To segment/detect/recognize dents/scratches from images of cars. The dataset contains car images with one or more damaged parts.

Detectron 2 is a next-generation open-source object detection system from Facebook AI Research. It can be used to train various state-of-the-art models like Densepose and panoptic feature pyramid networks for detection tasks such as bounding-box detection, instance and semantic segmentation, and person key point detection.

With a modular design, Detectron2 is flexible and extensible, and able to provide fast training on single or multiple GPU servers.

I hope that releasing Detectron2 will continue to accelerate progress in the area of object detection and segmentation. This Kernel is my attempt of contributing to the progress.

Detectron2 is a ground-up rewrite of Detectron that started with maskrcnn-benchmark. The platform is now implemented in PyTorch. With a new, more modular design, Detectron2 is flexible and extensible, and able to provide fast training on single or multiple GPU servers. Detectron2 includes high-quality implementations of state-ofthe-art object detection algorithmsFirst of this we had tried using the TensorFlow but Due to the unavailability of necessary resources and error occurring in the TensorFlow we choose the detectron

Where it was so helpful and the precision and the accuracy rate were a boost compared to TensorFlow and it was the emerging technology in the developing world.