[Enhancement]: Support empty val. (#310)

nanodet/evaluator/coco_detection.py

@@ -15,6 +15,7 @@
 import copy
 import json
 import os
+import warnings
 
 from pycocotools.cocoeval import COCOeval
 
@@ -65,6 +66,17 @@ def results2json(self, results):
 
     def evaluate(self, results, save_dir, rank=-1):
         results_json = self.results2json(results)
+        if len(results_json) == 0:
+            warnings.warn(
+                "Detection result is empty! Please check whether "
+                "training set is too small (need to increase val_interval "
+                "in config and train more epochs). Or check annotation "
+                "correctness."
+            )
+            empty_eval_results = {}
+            for key in self.metric_names:
+                empty_eval_results[key] = 0
+            return empty_eval_results
         json_path = os.path.join(save_dir, "results{}.json".format(rank))
         json.dump(results_json, open(json_path, "w"))
         coco_dets = self.coco_api.loadRes(json_path)