,9 @@
     },
     "[python]": {
         "editor.defaultFormatter": "ms-python.black-formatter",
+        "editor.formatOnSave": true,
+        "editor.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
     },
     "debug.inlineValues": "off",
     "python.analysis.typeCheckingMode": "off",

create_venv.sh

@@ -0,0 +1,28 @@
+#!/bin/bash
+
+# Checking if .venv dir already exists.
+if [ -d ".venv" ]; then
+    echo "VENV dir (.venv) already exists, it will be removed."
+    rm -rf .venv
+fi
+
+echo "VENV will be created"
+
+# Checking if python3.8 is available in PATH.
+if command -v python3.8 &>/dev/null; then
+    python_executable="python3.8" && \
+    echo "Python 3.8 found, it will be used for creating VENV dir."
+else
+    python_executable="python3" && \
+    echo "Python 3.8 not found, default python3 will be used for creating VENV dir."
+fi
+
+# Creating VENV dir with selected python executable.
+$python_executable -m venv .venv && \
+source .venv/bin/activate && \
+
+# Installing requirements from requirements.txt.
+echo "Install dev_requirements..." && \
+pip3 install -r dev_requirements.txt && \
+echo "Requirements have been successfully installed, VENV ready." && \
+deactivate

project_dataset/.gitignore

@@ -0,0 +1,2 @@
+/secret_debug.env
+temp/

project-dataset/config.json → project_dataset/config.json

@@ -1,6 +1,7 @@
 {
   "name": "Apply NN to Images Project",
   "type": "app",
+  "version": "2.0.0",
   "categories": [
     "neural network",
     "images",
@@ -11,10 +12,9 @@
     "labeling"
   ],
   "description": "NN Inference on images in project or dataset",
-  "docker_image": "supervisely/labeling:6.73.22",
+  "docker_image": "supervisely/labeling:6.72.234",
   "min_instance_version": "6.8.73",
-  "main_script": "project-dataset/src/main.py",
-  "gui_template": "project-dataset/src/gui.html",
+  "entrypoint": "python -m uvicorn project_dataset.src.main:app --host 0.0.0.0 --port 8000",
   "task_location": "workspace_tasks",
   "isolate": true,
   "headless": false,

project_dataset/local.env

@@ -0,0 +1,4 @@
+TEAM_ID=448
+WORKSPACE_ID=690
+PROJECT_ID=34969
+DATASET_ID=85450

project_dataset/src/globals.py

@@ -0,0 +1,53 @@
+import os
+
+import supervisely as sly
+from dotenv import load_dotenv
+
+ABSOLUTE_PATH = os.path.dirname(os.path.abspath(__file__))
+PARENT_DIR = os.path.dirname(ABSOLUTE_PATH)
+STATIC_DIR = os.path.join(PARENT_DIR, "temp")
+sly.fs.mkdir(STATIC_DIR)
+
+if sly.is_development():
+    load_dotenv(os.path.join(PARENT_DIR, "local.env"))
+    load_dotenv(os.path.expanduser("~/supervisely.env"))
+
+team_id = sly.env.team_id()
+workspace_id = sly.env.workspace_id()
+project_id = sly.env.project_id(raise_not_found=False)
+dataset_id = sly.env.dataset_id(raise_not_found=False)
+
+sly.logger.info(
+    f"TEAM_ID: {team_id}, WORKSPACE_ID: {workspace_id}, PROJECT_ID: {project_id}, DATASET_ID: {dataset_id}"
+)
+
+api = sly.Api.from_env()
+if dataset_id:
+    dataset_info = api.dataset.get_info_by_id(dataset_id)
+    project_id = dataset_info.project_id
+
+# region ui-settings
+selected_project = None
+selected_datasets = None
+model_session_id = None
+model_meta = None
+inference_settings = None
+# endregion
+
+# region ui-consants
+deployed_nn_tags = ["deployed_nn"]
+inference_modes = ["full image", "sliding window"]
+add_predictions_modes = ["merge with existing labels", "replace existing labels"]
+# endregion
+
+# region caches
+input_images = None
+project_info = api.project.get_info_by_id(project_id)
+project_meta = sly.ProjectMeta.from_json(api.project.get_meta(project_id))
+# endregion
+
+# region sliding window parameters
+det_model_meta = None
+model_info = None
+inference_request_uuid = None
+# endregion

project_dataset/src/main.py

@@ -0,0 +1,23 @@
+import supervisely as sly
+from supervisely.app.widgets import Container
+
+import project_dataset.src.globals as g
+import project_dataset.src.ui.connect_nn as connect_nn
+import project_dataset.src.ui.inference_preview as inference_preview
+import project_dataset.src.ui.inference_settings as inference_settings
+import project_dataset.src.ui.input_data as input_data
+import project_dataset.src.ui.nn_info as nn_info
+import project_dataset.src.ui.output_data as output_data
+
+layout = Container(
+    widgets=[
+        input_data.card,
+        connect_nn.card,
+        nn_info.card,
+        inference_settings.card,
+        inference_preview.card,
+        output_data.card,
+    ],
+)
+
+app = sly.Application(layout=layout, static_dir=g.STATIC_DIR)

project_dataset/src/ui/connect_nn.py

@@ -0,0 +1,152 @@
+import supervisely as sly
+import yaml
+from supervisely.app.widgets import Button, Card, Container, ModelInfo, SelectAppSession, Text
+
+import project_dataset.src.globals as g
+import project_dataset.src.ui.inference_preview as inference_preview
+import project_dataset.src.ui.inference_settings as inference_settings
+import project_dataset.src.ui.nn_info as nn_info
+import project_dataset.src.ui.output_data as output_data
+
+select_session = SelectAppSession(g.team_id, g.deployed_nn_tags)
+connect_button = Button("Connect", icon="zmdi zmdi-check")
+disconnect_button = Button("Disconnect", icon="zmdi zmdi-close")
+disconnect_button.hide()
+error_text = Text(status="warning")
+error_text.hide()
+
+model_info = ModelInfo()
+model_info.hide()
+
+card = Card(
+    "2️⃣ Choose model",
+    "Select a deployed neural network to start and click on Select button.",
+    content=Container([select_session, connect_button, model_info, disconnect_button, error_text]),
+    collapsable=True,
+    lock_message="Select a project or a dataset on step 1️⃣.",
+)
+card.collapse()
+card.lock()
+
+
+@connect_button.click
+def model_selected() -> None:
+    """Connects to the selected model session and changes the UI state."""
+    g.model_session_id = select_session.get_selected_id()
+    if g.model_session_id is None:
+        error_text.text = "No model was selected, please select a model and try again."
+        error_text.show()
+        return
+
+    connect_status = connect_to_model()
+    if not connect_status:
+        error_text.text = (
+            "Couldn't connect to the model. Make sure that model is deployed and try again."
+        )
+        error_text.show()
+        return
+
+    g.model_meta = get_model_meta()
+    g.inference_settings = get_inference_settings()
+    inference_settings.additional_settings.set_text(g.inference_settings["settings"])
+
+    error_text.hide()
+    model_info.set_session_id(g.model_session_id)
+    model_info.show()
+    disconnect_button.show()
+
+    connect_button.hide()
+    select_session.hide()
+
+    nn_info.load_classes()
+    nn_info.load_tags()
+
+    nn_info.card.unlock()
+    nn_info.card.uncollapse()
+
+    inference_settings.card.unlock()
+    inference_settings.card.uncollapse()
+
+    inference_preview.card.unlock()
+    inference_preview.card.uncollapse()
+
+    inference_preview.random_image_checkbox.enable()
+    inference_preview.preview_button.enable()
+
+    output_data.card.unlock()
+    output_data.card.uncollapse()
+
+
+@disconnect_button.click
+def model_changed() -> None:
+    """Changes the UI state when the model is changed."""
+    connect_button.show()
+    select_session.show()
+
+    disconnect_button.hide()
+    g.model_session_id = None
+    g.model_meta = None
+    sly.logger.info(f"Change button was clicked. Model session: {g.model_session_id}")
+    model_info.hide()
+
+    nn_info.card.lock()
+    nn_info.card.collapse()
+
+    inference_settings.card.lock()
+    inference_settings.card.collapse()
+
+    inference_preview.card.lock()
+    inference_preview.card.collapse()
+
+    inference_preview.random_image_checkbox.disable()
+    inference_preview.preview_button.disable()
+
+    output_data.card.lock()
+    output_data.card.collapse()
+
+
+def connect_to_model() -> bool:
+    """Connects to the selected model session.
+
+    :return: True if the connection was successful, False otherwise.
+    :rtype: bool
+    """
+    try:
+        session_info = g.api.task.send_request(g.model_session_id, "get_session_info", data={})
+        sly.logger.info(f"Connected to model session: {session_info}")
+        return True
+    except Exception as e:
+        sly.logger.warning(
+            f"Couldn't get model info. Make sure that model is deployed and try again. Reason: {e}"
+        )
+        return False
+
+
+def get_model_meta() -> sly.ProjectMeta:
+    """Returns model meta in Supervisely format.
+
+    :return: Model meta in Supervisely format.
+    :rtype: sly.ProjectMeta
+    """
+    meta_json = g.api.task.send_request(g.model_session_id, "get_output_classes_and_tags", data={})
+    return sly.ProjectMeta.from_json(meta_json)
+
+
+def get_inference_settings() -> str:
+    """Returns custom inference settings for the model.
+    The settings are returned as a string in YAML format.
+
+    :return: Custom inference settings for the model.
+    :rtype: str
+    """
+    inference_settings = g.api.task.send_request(
+        g.model_session_id, "get_custom_inference_settings", data={}
+    )
+    if inference_settings["settings"] is None or len(inference_settings["settings"]) == 0:
+        inference_settings["settings"] = ""
+        sly.logger.info("Model doesn't support custom inference settings.")
+    elif isinstance(inference_settings["settings"], dict):
+        inference_settings["settings"] = yaml.dump(
+            inference_settings["settings"], allow_unicode=True
+        )
+    return inference_settings