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PyTorch](https://img.shields.io/pypi/v/torch?label=pytorch\u0026logo=pypi)](https://pypi.org/project/torch/)\n[![PyPI - NumPy](https://img.shields.io/pypi/v/numpy?label=numpy\u0026logo=pypi)](https://pypi.org/project/numpy/)\n[![PyPI - Pandas](https://img.shields.io/pypi/v/pandas?label=pandas\u0026logo=pypi)](https://pypi.org/project/pandas/)\n[![PyPI - Scikit-Learn](https://img.shields.io/pypi/v/scikit-learn?label=scikit-learn\u0026logo=pypi)](https://pypi.org/project/scikit-learn/)\n[![PyPI - Matplotlib](https://img.shields.io/pypi/v/matplotlib?label=matplotlib\u0026logo=pypi)](https://pypi.org/project/matplotlib/)\n[![PyPI - Pillow](https://img.shields.io/pypi/v/Pillow?label=pillow\u0026logo=pypi)](https://pypi.org/project/Pillow/)\n\n## 🚀 Usage\n\n### 📓 Notebooks\n\n\u003e #### Fully Connected \n- **Training the VAE Fully Connected**: [train_vae_fconnected_notebook](./notebooks/1-train_vae_fconnected_notebook.ipynb)\n- **Evaluating the VAE Fully Connected**: [eval_vae_fconnected_notebook](./notebooks/1-eval_vae_fconnected_notebook.ipynb)\n\n\u003e #### Fully Convolutional \n- **Training the VAE Fully Convolutional**: [train_vae_fconv_notebook](./notebooks/2-train_vae_fconv_notebook.ipynb)\n- **Evaluating the VAE Fully Convolutional**: [eval_vae_fconv_notebook](./notebooks/2-eval_vae_fconv_notebook.ipynb)\n\n\u003e #### GIFs \u0026 Videos\n- **Generating GIFs/Videos**: [video_gif_generator.ipynb](./video-gif/video_gif_generator.ipynb)\n\n\n## 📦 Installing Dependencies\n\nYou can install all the necessary dependencies listed in the `requirements.txt` file using one of the following methods:\n\n### 1. **Using pip from the terminal**\n\nIf you are in the root directory of the project, where the `requirements.txt` file is located, run:\n\n```bash\n$ pip install -r requirements.txt\n```\n\n## 🤖 Train \n\nIf you prefer to run the model directly without using the notebooks, you can execute the training script from the terminal:\n\n\u003e Fully Connected\n\n```bash\n!python train.py --path \"./train_images.h5\" --model fconnected  --batch_size 128 --epochs 100\n\n```\n\n\u003e Fully Convolutional\n\n```bash\n!python train.py --path \"./train_images.h5\" --model fconv --batch_size 128 --epochs 100\n```\n\nThis will start the training process using the `train.py` script, which is configured to load the dataset, prepare the model, and begin training.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdantas-ds%2Fvae-meandering-rivers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdantas-ds%2Fvae-meandering-rivers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdantas-ds%2Fvae-meandering-rivers/lists"}