check if model meta is none

annotation-tool/debug.env

@@ -1,12 +1,12 @@
 PYTHONUNBUFFERED=1
 LOG_LEVEL="trace"
 
-TASK_ID=52097 # ⬅️ change value (run 'While True Script' app and copy task ID)
+TASK_ID=52548 # ⬅️ change value (run 'While True Script' app and copy task ID)
 
 context.userId=330                  # ⬅️ change value
 context.teamId=506                  # ⬅️ change value
 context.workspaceId=942             # ⬅️ change value
-modal.state.slyProjectId=28001      # ⬅️ change value
+modal.state.slyProjectId=34944      # ⬅️ change value
 # modal.state.slyDatasetId=75910    # ⬅️ change value (optional)
 
 DEBUG_APP_DIR="debug/app_debug_data"

annotation-tool/src/main.py

@@ -13,6 +13,7 @@
 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
@@ -103,6 +104,12 @@ def deselect_all_tags(api: sly.Api, task_id, context, state, app_logger):
 @sly.timeit
 def inference(api: sly.Api, task_id, context, state, app_logger):
     global model_meta
+    if model_meta is None:
+        err = "Model meta is None. Make sure that the model is deployed, has meta, and try again."
+        set_error(api, task_id, err)
+        fields = [{"field": "state.processing", "payload": False}]
+        api.task.set_fields(task_id, fields)
+        return
     project_id = context.get("projectId")
     image_id = context.get("imageId")
     figure_id = context.get("figureId")
@@ -330,7 +337,6 @@ def inference(api: sly.Api, task_id, context, state, app_logger):
 
     if session_info.get("task type") == "prompt-based object detection":
         # add tag to model meta if necessary
-        global model_meta
         if not model_meta.get_tag_meta("confidence"):
             model_meta = model_meta.add_tag_meta(sly.TagMeta("confidence", value_type="any_number"))
         # add obj class to model meta if necessary

shared_utils/connect.py

@@ -26,7 +26,8 @@ def get_model_info(api: sly.Api, task_id, context, state, app_logger) -> sly.Pro
         )
         sly.logger.info(f"Model meta: {str(meta_json)}")
         model_meta = sly.ProjectMeta.from_json(meta_json)
-
+        if model_meta is None:
+            raise RuntimeError("Model meta is None. Make sure that the model is deployed, has meta, and try again.")
         try:
             inf_settings = api.task.send_request(
                 state["sessionId"], "get_custom_inference_settings", data={}

shared_utils/ui2.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Union
 import supervisely as sly
 
 
@@ -25,12 +25,15 @@ def set_model_info(api: sly.Api, task_id, model_meta: sly.ProjectMeta, model_inf
     api.task.set_fields(task_id, fields)
 
 
-def set_error(api: sly.Api, task_id, e: Exception, log_error: bool = True):
+def set_error(api: sly.Api, task_id, e: Union[Exception, str], log_error: bool = True):
+    err = e if isinstance(e, str) else repr(e)
     if log_error:
-        sly.logger.error(repr(e))
+        sly.logger.error(err)
+    else:
+        sly.logger.warn(err)
     fields = [
         {"field": "data.connected", "payload": False},
-        {"field": "data.connectionError", "payload": repr(e)},
+        {"field": "data.connectionError", "payload": err},
     ]
     api.task.set_fields(task_id, fields)