diff --git a/README.md b/README.md
index c527cd00..024ae595 100755
--- a/README.md
+++ b/README.md
@@ -147,34 +147,34 @@ $ python3 test.py --cfg yolov3-spp.cfg --weights yolov3-spp-ultralytics.pt
|Size |COCO mAP
@0.5...0.95 |COCO mAP
@0.5
--- | --- | --- | ---
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |320 |14.0
28.7
30.5
**38.9** |29.1
51.8
52.3
**56.9**
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0
31.2
33.9
**42.5** |33.0
55.4
56.9
**61.1**
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6
32.7
35.6
**43.6** |34.9
57.7
59.5
**62.5**
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6
33.1
37.0
**44.0** |35.4
58.2
60.7
**62.6**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |320 |14.0
28.7
30.5
**37.0** |29.1
51.8
52.3
**56.0**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0
31.2
33.9
**40.7** |33.0
55.4
56.9
**60.4**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6
32.7
35.6
**42.0** |34.9
57.7
59.5
**61.9**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6
33.1
37.0
**42.4** |35.4
58.2
60.7
**62.0**
```bash
$ python3 test.py --cfg yolov3-spp.cfg --weights yolov3-spp-ultralytics.pt --img 640 --augment
-Namespace(augment=True, batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.001, data='coco2014.data', device='', img_size=608, iou_thres=0.7, save_json=True, single_cls=False, task='test', weights='weights/yolov3-spp-ultralytics.pt')
+Namespace(augment=True, batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.001, data='coco2014.data', device='', img_size=640, iou_thres=0.6, save_json=True, single_cls=False, task='test', weights='weight
Using CUDA device0 _CudaDeviceProperties(name='Tesla V100-SXM2-16GB', total_memory=16130MB)
Class Images Targets P R mAP@0.5 F1: 100%|█████████| 313/313 [03:00<00:00, 1.74it/s]
- all 5e+03 3.51e+04 0.35 0.737 0.624 0.47
+ all 5e+03 3.51e+04 0.396 0.731 0.634 0.509
- Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.457
- Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.635
- Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.502
- Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.282
- Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.501
- Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.589
- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.359
- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.621
- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.828
- Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.772
- Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.861
- Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.893
+ Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.447
+ Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.641
+ Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.485
+ Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.271
+ Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.492
+ Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.357
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.587
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.652
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.488
+ Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.701
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.787
-Speed: 21.6/2.6/24.1 ms inference/NMS/total per 640x640 image at batch-size 16
+Speed: 21.3/3.0/24.4 ms inference/NMS/total per 640x640 image at batch-size 16
```
# Reproduce Our Results