Update README.md

README.md

@@ -16,22 +16,22 @@ YOLOS model fine-tuned on COCO 2017 object detection (118k annotated images). It
 
 
 ## Model description
-This model has been finetuned on the following [crowd-detection dataset](https://universe.roboflow.com/institut-teknologi-nasional-bandung-mxgtc/crowd-detection-i75bl) (669 samples) with the following results on the test set:
+This model has been finetuned on these two datasets[[1](https://universe.roboflow.com/new-workspace-phqon/object-detection-brcrx)][[2](https://universe.roboflow.com/tank-detect/person-dataset-kzsop)] (2604 samples) with the following results on the test set:
 
 ```
-IoU metric: bbox
- Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.630
- Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.908
- Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.672
- Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000
- Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.005
- Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.636
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.431
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.740
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.762
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.300
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.766
+ IoU metric: bbox
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.472
+ Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.856
+ Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.494
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.029
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.420
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.633
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.381
+ 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 ] = 0.662
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.157
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.647
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.775
 ```
 
 ## How to use
@@ -64,7 +64,7 @@ Refer to the [documentation](https://huggingface.co/docs/transformers/main/en/mo
 
 ## Intended uses & limitations
 
-This model is more of an experiment on a small scale and will need retraining on a better dataset. This fine-tuned model performs best when detecting individuals who are relatively close (but not too close) to the viewpoint. As indicated by the metrics, it struggles to identify individuals farther away.
+This model is more of an experiment on a small scale and will need retraining on a more diverse dataset. This fine-tuned model performs best when detecting individuals who are relatively close to the viewpoint. As indicated by the metrics, it struggles to identify individuals farther away.
 
 ### Training hyperparameters