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---
license: cc-by-4.0
language:
- en
library_name: keras
pipeline_tag: image-classification
---
## Traffic Congestion Model
This model is designed for processing grayscale images with duplicated channels (single-channel replication). It requires input images of size 200 by 200 pixels.
### Classes
The model makes predictions on the following classes:
- `congested_traffic`: Indicates traffic congestion.
- `traffic_unrelated`: Indicates an absence of congestion-related traffic.
- `uncongested_traffic`: Indicates clear or uncongested traffic conditions.
You can use this model for tasks related to traffic congestion detection and classification.
### Training Notebook
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). |