add stride to datasets.py

train.py

@@ -160,7 +160,8 @@ def train(hyp):
                                   hyp=hyp,  # augmentation hyperparameters
                                   rect=opt.rect,  # rectangular training
                                   cache_images=opt.cache_images,
-                                  single_cls=opt.single_cls)
+                                  single_cls=opt.single_cls,
+                                  stride=gs)
     mlc = np.concatenate(dataset.labels, 0)[:, 0].max()  # max label class
     assert mlc < nc, 'Label class %g exceeds nc=%g in %s. Correct your labels or your model.' % (mlc, nc, opt.cfg)
 
@@ -179,7 +180,8 @@ def train(hyp):
                                                                  hyp=hyp,
                                                                  rect=True,
                                                                  cache_images=opt.cache_images,
-                                                                 single_cls=opt.single_cls),
+                                                                 single_cls=opt.single_cls,
+                                                                 stride=gs),
                                              batch_size=batch_size,
                                              num_workers=nw,
                                              pin_memory=True,