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pinball-score-detection-yolov11M
rwitz/pinball-score-detection-yolov11M
pinball-score-detection-yolov11M is a machine learning model from rwitz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
This repository contains a YOLOv11m model trained to detect pinball scores in images. The model aims to facilitate the segmentation of pinball scores for Optical Character Recognition (OCR) tasks.
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Updated Nov 19, 2024
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Nov 19, 2024
- Updated
- Nov 19, 2024
- SHA
- c1b2ee31
Model card
From the Hugging Face model README
YOLOv11m Model for Pinball Score Detection
Overview
This repository contains a YOLOv11m model trained to detect pinball scores in images. The model aims to facilitate the segmentation of pinball scores for Optical Character Recognition (OCR) tasks.
Dataset
- Images: 1,100 hand-annotated images.
- Annotations: Bounding boxes around pinball scores.
Training Details
The model was trained over 100 epochs using an A100 GPU with 40GB VRAM.
Performance Metrics at Final Epoch
Validation Metrics
Class Images Instances P R mAP50 mAP50-95
100%|██████████| 7/7 [00:01<00:00, 4.28it/s]
all 152 187 0.948 0.966 0.986 0.683
- Precision (P): 0.948
- Recall (R): 0.966
- Mean Average Precision at IoU=0.50 (mAP50): 0.986
- Mean Average Precision at IoU=0.50:0.95 (mAP50-95): 0.683
Purpose
The primary goal of this model is to detect pinball scores in any image to enable segmentation for OCR processing.
- License
- apache-2.0
- Created
- Nov 19, 2024
- Updated
- Nov 19, 2024