feat: update score

web_server.py

@@ -7,6 +7,7 @@ import io
 import enum
 import hugsim_env
 import subprocess as sp
+import shutil
 from collections import deque, OrderedDict
 from datetime import datetime
 from typing import Any, Dict, Optional, List
@@ -208,6 +209,7 @@ class EnvHandler:
         if self.env is not None:
             del self.env
         self.env = None
+        shutil.rmtree(self.base_output, ignore_errors=True)
         self._log("Environment closed.")
 
     def reset_env(self):
@@ -216,6 +218,7 @@ class EnvHandler:
         """
         self._log_list = deque(maxlen=100)
         self._done = False
+        self._score_list = []
         self._switch_scene(0)
         self._log("Environment reset complete.")
     
@@ -299,6 +302,7 @@ class EnvHandler:
         results = hugsim_evaluate([self._save_data], ground_xyz, scene_xyz)
         with open(os.path.join(self.cur_otuput, 'eval.json'), 'w') as f:
             json.dump(results, f)
+        self._score_list.append(results.copy())
         
         self._log(f"Scene {self.cur_scene_index} completed. Evaluation results saved.")
     
@@ -322,16 +326,9 @@ class EnvHandler:
         """
         if not self._done:
             raise ValueError("Environment is not done yet. Cannot calculate score.")
-        
-        all_score_json = []
-        for scene_config in self.scene_list:
-            scene_output = os.path.join(self.base_output, scene_config.name)
-            with open(os.path.join(scene_output, 'eval.json'), 'r') as f:
-                score_json = json.load(f)
-            all_score_json.append(score_json)
-
-        rc = np.mean([score['rc'] for score in all_score_json]).round(4)
-        hdscore = np.mean([score['hdscore'] for score in all_score_json]).round(4)
+
+        rc = np.mean([float(score['rc']) for score in self._score_list]).round(4)
+        hdscore = np.mean([float(score['hdscore']) for score in self._score_list]).round(4)
         return {"rc": rc, "hdscore": hdscore}