Merge remote-tracking branch 'origin/docstrings' into docstrings

utils/metrics.py

@@ -180,7 +180,9 @@ def process_batch(self, detections, labels):
                     self.matrix[dc, self.nc] += 1  # predicted background
 
     def tp_fp(self):
-        """Calculates true positives (tp) and false positives (fp) excluding the background class from the confusion matrix."""
+        """Calculates true positives (tp) and false positives (fp) excluding the background class from the confusion
+        matrix.
+        """
         tp = self.matrix.diagonal()  # true positives
         fp = self.matrix.sum(1) - tp  # false positives
         # fn = self.matrix.sum(0) - tp  # false negatives (missed detections)
@@ -226,7 +228,11 @@ def print(self):
 
 
 def bbox_iou(box1, box2, xywh=True, GIoU=False, DIoU=False, CIoU=False, eps=1e-7):
-    """Calculates IoU, GIoU, DIoU, or CIoU between two boxes, supporting xywh/xyxy formats. Input shapes are box1(1,4) to box2(n,4)."""
+    """
+    Calculates IoU, GIoU, DIoU, or CIoU between two boxes, supporting xywh/xyxy formats.
+
+    Input shapes are box1(1,4) to box2(n,4).
+    """
 
     # Get the coordinates of bounding boxes
     if xywh:  # transform from xywh to xyxy
@@ -316,7 +322,9 @@ def bbox_ioa(box1, box2, eps=1e-7):
 
 
 def wh_iou(wh1, wh2, eps=1e-7):
-    """Calculates the Intersection over Union (IoU) for two sets of widths and heights; `wh1` and `wh2` should be nx2 and mx2 tensors."""
+    """Calculates the Intersection over Union (IoU) for two sets of widths and heights; `wh1` and `wh2` should be nx2
+    and mx2 tensors.
+    """
     wh1 = wh1[:, None]  # [N,1,2]
     wh2 = wh2[None]  # [1,M,2]
     inter = torch.min(wh1, wh2).prod(2)  # [N,M]
@@ -328,7 +336,9 @@ def wh_iou(wh1, wh2, eps=1e-7):
 
 @threaded
 def plot_pr_curve(px, py, ap, save_dir=Path("pr_curve.png"), names=()):
-    """Plots precision-recall curve, optionally per class, saving to `save_dir`; `px`, `py` are lists, `ap` is Nx2 array, `names` optional."""
+    """Plots precision-recall curve, optionally per class, saving to `save_dir`; `px`, `py` are lists, `ap` is Nx2
+    array, `names` optional.
+    """
     fig, ax = plt.subplots(1, 1, figsize=(9, 6), tight_layout=True)
     py = np.stack(py, axis=1)