Skip to main content

Mask R-CNN for object detection and instance segmentation

Project description

This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It’s based on Feature Pyramid Network (FPN) and a ResNet101 backbone. I create this package to make easy to use it on google colab all.

Project details


Release history Release notifications | RSS feed

This version

2.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mrcnn_colab-2.1.0-py3-none-any.whl (56.8 kB view details)

Uploaded Python 3

File details

Details for the file mrcnn_colab-2.1.0-py3-none-any.whl.

File metadata

  • Download URL: mrcnn_colab-2.1.0-py3-none-any.whl
  • Upload date:
  • Size: 56.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/41.4.0 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.7.4

File hashes

Hashes for mrcnn_colab-2.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 4c518af09bb835a87f0d02c6fa9f556b06fddac6c5fadbbe6a18ef45b3d2c6f4
MD5 e2366f07eae59e980841e4aab741252d
BLAKE2b-256 76521e37b80567bbbdd121a68fa419f0f5b4a43ad755ee3a8bacc4b180ecd244

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page