diff --git a/README.md b/README.md
index 7aa89f1e..7977c7a5 100755
--- a/README.md
+++ b/README.md
@@ -147,31 +147,31 @@ $ 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
**36.3** |29.1
51.8
52.3
**55.5**
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0
31.2
33.9
**39.8** |33.0
55.4
56.9
**59.6**
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6
32.7
35.6
**41.3** |34.9
57.7
59.5
**61.3**
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6
33.1
37.0
**41.7** |35.4
58.2
60.7
**61.5**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |320 |14.0
28.7
30.5
**36.4** |29.1
51.8
52.3
**55.7**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0
31.2
33.9
**40.0** |33.0
55.4
56.9
**60.0**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6
32.7
35.6
**41.5** |34.9
57.7
59.5
**61.4**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6
33.1
37.0
**41.9** |35.4
58.2
60.7
**61.6**
```bash
-$ python3 test.py --cfg yolov3-spp.cfg --weights yolov3-spp-ultralytics.pt --img 608
+$ python3 test.py --cfg yolov3-spp.cfg --weights yolov3-spp-ultralytics.pt --img 608
-Namespace(batch_size=32, cfg='yolov3-spp.cfg', conf_thres=0.001, data='data/coco2014.data', device='', img_size=608, iou_thres=0.6, save_json=True, single_cls=False, task='test', weights='last54.pt')
-Using CUDA device0 _CudaDeviceProperties(name='Tesla P100-PCIE-16GB', total_memory=16280MB)
+Namespace(batch_size=32, cfg='yolov3-spp.cfg', conf_thres=0.001, data='data/coco2014.data', device='', img_size=608, iou_thres=0.6, save_json=True, single_cls=False, task='test', weights='yolov3-spp-ultralytics.pt')
+Using CUDA device0 _CudaDeviceProperties(name='Tesla T4', total_memory=15079MB)
- Class Images Targets P R mAP@0.5 F1: 100% 157/157 [04:25<00:00, 1.04it/s]
- all 5e+03 3.51e+04 0.0467 0.886 0.607 0.0875
- Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.415
- Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.615
- Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.443
- Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.245
- Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.458
- Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.531
- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.341
+ Class Images Targets P R mAP@0.5 F1: 100% 157/157 [04:25<00:00, 1.01s/it]
+ all 5e+03 3.51e+04 0.0453 0.885 0.609 0.0852
+ Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.417
+ Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.616
+ Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.448
+ Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.242
+ Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.462
+ Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.522
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.337
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.559
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.611
- Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.441
- Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.658
- Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.748
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.436
+ Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.659
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.741
```
# Reproduce Our Results