diff --git a/train.py b/train.py
index 24bf2063..401bf40b 100644
--- a/train.py
+++ b/train.py
@@ -313,7 +313,7 @@ if __name__ == '__main__':
     parser.add_argument('--batch-size', type=int, default=8, help='batch size')
     parser.add_argument('--accumulate', type=int, default=8, help='number of batches to accumulate before optimizing')
     parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
-    parser.add_argument('--data-cfg', type=str, default='data/coco_64img.data', help='coco.data file path')
+    parser.add_argument('--data-cfg', type=str, default='../supermarket2/supermarket2.data', help='coco.data file path')
     parser.add_argument('--single-scale', action='store_true', help='train at fixed size (no multi-scale)')
     parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
     parser.add_argument('--resume', action='store_true', help='resume training flag')
@@ -360,7 +360,7 @@ if __name__ == '__main__':
             # Mutate hyperparameters
             old_hyp = hyp.copy()
             init_seeds(seed=int(time.time()))
-            s = [0.5, .5, .5, .5, .5, .5, .5, .5, .05, .5]  # xy, wh, cls, conf, iou_t, lr0, lrf, momentum, weight_decay
+            s = [.5, .5, .5, .5, .5, .5, .5, .5, .05, .5]  # xy, wh, cls, conf, iou_t, lr0, lrf, momentum, weight_decay
             for i, k in enumerate(hyp.keys()):
                 x = (np.random.randn(1) * s[i] + 1) ** 1.1  # plt.hist(x.ravel(), 100)
                 hyp[k] = hyp[k] * float(x)  # vary by about 30% 1sigma