🐞 Bugfix: Incorrect Normal score computation (#152)

Author: ashwinvaidya17

model_api/cpp/models/src/anomaly_model.cpp

@@ -84,6 +84,10 @@ std::unique_ptr<ResultBase> AnomalyModel::postprocess(InferenceResult& infResult
     anomaly_map.convertTo(anomaly_map, CV_8UC1, 255);
 
     pred_score = normalize(pred_score, imageThreshold);
+    if (pred_label == labels[0]) {    // normal label
+        pred_score = 1 - pred_score;  // Score of normal is 1 - score of anomaly
+    }
+
     if (!anomaly_map.empty()) {
         cv::resize(anomaly_map, anomaly_map, cv::Size{inputImgSize.inputImgWidth, inputImgSize.inputImgHeight});
     }
@@ -106,6 +110,10 @@ cv::Mat AnomalyModel::normalize(cv::Mat& tensor, float threshold) {
     return normalized;
 }
 
+/// @brief Normalize the value to be in the range [0, 1]. Centered around 0.5 and scaled by the normalization scale.
+/// @param value Unbounded value to be normalized.
+/// @param threshold This is the value that is subtracted from the input value before normalization.
+/// @return value between 0 and 1.
 double AnomalyModel::normalize(double& value, float threshold) {
     double normalized = ((value - threshold) / normalizationScale) + 0.5f;
     return std::min(std::max(normalized, 0.), 1.);

model_api/python/openvino/model_api/models/anomaly.py

@@ -79,6 +79,9 @@ def postprocess(self, outputs: dict[str, np.ndarray], meta: dict[str, Any]):
         # normalize
         pred_score = self._normalize(pred_score, self.image_threshold)
 
+        if pred_label == self.labels[0]:  # normal
+            pred_score = 1 - pred_score  # Score of normal is 1 - score of anomaly
+
         # resize outputs
         if anomaly_map is not None:
             anomaly_map = cv2.resize(

model_api/python/openvino/model_api/models/utils.py

@@ -43,7 +43,7 @@ def __str__(self) -> str:
         pred_mask_min, pred_mask_max = self._compute_min_max(self.pred_mask)
         return (
             f"anomaly_map min:{anomaly_map_min} max:{anomaly_map_max};"
-            f"pred_score:{self.pred_score};"
+            f"pred_score:{np.round(self.pred_score, 1)};"
             f"pred_label:{self.pred_label};"
             f"pred_mask min:{pred_mask_min} max:{pred_mask_max};"
         )

tests/python/accuracy/public_scope.json

@@ -367,7 +367,7 @@
             {
                 "image": "coco128/images/train2017/000000000074.jpg",
                 "reference": [
-                    "anomaly_map min:152 max:255;pred_score:1.0;pred_label:Anomaly;pred_mask min:1 max:1;"
+                    "anomaly_map min:151 max:255;pred_score:1.0;pred_label:Anomaly;pred_mask min:1 max:1;"
                 ]
             }
         ]
@@ -379,7 +379,7 @@
             {
                 "image": "coco128/images/train2017/000000000074.jpg",
                 "reference": [
-                    "anomaly_map min:126 max:255;pred_score:1.0;pred_label:Anomaly;pred_mask min:0 max:1;"
+                    "anomaly_map min:124 max:225;pred_score:0.9;pred_label:Anomaly;pred_mask min:0 max:1;"
                 ]
             }
         ]