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https://github.com/lromul/kaggle-planet-amazon

Solution for Kaggle competition "Planet: Understanding the Amazon from Space"

https://github.com/lromul/kaggle-planet-amazon

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
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    DOI references
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    Academic publication links
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    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (3.9%) to scientific vocabulary
Last synced: 4 months ago · JSON representation

Repository

Solution for Kaggle competition "Planet: Understanding the Amazon from Space"

Basic Info
  • Host: GitHub
  • Owner: lRomul
  • Language: Python
  • Default Branch: master
  • Size: 126 KB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 8 years ago · Last pushed over 8 years ago
Metadata Files
Readme

README.md

Planet: Understanding the Amazon from Space

Use satellite data to track the human footprint in the Amazon rainforest.

This is my part of our team's solution for the Kaggle challange of Understanding the Amazon from Space.

Our team ods.ai finished 7th.

Requirements

  • Linux
  • Nvidia drivers, CUDA 8
  • Docker, nvidia-docker

How to Use?

Put data to data::

data
├── train-jpg
├── test
├── 10_folds.npy
├── train_v2.csv
└── sample_submission_v2.csv

test contains images from test-jpg and test-jpg-additional.

  1. Go to folder docker and build image cd docker ./build.sh

  2. Run container with nvidia-docker ./run.sh

  3. Go to folder src/kfold_train and start train models

cd src/kfold_train/ python densenet121_001.py python vgg11_001.py ... python vgg19_001.py

Owner

  • Name: Ruslan Baikulov
  • Login: lRomul
  • Kind: user
  • Location: Moscow, Russia

Deep Learning Engineer

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