Build Fashion Recommendation System Using Python

The instructions for running a Fashion Recommendation Service created using this kit are added in this section. The entire solution is available as a package to download from the source code repository.

For Windows OS,

1. Download, extract and double-click the kit installer file to install the kit. Note: Do ensure to extract the zip file before running it. The installation may take from 10 to 20 minutes based on network bandwidth.
2. When you're prompted during the installation of the kit, press Y to launch the app automatically and execute cells in the notebook by selecting Cell --> Run All from Menu bar
3. To run the app manually, press N when you're prompted and locate the folder 'fashion-recommendation' in the "C://kandikits/fashion-recommendation" location
4. Navigate into the directory 'fashion-recommendation'
5. Open command prompt from this directory and run the 'run.bat' file. This would activate the virtual environment and open the jupyter notebook homepage automatically.
6. Select the notebook 'Fashion Recommendation Service.ipynb' to open the Flask service implementation of Fashion recommendation.

For other Operating System,

1. Download python
2. download the repository
3. Extract the zip file and navigate to the directory 'fashion-recommendation'
4. Run the following commands to install Python

tar -xf python*.tar.gz
cd python3.*
./configure
sudo make install

• Open the terminal in the extracted directory 'fashion-recommendation'
• Create and activate a virtual environment by these commands:

python3.9 -m venv example
source example/bin/activate

• Install dependencies by executing the command

pip install -r requirements.txt

• Run the command ‘jupyter notebook’ and select the notebook 'Fashion Recommendation Service.ipynb' to open the Flask service implementation of Fashion recommendation.

Click on the button below to download the solution and follow the deployment instructions to begin set-up. This 1-click kit has all the required dependencies and resources you may need to build your Fashion Recommendation App.