Prevent zero-sized saliency map in tiling if tile size is too big (op…

…envinotoolkit#2452) * Prevent zero-sized saliency map in tiling if tile size is too big * Prevent zero-sized saliency in tiling (PyTorch) * Add unit tests for Tiler merge features methods --------- Co-authored-by: Galina <[email protected]>
yunchu · Aug 30, 2023 · 46968ba · 46968ba
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commit 46968ba
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Showing 2 changed files with 16 additions and 3 deletions.
diff --git a/src/otx/algorithms/detection/adapters/mmdet/datasets/tiling.py b/src/otx/algorithms/detection/adapters/mmdet/datasets/tiling.py
@@ -538,8 +538,8 @@ def merge_maps(self, saliency_maps: Union[List[List[np.ndarray]], List[np.ndarra
 
         for orig_image in self.cached_results:
             img_idx = orig_image["index"]
-            ratios[img_idx] = np.array([feat_h, feat_w]) / self.tile_size
             image_h, image_w = orig_image["height"], orig_image["width"]
+            ratios[img_idx] = np.array([feat_h / min(self.tile_size, image_h), feat_w / min(self.tile_size, image_w)])
 
             image_map_h = int(image_h * ratios[img_idx][0])
             image_map_w = int(image_w * ratios[img_idx][1])

diff --git a/tests/unit/algorithms/detection/tiling/test_tiling_tile_classifier.py b/tests/unit/algorithms/detection/tiling/test_tiling_tile_classifier.py
@@ -81,9 +81,18 @@ def test_openvino_sync(self, mocker):
         mocked_model.return_value = mocker.MagicMock(spec=MaskRCNNModel, model_adapter=adapter_mock)
         params = DetectionConfig(header=self.hyper_parameters.header)
         ov_mask_inferencer = OpenVINOMaskInferencer(params, self.label_schema, "")
-        ov_mask_inferencer.model = mocked_model
+        original_shape = (self.dataset[0].media.width, self.dataset[0].media.height, 3)
         ov_mask_inferencer.model.resize_mask = False
-        ov_mask_inferencer.model.preprocess.return_value = ({"foo": "bar"}, {"baz": "qux"})
+        ov_mask_inferencer.model.preprocess.return_value = (
+            {"foo": "bar"},
+            {"baz": "qux", "original_shape": original_shape},
+        )
+        ov_mask_inferencer.model.postprocess.return_value = (
+            np.array([], dtype=np.float32),
+            np.array([], dtype=np.uint32),
+            np.zeros((0, 4), dtype=np.float32),
+            [],
+        )
         ov_inferencer = OpenVINOTileClassifierWrapper(
             ov_mask_inferencer, tile_classifier_model_file="", tile_classifier_weight_file="", mode="sync"
         )
@@ -99,6 +108,10 @@ def test_openvino_sync(self, mocker):
                 [], [np.zeros((0, 4), dtype=np.float32)], np.zeros((0, 4), dtype=np.float32)
             ),
         )
+        ov_inferencer.tiler.model.infer_sync.return_value = {
+            "feature_vector": np.zeros((1, 5), dtype=np.float32),
+            "saliency_map": np.zeros((1, 1, 2, 2), dtype=np.float32),
+        }
         mocker.patch.object(OpenVINODetectionTask, "load_inferencer", return_value=ov_inferencer)
         ov_task = OpenVINODetectionTask(self.task_env)
         updated_dataset = ov_task.infer(self.dataset)