Update evaluation script.

evaluation.py

@@ -34,12 +34,12 @@ if __name__ == "__main__":
         help="Path to judge model checkpoint.",
     )
     parser.add_argument(
-        "--video_path",
+        "--video_dir",
         type=str,
         help="Path to the generated video directory.",
     )
     parser.add_argument(
-        "--save_path",
+        "--save_name",
         type=str,
         help="Path to save evaluation results.",
     )
@@ -47,25 +47,27 @@ if __name__ == "__main__":
     args = parser.parse_args()
 
     validation_set = load("./worldmodelbench.json")
-    save_name = args.judge.replace("/", "_")
     if args.cot:
-        save_name += "_cot"
+        args.save_name += "_cot"
     results = None
-    if os.path.exists(save_name):
-        results = load(save_name)
-        preds = results["preds"]
-        accs = results["accs"]
+    if os.path.exists(args.save_name):
+        results = load(args.save_name)
+        try:
+            preds = results["preds"]
+            accs = results["accs"]
+        except:
+            raise "Expected keys are not found in the results."
     else:
         model = llava.load(args.judge)
-        video_root = args.video_path
 
         preds = dict()
         accs = defaultdict(list)
         for vid, v_i in tqdm(enumerate(validation_set), total=len(validation_set)):
+            ## Load video
             video_name = v_i["first_frame"].split("/")[-1].split(".")[0]
-            video = os.path.join(video_root, video_name + ".mp4")
+            video = os.path.join(args.video_dir, video_name + ".mp4")
             video = llava.Video(video)
-            ## traverse criterions
+            ## Traverse criterions
             for k in ["instruction", "physical_laws", "commonsense"]:
                 preds_i = []
                 prompt_template = PROMPT_TEMPLATES[k]
@@ -83,6 +85,7 @@ if __name__ == "__main__":
                             ).replace("Let's analyze step-by-step and conclude with", "Answer with")
                         pred = model.generate_content([video, text_prompt])
                         preds_i.append(pred)
+                        ## Always ask for violations, so a "No" is preferred!
                         accs_i.append("no" in pred.lower())
                     accs[k].append(np.mean(accs_i))
                 else:
@@ -107,7 +110,8 @@ if __name__ == "__main__":
             print(f"{k} accuracy: {np.mean(v) * 100}%.")
         else:
             print(f"{k} accuracy: {v}%.")
+    ## Save results
     if results is None:
         results = {"preds": preds, "accs": accs}
-        dump(results, f"./{save_name}.json", indent=4)
+        dump(results, f"./{args.save_name}.json", indent=4)