diff --git a/ultralytics/models/yolo/detect/val.py b/ultralytics/models/yolo/detect/val.py
index 31f0fdc0..9ad9a4fb 100644
--- a/ultralytics/models/yolo/detect/val.py
+++ b/ultralytics/models/yolo/detect/val.py
@@ -74,7 +74,7 @@ class DetectionValidator(BaseValidator):
             and (val.endswith(f"{os.sep}val2017.txt") or val.endswith(f"{os.sep}test-dev2017.txt"))
         )  # is COCO
         self.is_lvis = isinstance(val, str) and "lvis" in val and not self.is_coco  # is LVIS
-        self.class_map = converter.coco80_to_coco91_class() if self.is_coco else list(range(len(model.names)))
+        self.class_map = converter.coco80_to_coco91_class() if self.is_coco else list(range(1, len(model.names) + 1))
         self.args.save_json |= self.args.val and (self.is_coco or self.is_lvis) and not self.training  # run final val
         self.names = model.names
         self.nc = len(model.names)
@@ -288,8 +288,7 @@ class DetectionValidator(BaseValidator):
             self.jdict.append(
                 {
                     "image_id": image_id,
-                    "category_id": self.class_map[int(p[5])]
-                    + (1 if self.is_lvis else 0),  # index starts from 1 if it's lvis
+                    "category_id": self.class_map[int(p[5])],
                     "bbox": [round(x, 3) for x in b],
                     "score": round(p[4], 5),
                 }
diff --git a/ultralytics/models/yolo/obb/val.py b/ultralytics/models/yolo/obb/val.py
index 93bb2bfa..9e9bcf7d 100644
--- a/ultralytics/models/yolo/obb/val.py
+++ b/ultralytics/models/yolo/obb/val.py
@@ -160,7 +160,7 @@ class OBBValidator(DetectionValidator):
             for d in data:
                 image_id = d["image_id"]
                 score = d["score"]
-                classname = self.names[d["category_id"]].replace(" ", "-")
+                classname = self.names[d["category_id"] - 1].replace(" ", "-")
                 p = d["poly"]
 
                 with open(f'{pred_txt / f"Task1_{classname}"}.txt', "a") as f:
@@ -175,7 +175,7 @@ class OBBValidator(DetectionValidator):
                 image_id = d["image_id"].split("__")[0]
                 pattern = re.compile(r"\d+___\d+")
                 x, y = (int(c) for c in re.findall(pattern, d["image_id"])[0].split("___"))
-                bbox, score, cls = d["rbox"], d["score"], d["category_id"]
+                bbox, score, cls = d["rbox"], d["score"], d["category_id"] - 1
                 bbox[0] += x
                 bbox[1] += y
                 bbox.extend([score, cls])