fix annotation filename to id

DeGirum · Nov 13, 2023 · d9a877f · d9a877f
1 parent 2ab0f04
commit d9a877f
Show file tree

Hide file tree

Showing 3 changed files with 7 additions and 5 deletions.
diff --git a/ultralytics/models/yolo/detect/val.py b/ultralytics/models/yolo/detect/val.py
@@ -242,7 +242,7 @@ def save_one_txt(self, predn, save_conf, shape, file):
     def pred_to_json(self, predn, filename):
         """Serialize YOLO predictions to COCO json format."""
         stem = Path(filename).stem
-        image_id = int(stem) if stem.isnumeric() else stem
+        image_id = (int(stem) if stem.isnumeric() else stem) if self.is_coco else os.path.basename(filename)
         box = ops.xyxy2xywh(predn[:, :4])  # xywh
         box[:, :2] -= box[:, 2:] / 2  # xy center to top-left corner
         for p, b in zip(predn.tolist(), box.tolist()):

diff --git a/ultralytics/models/yolo/pose/val.py b/ultralytics/models/yolo/pose/val.py
@@ -1,5 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
+import os
 from pathlib import Path
 
 import numpy as np
@@ -202,7 +203,7 @@ def plot_predictions(self, batch, preds, ni):
     def pred_to_json(self, predn, filename):
         """Converts YOLO predictions to COCO JSON format."""
         stem = Path(filename).stem
-        image_id = int(stem) if stem.isnumeric() else stem
+        image_id = (int(stem) if stem.isnumeric() else stem) if self.is_coco else os.path.basename(filename)
         box = ops.xyxy2xywh(predn[:, :4])  # xywh
         box[:, :2] -= box[:, 2:] / 2  # xy center to top-left corner
         for p, b in zip(predn.tolist(), box.tolist()):
@@ -217,7 +218,7 @@ def eval_json(self, stats):
         """Evaluates object detection model using COCO JSON format."""
         if self.args.save_json and (self.is_coco or self.args.anno_json) and len(self.jdict):
             anno_json = Path(self.args.anno_json) if self.args.anno_json else self.data['path'] / 'annotations/person_keypoints_val2017.json'  # annotations
-            pred_json = self.save_dir / 'predictions.json'  # predictions
+            pred_json = self.save_dir / 'predictions-pose.json'  # predictions
             LOGGER.info(f'\nEvaluating pycocotools mAP using {pred_json} and {anno_json}...')
             try:  # https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocoEvalDemo.ipynb
                 check_requirements('pycocotools>=2.0.6')

diff --git a/ultralytics/models/yolo/segment/val.py b/ultralytics/models/yolo/segment/val.py
@@ -1,5 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
+import os
 from multiprocessing.pool import ThreadPool
 from pathlib import Path
 
@@ -231,7 +232,7 @@ def single_encode(x):
             return rle
 
         stem = Path(filename).stem
-        image_id = int(stem) if stem.isnumeric() else stem
+        image_id = (int(stem) if stem.isnumeric() else stem) if self.is_coco else os.path.basename(filename)
         box = ops.xyxy2xywh(predn[:, :4])  # xywh
         box[:, :2] -= box[:, 2:] / 2  # xy center to top-left corner
         pred_masks = np.transpose(pred_masks, (2, 0, 1))
@@ -249,7 +250,7 @@ def eval_json(self, stats):
         """Return COCO-style object detection evaluation metrics."""
         if self.args.save_json and (self.is_coco or self.args.anno_json) and len(self.jdict):
             anno_json = Path(self.args.anno_json) if self.args.anno_json else self.data['path'] / 'annotations/instances_val2017.json'  # annotations
-            pred_json = self.save_dir / 'predictions.json'  # predictions
+            pred_json = self.save_dir / 'predictions-seg.json'  # predictions
             LOGGER.info(f'\nEvaluating pycocotools mAP using {pred_json} and {anno_json}...')
             try:  # https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocoEvalDemo.ipynb
                 check_requirements('pycocotools>=2.0.6')