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Here you can see how conditional image2image model moves pictures by the given condition.

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Pashtetickus/ConditionalCNN_demo

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Conditional image2image model demo

Here you can see how conditional image2image model moves pictures by the given condition.

This type of neural network models can be adapted and used to simulate various physical processes.

Usage example:

Demo CountPages alpha

Для запуска опыта нарисуйте что-нибудь в специальном поле, докрутите кнопки Выполнить и нажмите ее. Затем внизу вы увидите как появится картинка с результатом работы нейросети. Если вы хотите посмотреть историю ваших опытов, кликните на соответствующую галочку в настройках и нажмите Выполнить - история будет обновляться внизу по мере ваших опытов.

Structure of this Repo

  • src : main code
  • scripts : scripts for data downloading
  • data : downloaded data saved here
  • weights : learnt weights

Requirements

  • python3
  • pip

Installation & Run

From source

Clone the repo and change to the project root directory:

git clone https://github.com/Pashtetickus/ConditionalCNN_demo.git
cd ConditionalCNN_demo

Create venv:

with conda

conda create -n CCNN_venv python=3.8
conda activate CCNN_venv

or with python:

python -m venv CCNN_venv
source CCNN_venv/bin/activate # Linux
source CCNN_venv/Scripts/activate # Windows

Install requirements:

python -m pip install -r requirements.txt

And run:

streamlit run run_demo.py

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Here you can see how conditional image2image model moves pictures by the given condition.

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