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cloud_image_segmentation

LWIR cloud image segmentation transfer learing

https://github.com/dominikgithub/cloud_image_segmentation

Science Score: 44.0%

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    Found CITATION.cff file
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    Scientific vocabulary similarity
    Low similarity (8.7%) to scientific vocabulary

Keywords

image-processing machine-learning pytorch segmentation-models tensorflow
Last synced: 6 months ago · JSON representation ·

Repository

LWIR cloud image segmentation transfer learing

Basic Info
  • Host: GitHub
  • Owner: DominikGithub
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 1.49 MB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
image-processing machine-learning pytorch segmentation-models tensorflow
Created 9 months ago · Last pushed 9 months ago
Metadata Files
Readme Citation

README.md

LWIR cloud image segmentation

Segment clouds in satellite infrared single channel images.

Download report (.pdf)

Approach

Supervised training of a model to learn the segmentation mask as a target labels (Y) from the satellite images (X).

Data set

Pairs of IR (single channel) images and binary masks for supervised learning.

  • Image/mask size: 1024x1024x1
  • Approx. 1000 samples

Data preprocessing

  • TIFF image format
  • Adaption to multi channel base model, by replicating gray scale input image to 3 channels
  • Augmentations (rotation, flip, noise, cropping)

IR color mapping IR error sample intensity historgram

Models

Transfer learning for image semantic segmentation tasks

(CNN) VGG19

Location: /tensorflow_vgg/

(static preprocessed TFRecord dataset, no augmentation)

VGG19 setup VGG19 results

  • Flat (one step) upsampling decoder
  • Deeper decoder designs increase training challenge significantly

(ViT) Segformer

Location: /pytorch_segformer/

segformer setup segformer results

  • Two step upsampling decoder

Training

f-scores

Owner

  • Name: Dominik Irimi
  • Login: DominikGithub
  • Kind: user
  • Location: Munich

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Irimi
    given-names: Dominik
    #orcid: https://orcid.org/1234
title: "Cloud image segmentation"
version: 2.0.4
#identifiers:
#  - type: doi
#    value: 10.5281/zenodo.1234
date-released: 2025-06-07

GitHub Events

Total
  • Push event: 1
Last Year
  • Push event: 1

Dependencies

tensorflow_vgg/poetry.lock pypi
  • absl-py 2.3.0
  • astunparse 1.6.3
  • certifi 2025.4.26
  • charset-normalizer 3.4.2
  • colorama 0.4.6
  • flatbuffers 25.2.10
  • gast 0.6.0
  • glob2 0.7
  • google-pasta 0.2.0
  • grpcio 1.71.0
  • h5py 3.13.0
  • idna 3.10
  • joblib 1.5.1
  • keras 3.10.0
  • libclang 18.1.1
  • markdown 3.8
  • markdown-it-py 3.0.0
  • markupsafe 3.0.2
  • mdurl 0.1.2
  • ml-dtypes 0.5.1
  • namex 0.1.0
  • narwhals 1.41.0
  • numpy 2.1.3
  • opt-einsum 3.4.0
  • optree 0.16.0
  • packaging 25.0
  • pandas 2.2.3
  • pillow 11.2.1
  • plotly 6.1.2
  • protobuf 5.29.5
  • pygments 2.19.1
  • python-dateutil 2.9.0.post0
  • pytz 2025.2
  • requests 2.32.3
  • rich 14.0.0
  • scikit-learn 1.6.1
  • scipy 1.15.3
  • setuptools 80.9.0
  • six 1.17.0
  • tensorboard 2.19.0
  • tensorboard-data-server 0.7.2
  • tensorflow 2.19.0
  • termcolor 3.1.0
  • threadpoolctl 3.6.0
  • tqdm 4.67.1
  • typing-extensions 4.13.2
  • tzdata 2025.2
  • urllib3 2.4.0
  • werkzeug 3.1.3
  • wheel 0.45.1
  • wrapt 1.17.2
tensorflow_vgg/pyproject.toml pypi
  • glob2 (>=0.7,<0.8)
  • pandas (>=2.2.3,<3.0.0)
  • pillow (>=11.2.1,<12.0.0)
  • plotly (>=6.1.2,<7.0.0)
  • scikit-learn (>=1.6.1,<2.0.0)
  • tensorflow (>=2.19.0,<3.0.0)
  • tqdm (>=4.67.1,<5.0.0)
torch_segformer/poetry.lock pypi
  • 117 dependencies
torch_segformer/pyproject.toml pypi
  • albumentations (>=2.0.8,<3.0.0)
  • glob2 (>=0.7,<0.8)
  • mlflow (>=2.22.0,<3.0.0)
  • numpy (>=2.2.6,<3.0.0)
  • pandas (>=2.2.3,<3.0.0)
  • plotly (>=6.1.2,<7.0.0)
  • torch (>=2.7.0,<3.0.0)
  • transformers (>=4.52.4,<5.0.0)
torch_segformer/requirements.txt pypi
  • Deprecated ==1.2.18
  • Flask ==3.1.1
  • GitPython ==3.1.44
  • Jinja2 ==3.1.6
  • Mako ==1.3.10
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  • PyGObject ==3.42.1
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  • SQLAlchemy ==2.0.41
  • SecretStorage ==3.3.1
  • Send2Trash ==1.8.3
  • Werkzeug ==3.1.3
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  • albumentations ==2.0.8
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  • annotated-types ==0.7.0
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  • arrow ==1.3.0
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  • certifi ==2025.4.26
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  • filelock ==3.16.1
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  • jupyter_server_terminals ==0.5.3
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  • kaleido ==0.2.1
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  • matplotlib ==3.10.3
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  • mistune ==3.1.3
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  • mlflow-skinny ==2.22.0
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  • mpmath ==1.3.0
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  • nbformat ==5.10.4
  • nest-asyncio ==1.6.0
  • networkx ==3.4.2
  • notebook ==7.3.3
  • notebook_shim ==0.2.4
  • numpy ==2.2.6
  • nvidia-cublas-cu12 ==12.4.5.8
  • nvidia-cuda-cupti-cu12 ==12.4.127
  • nvidia-cuda-nvrtc-cu12 ==12.4.127
  • nvidia-cuda-runtime-cu12 ==12.4.127
  • nvidia-cudnn-cu12 ==9.1.0.70
  • nvidia-cufft-cu12 ==11.2.1.3
  • nvidia-cufile-cu12 ==1.13.0.11
  • nvidia-curand-cu12 ==10.3.5.147
  • nvidia-cusolver-cu12 ==11.6.1.9
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  • nvidia-nccl-cu12 ==2.21.5
  • nvidia-nvjitlink-cu12 ==12.4.127
  • nvidia-nvtx-cu12 ==12.4.127
  • oauthlib ==3.2.0
  • opencv-python-headless ==4.11.0.86
  • opentelemetry-api ==1.33.1
  • opentelemetry-sdk ==1.33.1
  • opentelemetry-semantic-conventions ==0.54b1
  • overrides ==7.7.0
  • packaging ==24.2
  • pandas ==2.2.3
  • pandocfilters ==1.5.1
  • parso ==0.8.4
  • pexpect ==4.9.0
  • pillow ==11.2.1
  • platformdirs ==4.3.7
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  • prometheus_client ==0.21.1
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  • protobuf ==6.31.1
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  • pure_eval ==0.2.3
  • pyarrow ==19.0.1
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  • pydantic_core ==2.33.2
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  • python-apt ==2.4.0
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  • python-json-logger ==3.3.0
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  • pyzmq ==26.3.0
  • referencing ==0.36.2
  • regex ==2024.11.6
  • requests ==2.32.3
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  • smmap ==5.0.2
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torch_segformer/runpod_requirements.txt pypi
  • albumentations *
  • glob2 *
  • opencv-python *
  • pipinstall--upgradekaleido *
  • pipinstall-Umlflow *
  • plotly *
  • scikit-learn *
  • torchvision *
  • transformers *