railway-track-fault-detection-inceptionv3

Railway Track Fault Detection — InceptionV3

Trained InceptionV3-based image classification model for detecting visible railway track faults from images.

This model is part of the Railway Track Fault Detection project, which uses transfer learning with an ImageNet-pretrained InceptionV3 backbone to classify railway track images into two classes:

• Defective
• Non defective

Model Details

The model uses an ImageNet-pretrained InceptionV3 backbone with include_top=False. Features are taken from the mixed7 layer and passed through a custom classification head consisting of Flatten, Dense (128, ReLU), Dropout (0.3), and Dense (1, Sigmoid).

Performance

Evaluation was performed on a held-out set containing 62 images, with 31 images from each class.

Classification Report

These results describe performance on the project's evaluation set and should not be interpreted as guaranteed performance on railway imagery from other environments or data distributions.

Input Preprocessing

Images should be:

1. Converted to RGB.
2. Resized to 300 × 300.
3. Converted to an array.
4. Normalized to [0, 1] by dividing pixel values by 255.0.
5. Expanded with a batch dimension before inference.

Output Interpretation

The model produces a single sigmoid probability.

With the project's threshold of 0.5:

• probability > 0.5 → Non defective
• probability <= 0.5 → Defective

Training

The model was trained using transfer learning with:

• ImageNet-pretrained InceptionV3
• Adam optimizer
• Binary cross-entropy loss
• Data augmentation
• Early stopping
• Model checkpointing

The project supports both the original training dataset and an offline-augmented training dataset. Dataset selection is configurable in the training pipeline.

Model File

inceptionv3_railway_fault_detector.h5

SHA-256:

BC79FC3BE8250276779D5FA168E1A2BA08651FDA2B834DC214A976F6C2689E4A

Source Code

The complete modular training, evaluation, preprocessing, visualization, and inference pipeline is available on GitHub:

https://github.com/MinhalHusain/railway-track-fault-detection

Dataset

The project was developed using the Railway Track Fault Detection dataset associated with the original Kaggle project:

kaggle kernels pull salmaneunus/railway-track-fault-detection-1

The dataset itself is not redistributed through this model repository. Users should review the original dataset source and its applicable terms before reuse.

Limitations

This model is an experimental computer-vision project and is not a certified railway inspection or safety system.

Performance may vary with:

• lighting conditions
• camera angle and distance
• image quality
• track environment
• fault types not represented in the training data
• images from distributions different from the training dataset

Predictions should not be used as the sole basis for real-world railway maintenance or safety decisions.

License

The project code and this model repository are released under the MIT License. Third-party datasets and other external materials remain subject to their respective licenses and terms.