fix: fix bugs in layoutelements

CHANGELOG.md

@@ -1,3 +1,8 @@
+## 0.7.41
+
+* fix: fix incorrect type casting with higher versions of `numpy` when substracting a `float` from an `int` array
+* fix: fix a bug where class id 0 becomes class type `None` when calling `LayoutElements.as_list()`
+
 ## 0.7.40
 
 * fix: store probabilities with `float` data type instead of `int`

test_unstructured_inference/test_elements.py

@@ -143,8 +143,10 @@ def test_minimal_containing_rect():
         assert rect2.is_in(big_rect)
 
 
-def test_partition_groups_from_regions(mock_embedded_text_regions):
+@pytest.mark.parametrize("coord_type", [int, float])
+def test_partition_groups_from_regions(mock_embedded_text_regions, coord_type):
     words = TextRegions.from_list(mock_embedded_text_regions)
+    words.element_coords = words.element_coords.astype(coord_type)
     groups = partition_groups_from_regions(words)
     assert len(groups) == 1
     text = "".join(groups[-1].texts)
@@ -421,3 +423,14 @@ def test_clean_layoutelements_for_class(
     elements = clean_layoutelements_for_class(elements, element_class=class_to_filter)
     np.testing.assert_array_equal(elements.element_coords, expected_coords)
     np.testing.assert_array_equal(elements.element_class_ids, expected_ids)
+
+
+def test_layoutelements_to_list_and_back(test_layoutelements):
+    back = LayoutElements.from_list(test_layoutelements.as_list())
+    np.testing.assert_array_equal(test_layoutelements.element_coords, back.element_coords)
+    np.testing.assert_array_equal(test_layoutelements.texts, back.texts)
+    assert all(np.isnan(back.element_probs))
+    assert [
+        test_layoutelements.element_class_id_map[idx]
+        for idx in test_layoutelements.element_class_ids
+    ] == [back.element_class_id_map[idx] for idx in back.element_class_ids]

unstructured_inference/__version__.py

@@ -1 +1 @@
-__version__ = "0.7.40"  # pragma: no cover
+__version__ = "0.7.41"  # pragma: no cover

unstructured_inference/inference/elements.py

@@ -237,7 +237,7 @@ def as_list(self):
         ]
 
     @classmethod
-    def from_list(cls, regions: list[TextRegion]):
+    def from_list(cls, regions: list):
         """create TextRegions from a list of TextRegion objects; the objects must have the same
         source"""
         coords, texts = [], []

unstructured_inference/inference/layoutelement.py

@@ -32,16 +32,34 @@
 class LayoutElements(TextRegions):
     element_probs: np.ndarray = field(default_factory=lambda: np.array([]))
     element_class_ids: np.ndarray = field(default_factory=lambda: np.array([]))
-    element_class_id_map: dict[int, str] | None = None
+    element_class_id_map: dict[int, str] = field(default_factory=dict)
 
     def __post_init__(self):
-        if self.element_probs is not None:
-            self.element_probs = self.element_probs.astype(float)
         element_size = self.element_coords.shape[0]
         for attr in ("element_probs", "element_class_ids", "texts"):
             if getattr(self, attr).size == 0 and element_size:
                 setattr(self, attr, np.array([None] * element_size))
 
+        self.element_probs = self.element_probs.astype(float)
+
+    def __eq__(self, other: object) -> bool:
+        if not isinstance(other, LayoutElements):
+            return NotImplemented
+
+        mask = ~np.isnan(self.element_probs)
+        other_mask = ~np.isnan(other.element_probs)
+        return (
+            np.array_equal(self.element_coords, other.element_coords)
+            and np.array_equal(self.texts, other.texts)
+            and np.array_equal(mask, other_mask)
+            and np.array_equal(self.element_probs[mask], other.element_probs[mask])
+            and (
+                [self.element_class_id_map[idx] for idx in self.element_class_ids]
+                == [other.element_class_id_map[idx] for idx in other.element_class_ids]
+            )
+            and self.source == other.source
+        )
+
     def slice(self, indices) -> LayoutElements:
         """slice and return only selected indices"""
         return LayoutElements(
@@ -85,10 +103,10 @@ def as_list(self):
                 text=text,
                 type=(
                     self.element_class_id_map[class_id]
-                    if class_id and self.element_class_id_map
+                    if class_id is not None and self.element_class_id_map
                     else None
                 ),
-                prob=prob,
+                prob=None if np.isnan(prob) else prob,
                 source=self.source,
             )
             for (x1, y1, x2, y2), text, prob, class_id in zip(
@@ -99,6 +117,36 @@ def as_list(self):
             )
         ]
 
+    @classmethod
+    def from_list(cls, elements: list):
+        """create LayoutElements from a list of LayoutElement objects; the objects must have the
+        same source"""
+        len_ele = len(elements)
+        coords = np.empty((len_ele, 4), dtype=float)
+        # text and probs can be Nones so use lists first then convert into array to avoid them being
+        # filled as nan
+        texts = []
+        class_probs = []
+        class_types = np.empty((len_ele,), dtype="object")
+
+        for i, element in enumerate(elements):
+            coords[i] = [element.bbox.x1, element.bbox.y1, element.bbox.x2, element.bbox.y2]
+            texts.append(element.text)
+            class_probs.append(element.prob)
+            class_types[i] = element.type or "None"
+
+        unique_ids, class_ids = np.unique(class_types, return_inverse=True)
+        unique_ids[unique_ids == "None"] = None
+
+        return cls(
+            element_coords=coords,
+            texts=np.array(texts),
+            element_probs=np.array(class_probs),
+            element_class_ids=class_ids,
+            element_class_id_map=dict(zip(range(len(unique_ids)), unique_ids)),
+            source=elements[0].source,
+        )
+
 
 @dataclass
 class LayoutElement(TextRegion):
@@ -315,7 +363,7 @@ def partition_groups_from_regions(regions: TextRegions) -> List[TextRegions]:
     regions, each list corresponding with a group"""
     if len(regions) == 0:
         return []
-    padded_coords = regions.element_coords.copy()
+    padded_coords = regions.element_coords.copy().astype(float)
     v_pad = (regions.y2 - regions.y1) * inference_config.ELEMENTS_V_PADDING_COEF
     h_pad = (regions.x2 - regions.x1) * inference_config.ELEMENTS_H_PADDING_COEF
     padded_coords[:, 0] -= h_pad

unstructured_inference/models/yolox.py

@@ -136,7 +136,7 @@ def image_processing(
         sorted_dets = dets[order]
 
         return LayoutElements(
-            element_coords=sorted_dets[:, :4],
+            element_coords=sorted_dets[:, :4].astype(float),
             element_probs=sorted_dets[:, 4].astype(float),
             element_class_ids=sorted_dets[:, 5].astype(int),
             element_class_id_map=self.layout_classes,