Fix icevision task metric names

CHANGELOG.md

@@ -42,6 +42,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Fixed a bug where `InstanceSegmentation` would fail if samples had an inconsistent number of bboxes, labels, and masks (these will now be treated as negative samples) ([#1222](https://github.com/PyTorchLightning/lightning-flash/pull/1222))
 
+- Fixed a bug where `ObjectDetector`, `InstanceSegmentation`, and `KeypointDetector` would log train and validation metrics with the same name ([#1252](https://github.com/PyTorchLightning/lightning-flash/pull/1252))
+
 ## [0.7.0] - 2022-02-15
 
 ### Added

flash/core/data/utils.py

@@ -39,6 +39,7 @@
     RunningStage.VALIDATING: "val",
     RunningStage.PREDICTING: "predict",
     RunningStage.SERVING: "serve",
+    RunningStage.SANITY_CHECKING: "val",
 }
 _STAGES_PREFIX_VALUES = {"train", "test", "val", "predict", "serve"}
 

flash/core/integrations/icevision/adapter.py

@@ -42,8 +42,8 @@ class SimpleCOCOMetric(COCOMetric):
     def finalize(self) -> Dict[str, float]:
         logs = super().finalize()
         return {
-            "Precision (IoU=0.50:0.95,area=all)": logs["AP (IoU=0.50:0.95) area=all"],
-            "Recall (IoU=0.50:0.95,area=all,maxDets=100)": logs["AR (IoU=0.50:0.95) area=all maxDets=100"],
+            "precision (IoU=0.50:0.95,area=all)": logs["AP (IoU=0.50:0.95) area=all"],
+            "recall (IoU=0.50:0.95,area=all,maxDets=100)": logs["AR (IoU=0.50:0.95) area=all maxDets=100"],
         }
 
 

flash/core/integrations/icevision/wrappers.py

@@ -15,16 +15,19 @@
 
 import torch
 
+from flash.core.data.utils import _STAGES_PREFIX
 from flash.core.utilities.imports import _ICEVISION_AVAILABLE
 
 if _ICEVISION_AVAILABLE:
     from icevision.models.ross.efficientdet.lightning.model_adapter import ModelAdapter as EffDetModelAdapter
 
 
-def _log_with_prog_bar_override(log, name, value, **kwargs):
+def _log_with_name_and_prog_bar_override(log, adapter, name, value, **kwargs):
     if "prog_bar" not in kwargs:
         kwargs["prog_bar"] = True
-    return log(name.split("/")[-1], value, **kwargs)
+    metric = name.split("/")[-1]
+    metric = f"{_STAGES_PREFIX[adapter.trainer.state.stage]}_{metric}"
+    return log(metric, value, **kwargs)
 
 
 def _effdet_validation_step(validation_step, batch, batch_idx):
@@ -36,7 +39,7 @@ def _effdet_validation_step(validation_step, batch, batch_idx):
 
 def wrap_icevision_adapter(adapter):
     if not isinstance(adapter.log, partial):
-        adapter.log = partial(_log_with_prog_bar_override, adapter.log)
+        adapter.log = partial(_log_with_name_and_prog_bar_override, adapter.log, adapter)
 
     if isinstance(adapter, EffDetModelAdapter) and not isinstance(adapter.validation_step, partial):
         adapter.validation_step = partial(_effdet_validation_step, adapter.validation_step)