Skip to content

The objective is to use Mask RCNN technique for instance segmentation on the COCO dataset.

Notifications You must be signed in to change notification settings

Resh-97/Object-Detection-using-MaskRCNN-Detectron-model

Repository files navigation

Object Detection using MaskRCNN Detectron model

The objective is to use Mask RCNN technique for instance segmentation on the COCO dataset.

Dataset:

COCO dataset!

The COCO dataset is a large image dataset designed for Object Detection, Segmentation, person keypoints detection, and Caption Generation. COCO has several features:

  • Object segmentation
  • Recognition in context
  • Superpixel stuff segmentationo330K images (>200K labeled)
  • 1.5 million object instances
  • 80 object categories
  • 91 stuff categories
  • 5 captions per image
  • 250,000 people with keypoints

Tasks performed:

•Clone the Facebook Detectron Modelusing the following link:

•Load the pre-trained weights using the following link:

•Use the Mask RCNN Architecture and the pre-trained weights to generate predictions for our own images or images from the COCO dataset

•Visualize the Results

Input and Output:

  • The input I provided:

Input

  • The output image with masks

Output

About

The objective is to use Mask RCNN technique for instance segmentation on the COCO dataset.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published