lorenzobloise/transmission_tower_electrical_cable_instance_segmentation
This repository contains the code used to train and test a Mask R-CNN model for instance segmentation of transmission towers and electrical cables. We also implemented classic data augmentation techniques and a new method introduced in the paper "Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation".
No commits in the last 6 months.
Stars
3
Forks
1
Language
Jupyter Notebook
License
—
Category
Last pushed
Nov 04, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/lorenzobloise/transmission_tower_electrical_cable_instance_segmentation"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
CAREamics/careamics
A deep-learning library for denoising images using Noise2Void and friends (CARE, PN2V, HDN...
yu4u/noise2noise
An unofficial and partial Keras implementation of "Noise2Noise: Learning Image Restoration...
rgeirhos/texture-vs-shape
Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased...
NICALab/SUPPORT
Accurate denoising of voltage imaging data through statistically unbiased prediction, Nature Methods.
jaewon-lee-b/lte
Local Texture Estimator for Implicit Representation Function, in CVPR 2022