uipath-face-recognition-framework
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In the UiPath Attended Robot Framework you can find a TensorFlow implementation of the face recognizer described in the paper "FaceNet: A Unified Embedding for Face Recognition and Clustering". The pr...
Instructions
- Install Python (including pip) using the provided installation kit in the Prerequisites folder
- Add the Python paths to your PATH system environment variable (You can find your PATH variable by going to My Computer > Properties > Advanced System Settings > Environment Variables > System Variables > Path). Click on Edit and add the following paths, replacing "YOUR_USERNAME" with your Windows username:
- C:\Users\YOUR_USERNAME\AppData\Local\Programs\Python\Python36
- C:\Users\YOUR_USERNAME\AppData\Local\Programs\Python\Python36\Scripts
- Run install.bat in the Prerequisites folder
- Update the Python path in the Config.xlsx with your Python path (C:\Users\YOUR_USERNAME\AppData\Local\Programs\Python\Python36).
- Create a project in AI Center
- Create a dataset and make it public
- Create assets in Orchestrator for the dataset endpoint/APIKey and update Config.xlsx file
- Run Main-UploadDataset.xaml file to populate dataset in AI Centre
- Upload custom ML Package in the AIC project. You can find the package here https://github.com/danielepassos-ui/uipath-face-recognition-mlpackage
- Follow instructions in the ML Package repository to create the MK Skill
- Create assets in Orchestrator for the MKSkill endpoint/APIKey and update Config.xlsx file, when the MLSkill is made public and available
- Run Main-Identify.xaml to identify someone