Replace 'ground truth' with 'labels' (#1337)

* Replace 'ground truth' with 'labels'

* Using torch... update

utils/general.py

@@ -275,10 +275,10 @@ def ap_per_class(tp, conf, pred_cls, target_cls, plot=False, fname='precision-re
     ap, p, r = np.zeros(s), np.zeros(s), np.zeros(s)
     for ci, c in enumerate(unique_classes):
         i = pred_cls == c
-        n_gt = (target_cls == c).sum()  # Number of ground truth objects
-        n_p = i.sum()  # Number of predicted objects
+        n_l = (target_cls == c).sum()  # number of labels
+        n_p = i.sum()  # number of predictions
 
-        if n_p == 0 or n_gt == 0:
+        if n_p == 0 or n_l == 0:
             continue
         else:
             # Accumulate FPs and TPs
@@ -286,7 +286,7 @@ def ap_per_class(tp, conf, pred_cls, target_cls, plot=False, fname='precision-re
             tpc = tp[i].cumsum(0)
 
             # Recall
-            recall = tpc / (n_gt + 1e-16)  # recall curve
+            recall = tpc / (n_l + 1e-16)  # recall curve
             r[ci] = np.interp(-pr_score, -conf[i], recall[:, 0])  # r at pr_score, negative x, xp because xp decreases
 
             # Precision
@@ -1076,8 +1076,8 @@ def plot_images(images, targets, paths=None, fname='images.jpg', names=None, max
             image_targets = targets[targets[:, 0] == i]
             boxes = xywh2xyxy(image_targets[:, 2:6]).T
             classes = image_targets[:, 1].astype('int')
-            gt = image_targets.shape[1] == 6  # ground truth if no conf column
-            conf = None if gt else image_targets[:, 6]  # check for confidence presence (gt vs pred)
+            labels = image_targets.shape[1] == 6  # labels if no conf column
+            conf = None if labels else image_targets[:, 6]  # check for confidence presence (label vs pred)
 
             boxes[[0, 2]] *= w
             boxes[[0, 2]] += block_x
@@ -1087,8 +1087,8 @@ def plot_images(images, targets, paths=None, fname='images.jpg', names=None, max
                 cls = int(classes[j])
                 color = color_lut[cls % len(color_lut)]
                 cls = names[cls] if names else cls
-                if gt or conf[j] > 0.3:  # 0.3 conf thresh
-                    label = '%s' % cls if gt else '%s %.1f' % (cls, conf[j])
+                if labels or conf[j] > 0.3:  # 0.3 conf thresh
+                    label = '%s' % cls if labels else '%s %.1f' % (cls, conf[j])
                     plot_one_box(box, mosaic, label=label, color=color, line_thickness=tl)
 
         # Draw image filename labels