Instructions to use ottoykh/Smart-Traffic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ottoykh/Smart-Traffic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="ottoykh/Smart-Traffic")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ottoykh/Smart-Traffic", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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# Model Card for Smart-Traffic
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This is a machine learning model designed for the Real-Time CCTV road traffic monitoring, use for the road traffic estimation and indexing.
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# Table of Contents
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- [Model Card for Smart-Traffic](#model-card-for--model_id-)
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# Model Card for Smart-Traffic
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This is a machine learning model designed for the Real-Time CCTV road traffic monitoring, use for the road traffic estimation and indexing.
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# Table of Contents
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- [Model Card for Smart-Traffic](#model-card-for--model_id-)
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