Merge pull request #110 from superannotateai/develop

Release

Author: dshabin

superannotate/api.py

@@ -51,7 +51,7 @@ def init(self, config_location=None):
             self._api_config = json.load(open(config_location))
 
             try:
-                self._token = self._api_config["token"]
+                self._token = self._api_config["token"].strip()
             except KeyError:
                 raise SABaseException(
                     0,

superannotate/db/annotation_classes.py

@@ -347,9 +347,9 @@ def fill_class_and_attribute_ids(annotation_json, annotation_classes_dict):
     annotation_classes_dict = {**annotation_classes_dict, **unknown_classes}
     templates_map = get_templates_mapping()
     for ann in (
-        i for i in annotation_json["instances"] if i['type'] == 'template'
+        i for i in annotation_json["instances"] if i.get('type', None) == 'template'
     ):
-        ann['templateId'] = templates_map.get(ann['templateName'], -1)
+        ann['templateId'] = templates_map.get(ann.get('templateName', ''), -1)
     for ann in annotation_json["instances"]:
         if "className" not in ann:
             logger.warning("No className in annotation instance")

superannotate/mixp/decorators.py

@@ -17,19 +17,26 @@ class Trackable(object):
     def __init__(self, function):
         lock = Lock()
         self.function = function
+        self._success = None
+        self._caller_name = None
+        self._func_name_to_track = None
         with lock:
             Trackable.registered.add(function.__name__)
         functools.update_wrapper(self, function)
 
-    def __call__(self, *args, **kwargs):
+    def should_track(self):
+        if self._caller_name not in Trackable.registered or self._func_name_to_track in always_trackable_func_names:
+            return True
+        return False
+
+    def track(self, *args, **kwargs):
         try:
-            func_name_to_track = self.function.__name__
-            caller_name = sys._getframe(1).f_code.co_name
-            if caller_name not in Trackable.registered or func_name_to_track in always_trackable_func_names:
-                data = getattr(parsers, func_name_to_track)(*args, **kwargs)
+            if self.should_track():
+                data = getattr(parsers, self._func_name_to_track)(*args, **kwargs)
                 user_id = _api.user_id
                 event_name = data['event_name']
                 properties = data['properties']
+                properties['Success'] = self._success
                 default = get_default(
                     _api.team_name,
                     _api.user_id,
@@ -39,6 +46,19 @@ def __call__(self, *args, **kwargs):
                 properties = {**default, **properties}
                 if "pytest" not in sys.modules:
                     mp.track(user_id, event_name, properties)
-        except:
+        except Exception as e:
             pass
-        return self.function(*args, **kwargs)
+
+
+    def __call__(self, *args, **kwargs):
+        try:
+            self._caller_name = sys._getframe(1).f_code.co_name
+            self._func_name_to_track = self.function.__name__
+            ret = self.function(*args, **kwargs)
+            self._success = True
+            self.track(*args, **kwargs)
+        except Exception as e:
+            self._success = False
+            self.track(*args, **kwargs)
+            raise e
+        return ret

superannotate/mixp/helper.py

@@ -1 +1 @@
-CALLERS_TO_IGNORE = ["get_project_metadata_bare"]
+CALLERS_TO_IGNORE = ["get_project_metadata_bare", "_path_to_folder_id_project"]

superannotate/mixp/utils/parsers.py

@@ -1183,33 +1183,44 @@ def coco_split_dataset(*args, **kwargs):
 
 
 def run_training(*args, **kwargs):
-    project = kwargs.get("project", None)
-    if not project:
-        project = args[0][0]
+
     task = kwargs.get("task", None)
     if not task:
-        task = args[4]
-    hyperparameters = kwargs.get("hyperparameters", None)
-    if not hyperparameters:
-        hyperparameters = args[4]
-    from superannotate.db.projects import get_project_metadata as sa_get_project_metadata
-    project_name = get_project_name(project)
-    project_metadata = sa_get_project_metadata(project_name)
+        task = args[2]
     log = kwargs.get("log", "empty")
     if log == "empty":
-        log = args[6:7]
+        log = args[7:8]
         if not log:
             log = False
         else:
-            log = args[6]
+            log = args[7]
+
+    train_data = kwargs.get("train_data", None)
+    if not train_data:
+        train_data = args[4]
+
+    test_data = kwargs.get("test_data", None)
+    if not test_data:
+        test_data = args[5]
+
+    data_structure = "Project"
+
+    for path in train_data + test_data:
+        if "/" in path:
+            data_structure = "Folder"
+            break
+
+    from superannotate.db.projects import get_project_metadata as sa_get_project_metadata
+    project_name = get_project_name(train_data[0])
+    project_metadata = sa_get_project_metadata(project_name)
+
     return {
         "event_name": "run_training",
         "properties":
             {
                 "Project Type": project_metadata['type'],
                 "Task": task,
-                "Learning Rate": hyperparameters['base_lr'],
-                "Batch Size": hyperparameters['images_per_batch'],
+                "Data Structure": data_structure,
                 "Log": log
             }
     }
@@ -1673,6 +1684,7 @@ def assign_folder(*args, **kwargs):
         }
     }
 
+
 def unassign_images(*args, **kwargs):
     image_names = kwargs.get("image_names", None)
     if not image_names:
@@ -1690,19 +1702,9 @@ def unassign_images(*args, **kwargs):
 
     return {
         "event_name": "unassign_images",
-        "properties": {
-            "Assign Folder": is_root,
-            "Image Count": len(image_names)
-        }
+        "properties":
+            {
+                "Assign Folder": is_root,
+                "Image Count": len(image_names)
+            }
     }
-
-
-
-
-# def unassign_images(project, image_names):
-
-
-
-#
-# Assign Folder: IsRoot(project) ,
-# Image Count: len(image_names),

superannotate/ml/defaults.py

@@ -1,7 +1,6 @@
 DEFAULT_HYPERPARAMETERS = {
     "instance_type": "1 x T4 16 GB",
     "num_epochs": 12,
-    "dataset_split_ratio": 80,
     "base_lr": 0.02,
     "gamma": 0.5,
     "images_per_batch": 4,