README.md · Rokyuto/BanknotesRecognition at main

metadata

license: agpl-3.0
base_model:
  - Ultralytics/YOLO11
pipeline_tag: image-classification
datasets:
  - Rokyuto/Banknotes
tags:
  - yolov11
  - banknotes
  - banknotes classification
widget:
  - text: Banknotes Classification
    output:
      url: model_predictions/prediction_50 EUR_20240923_190943.jpg
model-index:
  - name: banknotes-recognizer
    results:
      - task:
          type: object-classification
        dataset:
          type: banknotes
          name: Banknotes
        metrics:
          - type: precision
            name: Precision
            value: 0.976
          - type: recall
            name: Recall
            value: 0.974
          - type: mAP50
            name: mAP50
            value: 0.991
          - type: mAP50-95
            name: mAP50-95
            value: 0.789

Model Metrics

YOLO11m summary (fused): 303 layers, 20,037,742 parameters, 0 gradients, 67.7 GFLOPs

Class	Images	Instances	Box(P)	R	mAP50	mAP50-95)
all	110	256	0.969	0.977	0.989	0.801
5 BGN	10	35	0.969	0.9	0.975	0.712
10 BGN	9	29	0.96	1	0.976	0.773
20 BGN	7	25	0.996	0.96	0.993	0.795
50 BGN	7	24	0.996	0.966	0.989	0.801
100 BGN	13	41	0.975	0.955	0.982	0.823
5 EUR	18	19	0.863	0.991	0.986	0.837
10 EUR	14	38	0.998	1	0.995	0.787
20 EUR	15	15	0.986	1	0.995	0.861
50 EUR	7	7	0.97	1	0.995	0.920
100 EUR	10	23	0.97	1	0.995	0.675