fix: wrong label map key type (#322)

When reading the json file via
`UNSTRUCTURED_DEFAULT_MODEL_INITIALIZE_PARAMS_JSON_PATH` environment
variable, the label_map keys have to be converted to `int` type before
it can be referenced. Added code to always convert label_map keys to
`int` type.

CHANGELOG.md

@@ -2,6 +2,7 @@
 
 * bug: check for None in Chipper bounding box reduction
 * chore: removes `install-detectron2` from the `Makefile`
+* fix: convert label_map keys read from os.environment `UNSTRUCTURED_DEFAULT_MODEL_INITIALIZE_PARAMS_JSON_PATH` to int type
 
 ## 0.7.24
 

test_unstructured_inference/models/test_model.py

@@ -1,3 +1,4 @@
+import json
 from typing import Any
 from unittest import mock
 
@@ -45,7 +46,9 @@ def test_model_initializes_once():
     from unstructured_inference.inference import layout
 
     with mock.patch.dict(models.model_class_map, {"yolox": MockModel}), mock.patch.object(
-        models, "models", {}
+        models,
+        "models",
+        {},
     ):
         doc = layout.DocumentLayout.from_file("sample-docs/loremipsum.pdf")
         doc.pages[0].detection_model.initializer.assert_called_once()
@@ -143,23 +146,32 @@ def test_env_variables_override_default_model(monkeypatch):
     # args, we should get back the model the env var calls for
     monkeypatch.setattr(models, "models", {})
     with mock.patch.dict(
-        models.os.environ, {"UNSTRUCTURED_DEFAULT_MODEL_NAME": "checkbox"}
+        models.os.environ,
+        {"UNSTRUCTURED_DEFAULT_MODEL_NAME": "checkbox"},
     ), mock.patch.dict(models.model_class_map, {"checkbox": MockModel}):
         model = models.get_model()
     assert isinstance(model, MockModel)
 
 
-def test_env_variables_override_intialization_params(monkeypatch):
+def test_env_variables_override_initialization_params(monkeypatch):
     # When initialization params are specified in an environment variable, and we call get_model, we
     # should see that the model was initialized with those params
     monkeypatch.setattr(models, "models", {})
+    fake_label_map = {"1": "label1", "2": "label2"}
     with mock.patch.dict(
         models.os.environ,
         {"UNSTRUCTURED_DEFAULT_MODEL_INITIALIZE_PARAMS_JSON_PATH": "fake_json.json"},
     ), mock.patch.object(models, "DEFAULT_MODEL", "fake"), mock.patch.dict(
-        models.model_class_map, {"fake": mock.MagicMock()}
+        models.model_class_map,
+        {"fake": mock.MagicMock()},
     ), mock.patch(
-        "builtins.open", mock.mock_open(read_data='{"date": "3/26/81"}')
+        "builtins.open",
+        mock.mock_open(
+            read_data='{"model_path": "fakepath", "label_map": ' + json.dumps(fake_label_map) + "}",
+        ),
     ):
         model = models.get_model()
-    model.initialize.assert_called_once_with(date="3/26/81")
+    model.initialize.assert_called_once_with(
+        model_path="fakepath",
+        label_map={1: "label1", 2: "label2"},
+    )

unstructured_inference/models/base.py

@@ -7,25 +7,15 @@
 from unstructured_inference.models.detectron2 import (
     MODEL_TYPES as DETECTRON2_MODEL_TYPES,
 )
-from unstructured_inference.models.detectron2 import (
-    UnstructuredDetectronModel,
-)
+from unstructured_inference.models.detectron2 import UnstructuredDetectronModel
 from unstructured_inference.models.detectron2onnx import (
     MODEL_TYPES as DETECTRON2_ONNX_MODEL_TYPES,
 )
-from unstructured_inference.models.detectron2onnx import (
-    UnstructuredDetectronONNXModel,
-)
-from unstructured_inference.models.super_gradients import (
-    UnstructuredSuperGradients,
-)
+from unstructured_inference.models.detectron2onnx import UnstructuredDetectronONNXModel
+from unstructured_inference.models.super_gradients import UnstructuredSuperGradients
 from unstructured_inference.models.unstructuredmodel import UnstructuredModel
-from unstructured_inference.models.yolox import (
-    MODEL_TYPES as YOLOX_MODEL_TYPES,
-)
-from unstructured_inference.models.yolox import (
-    UnstructuredYoloXModel,
-)
+from unstructured_inference.models.yolox import MODEL_TYPES as YOLOX_MODEL_TYPES
+from unstructured_inference.models.yolox import UnstructuredYoloXModel
 
 DEFAULT_MODEL = "yolox"
 
@@ -58,6 +48,10 @@ def get_model(model_name: Optional[str] = None) -> UnstructuredModel:
     if initialize_param_json is not None:
         with open(initialize_param_json) as fp:
             initialize_params = json.load(fp)
+            label_map_int_keys = {
+                int(key): value for key, value in initialize_params["label_map"].items()
+            }
+            initialize_params["label_map"] = label_map_int_keys
     else:
         if model_name in DETECTRON2_MODEL_TYPES:
             initialize_params = DETECTRON2_MODEL_TYPES[model_name]