Update README.md
Browse files
README.md
CHANGED
@@ -6,24 +6,49 @@ pipeline_tag: image-classification
|
|
6 |
datasets:
|
7 |
- Rokyuto/Banknotes
|
8 |
tags:
|
|
|
9 |
- banknotes
|
10 |
- banknotes classification
|
11 |
-
- yolov11
|
12 |
widget:
|
13 |
- text: Banknotes Classification
|
14 |
output:
|
15 |
url: model_predictions/prediction_50 EUR_20240923_190943.jpg
|
16 |
-
|
17 |
-
-
|
18 |
-
|
19 |
-
|
20 |
-
|
21 |
-
|
22 |
-
|
23 |
-
|
24 |
-
|
25 |
-
|
26 |
-
|
27 |
-
|
28 |
-
|
29 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
6 |
datasets:
|
7 |
- Rokyuto/Banknotes
|
8 |
tags:
|
9 |
+
- yolov11
|
10 |
- banknotes
|
11 |
- banknotes classification
|
|
|
12 |
widget:
|
13 |
- text: Banknotes Classification
|
14 |
output:
|
15 |
url: model_predictions/prediction_50 EUR_20240923_190943.jpg
|
16 |
+
model-index:
|
17 |
+
- name: banknotes-recognizer
|
18 |
+
results:
|
19 |
+
- task:
|
20 |
+
type: object-classification
|
21 |
+
metrics:
|
22 |
+
- type: precision
|
23 |
+
name: Precision
|
24 |
+
value: 0.976
|
25 |
+
- type: recall
|
26 |
+
name: Recall
|
27 |
+
value: 0.974
|
28 |
+
- type: mAP50
|
29 |
+
name: mAP50
|
30 |
+
value: 0.991
|
31 |
+
- type: mAP50-95
|
32 |
+
name: mAP50-95
|
33 |
+
value: 0.789
|
34 |
+
---
|
35 |
+
|
36 |
+
<details><summary>Metrics</summary>
|
37 |
+
|
38 |
+
YOLO11m summary (fused): 303 layers, 20,037,742 parameters, 0 gradients, 67.7 GFLOPs
|
39 |
+
|
40 |
+
| Class | Images | Instances | Box(P) | R | mAP50 | mAP50-95 |
|
41 |
+
|--------|--------|-----------|---------|-------|-------|----------|
|
42 |
+
| all | 110 | 256 | 0.969 | 0.977 | 0.989 | 0.801 |
|
43 |
+
| 5 BGN | 10 | 35 | 0.969 | 0.9 | 0.975 | 0.712 |
|
44 |
+
| 10 BGN | 9 | 29 | 0.96 | 1 | 0.976 | 0.773 |
|
45 |
+
| 20 BGN | 7 | 25 | 0.996 | 0.96 | 0.993 | 0.795 |
|
46 |
+
| 50 BGN | 7 | 24 | 0.996 | 0.966 | 0.989 | 0.801 |
|
47 |
+
| 100 BGN| 13 | 41 | 0.975 | 0.955 | 0.982 | 0.823 |
|
48 |
+
| 5 EUR | 18 | 19 | 0.863 | 0.991 | 0.986 | 0.837 |
|
49 |
+
| 10 EUR | 14 | 38 | 0.998 | 1 | 0.995 | 0.787 |
|
50 |
+
| 20 EUR | 15 | 15 | 0.986 | 1 | 0.995 | 0.861 |
|
51 |
+
| 50 EUR | 7 | 7 | 0.97 | 1 | 0.995 | 0.920 |
|
52 |
+
| 100 EUR| 10 | 23 | 0.97 | 1 | 0.995 | 0.675 |
|
53 |
+
|
54 |
+
</details>
|