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GitHub / jpgold830 / Land-Cover-Semantic-Segmentation-PyTorch
🛣 Building an end-to-end Promptable Semantic Segmentation (Computer Vision) project from training to inferencing a model on LandCover.ai data (Satellite Imagery).
Stars: 0
Forks: 0
Open Issues: 0
License: mit
Language: Jupyter Notebook
Repo Size: 74.4 MB
Dependencies:
53
Created: 3 months ago
Updated: 3 months ago
Last pushed: 3 months ago
Last synced: 3 months ago
Topics: ai, ai-project, computer-vision, deep-learning, end-to-end, image-segmentation, landcover, machine-learning, ml-project, neural-network, promptapi, pytorch, satellite-imagery, semantic-segmentation, unet
Files
Dependencies
- python 3.9 build
- Jinja2 ==3.1.2
- MarkupSafe ==2.1.3
- Pillow ==9.5.0
- PyWavelets ==1.4.1
- PyYAML ==6.0
- albumentations ==1.3.1
- certifi ==2023.5.7
- charset-normalizer ==3.1.0
- colorama ==0.4.6
- contourpy ==1.0.7
- cycler ==0.11.0
- efficientnet-pytorch ==0.7.1
- filelock ==3.12.2
- fonttools ==4.40.0
- fsspec ==2023.6.0
- huggingface-hub ==0.15.1
- idna ==3.4
- imageio ==2.31.1
- importlib-resources ==5.12.0
- joblib ==1.2.0
- kiwisolver ==1.4.4
- lazy_loader ==0.2
- matplotlib ==3.7.1
- mpmath ==1.3.0
- munch ==3.0.0
- networkx ==3.1
- numpy ==1.24.3
- opencv-python-headless ==4.7.0.72
- packaging ==23.1
- patchify ==0.2.3
- pretrainedmodels ==0.7.4
- pyparsing ==3.0.9
- python-dateutil ==2.8.2
- qudida ==0.0.4
- requests ==2.31.0
- safetensors ==0.3.1
- scikit-image ==0.21.0
- scikit-learn ==1.2.2
- scipy ==1.10.1
- segmentation-models-pytorch ==0.3.3
- six ==1.16.0
- split-folders ==0.5.1
- sympy ==1.12
- threadpoolctl ==3.1.0
- tifffile ==2023.4.12
- timm ==0.9.2
- torch ==2.0.1
- torchvision ==0.15.2
- tqdm ==4.65.0
- typing_extensions ==4.6.3
- urllib3 ==2.0.3
- zipp ==3.15.0