car-damage-detector and Automated-Car-Damage-Detection

Both are independent implementations of the same Mask R-CNN architecture for the identical task of segmenting car damage regions, making them direct competitors offering functionally equivalent solutions with no technical interdependencies.

Maintenance 0/25
Adoption 9/25
Maturity 16/25
Community 22/25
Maintenance 0/25
Adoption 8/25
Maturity 8/25
Community 18/25
Stars: 87
Forks: 48
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 46
Forks: 13
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About car-damage-detector

louisyuzhe/car-damage-detector

Mask R-CNN Model to detect the area of damage on a car. The rationale for such a model is that it can be used by insurance companies for faster processing of claims if users can upload pics and they can assess damage from them. This model can also be used by lenders if they are underwriting a car loan especially for a used car.

About Automated-Car-Damage-Detection

basel-ay/Automated-Car-Damage-Detection

Implementation of Mask-RCNN for detecting and segmenting damaged areas in car images for the purpose of damage assessment.

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