Return raw anomaly maps as metadata (#2217)

* return raw anomaly map instead of colormap

* return raw heatmap in openvino inference

* Update changelog

* convert anomaly map to numpy

Author: djdameln

CHANGELOG.md

@@ -53,6 +53,7 @@ All notable changes to this project will be documented in this file.
 
 ### Bug fixes
 
+- Return raw anomaly map instead of colormap as metadata to prevent applying colormap conversion twice (<https://github.com/openvinotoolkit/training_extensions/pull/2217>)
 - Hotfix: use 0 confidence threshold when computing best threshold based on F1
 
 ## \[v1.2.2\]

otx/algorithms/anomaly/adapters/anomalib/callbacks/inference.py

@@ -20,7 +20,6 @@
 import pytorch_lightning as pl
 import torch
 from anomalib.models import AnomalyModule
-from anomalib.post_processing import anomaly_map_to_color_map
 from pytorch_lightning.callbacks import Callback
 from torch import Tensor
 
@@ -82,7 +81,7 @@ def on_predict_epoch_end(self, _trainer: pl.Trainer, _pl_module: AnomalyModule,
                     name="Anomaly Map",
                     type="anomaly_map",
                     annotation_scene=dataset_item.annotation_scene,
-                    numpy=anomaly_map_to_color_map(anomaly_map.squeeze().numpy(), normalize=False),
+                    numpy=(anomaly_map * 255).cpu().numpy().astype(np.uint8),
                 )
             )
 

otx/algorithms/anomaly/tasks/openvino.py

@@ -24,7 +24,6 @@
 import numpy as np
 from addict import Dict as ADDict
 from anomalib.deploy import OpenVINOInferencer
-from anomalib.post_processing import anomaly_map_to_color_map
 from compression.api import DataLoader
 from compression.engines.ie_engine import IEEngine
 from compression.graph import load_model, save_model
@@ -193,7 +192,7 @@ def infer(self, dataset: DatasetEntity, inference_parameters: InferenceParameter
                 raise ValueError(f"Unknown task type: {self.task_type}")
 
             dataset_item.append_labels([ScoredLabel(label=label, probability=float(probability))])
-            anomaly_map = anomaly_map_to_color_map(image_result.anomaly_map, normalize=False)
+            anomaly_map = (image_result.anomaly_map * 255).astype(np.uint8)
             heatmap_media = ResultMediaEntity(
                 name="Anomaly Map",
                 type="anomaly_map",