ultralytics 8.0.80 single-line docstring fixes (#2060)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ultralytics/yolo/v8/segment/predict.py

@@ -10,7 +10,7 @@ from ultralytics.yolo.v8.detect.predict import DetectionPredictor
 class SegmentationPredictor(DetectionPredictor):
 
     def postprocess(self, preds, img, orig_imgs):
-        # TODO: filter by classes
+        """TODO: filter by classes."""
         p = ops.non_max_suppression(preds[0],
                                     self.args.conf,
                                     self.args.iou,

ultralytics/yolo/v8/segment/train.py

@@ -140,7 +140,7 @@ class SegLoss(Loss):
         return loss.sum() * batch_size, loss.detach()  # loss(box, cls, dfl)
 
     def single_mask_loss(self, gt_mask, pred, proto, xyxy, area):
-        # Mask loss for one image
+        """Mask loss for one image."""
         pred_mask = (pred @ proto.view(self.nm, -1)).view(-1, *proto.shape[1:])  # (n, 32) @ (32,80,80) -> (n,80,80)
         loss = F.binary_cross_entropy_with_logits(pred_mask, gt_mask, reduction='none')
         return (crop_mask(loss, xyxy).mean(dim=(1, 2)) / area).mean()

ultralytics/yolo/v8/segment/val.py

@@ -52,7 +52,7 @@ class SegmentationValidator(DetectionValidator):
         return p, proto
 
     def update_metrics(self, preds, batch):
-        # Metrics
+        """Metrics."""
         for si, (pred, proto) in enumerate(zip(preds[0], preds[1])):
             idx = batch['batch_idx'] == si
             cls = batch['cls'][idx]
@@ -179,7 +179,7 @@ class SegmentationValidator(DetectionValidator):
         self.plot_masks.clear()
 
     def pred_to_json(self, predn, filename, pred_masks):
-        # Save one JSON result
+        """Save one JSON result."""
         # Example result = {"image_id": 42, "category_id": 18, "bbox": [258.15, 41.29, 348.26, 243.78], "score": 0.236}
         from pycocotools.mask import encode  # noqa