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license: cc-by-4.0 |
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language: |
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- en |
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library_name: keras |
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pipeline_tag: image-classification |
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--- |
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## Traffic Congestion Model |
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This model is designed for processing grayscale images with duplicated channels (single-channel replication). It requires input images of size 200 by 200 pixels. |
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### Classes |
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The model makes predictions on the following classes: |
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- `congested_traffic`: Indicates traffic congestion. |
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- `traffic_unrelated`: Indicates an absence of congestion-related traffic. |
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- `uncongested_traffic`: Indicates clear or uncongested traffic conditions. |
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You can use this model for tasks related to traffic congestion detection and classification. |
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### Training Notebook |
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If you're interested in the details of how this model was trained, you can find the training notebook [here](https://www.kaggle.com/code/abhashrai/traffic-congestion-prediction-cnn-xception/notebook). |
