diff --git a/README.md b/README.md
index 7246b589..a7c90ed8 100755
--- a/README.md
+++ b/README.md
@@ -151,24 +151,24 @@ YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**YOLOv3-SPP ultralytics** |416 |16.0<br>
 YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**YOLOv3-SPP ultralytics** |608 |16.6<br>33.0<br>37.0<br>**40.7** |35.5<br>57.9<br>60.6<br>**60.7**
 
 ```bash
-$ python3 test.py --save-json --img-size 608 --nms-thres 0.65 --weights ultralytics68.pt
-Namespace(batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.001, data='data/coco.data', device='', img_size=608, iou_thres=0.5, nms_thres=0.65, save_json=True, weights='ultralytics68.pt')
-Using CUDA device0 _CudaDeviceProperties(name='Tesla T4', total_memory=15079MB)
+Namespace(batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.001, data='data/coco.data', device='', img_size=608, iou_thres=0.5, nms_thres=0.7, save_json=True, weights='ultralytics68.pt')
+Using CUDA device0 _CudaDeviceProperties(name='Tesla P100-PCIE-16GB', total_memory=16280MB)
 
-               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 313/313 [06:52<00:00,  1.24it/s]
-                 all     5e+03  3.58e+04     0.107     0.779      0.59     0.182
- Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.404 <---
- Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.597 <---
- Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.438
- Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.241
- Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.444
+Downloading https://drive.google.com/uc?export=download&id=1Jm8kqnMdMGUUxGo8zMFZMJ0eaPwLkxSG as ultralytics68.pt... Done (2.2s)
+               Class    Images   Targets         P         R   mAP@0.5        F1: 100% 313/313 [16:23<00:00,  1.59s/it]
+                 all     5e+03  3.58e+04    0.0465     0.831     0.586    0.0868
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.407
+ Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.598
+ Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.444
+ 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 ] = 0.446
  Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.511
  Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.326
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.533
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.570
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.393
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.614
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.691
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.537
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.595
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.427
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.641
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.706
 ```
 
 # Citation