tests for box validation

image_prediction/extractor_classifier/extractor_classifier.py

@@ -2,7 +2,7 @@ from itertools import chain
 from typing import Iterable
 
 from image_prediction.classifier.image_classifier import ImageClassifier
-from image_prediction.image_extractor.extractor import ImageExtractor, ImageMetadataPair
+from image_prediction.image_extractor.extractor import ImageExtractor
 from image_prediction.utils.generic import chunk_iterable
 
 
@@ -24,7 +24,7 @@ class ExtractorClassifier:
         responses = ({"classification": prd, **mdt} for prd, mdt in zip(predictions, metadata))
         return responses
 
-    def __call__(self, obj, **kwargs) -> Iterable[ImageMetadataPair]:
+    def __call__(self, obj, **kwargs) -> Iterable[dict]:
         image_metadata_pairs = self.extractor(obj, **kwargs)
         batches = chunk_iterable(image_metadata_pairs, chunk_size=16)
         predictions = chain.from_iterable(map(self.__process_batch, batches))

test/unit_tests/box_validation_test.py

@@ -0,0 +1,29 @@
+import pytest
+
+from image_prediction.exceptions import InvalidBox
+from image_prediction.info import Info
+from image_prediction.stitching.utils import validate_box_size, validate_box_coords
+
+
+def test_validate_fail_too_short():
+    box = {Info.WIDTH: 1, Info.HEIGHT: 0}
+    with pytest.raises(InvalidBox):
+        validate_box_size(box)
+
+
+def test_validate_fail_too_thin():
+    box = {Info.WIDTH: 0, Info.HEIGHT: 1}
+    with pytest.raises(InvalidBox):
+        validate_box_size(box)
+
+
+def test_validate_fail_xs_width_mismatch():
+    box = {Info.WIDTH: 2, Info.HEIGHT: 4, Info.X1: 0, Info.Y1: 0, Info.X2: 1, Info.Y2: 4}
+    with pytest.raises(InvalidBox):
+        validate_box_coords(box)
+
+
+def test_validate_fail_ys_width_mismatch():
+    box = {Info.WIDTH: 2, Info.HEIGHT: 3, Info.X1: 0, Info.Y1: 0, Info.X2: 2, Info.Y2: 4}
+    with pytest.raises(InvalidBox):
+        validate_box_coords(box)