- 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
-
Notifications
You must be signed in to change notification settings - Fork 21
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 project also uses ideas from the paper "Deep Face Recognition" from the Visual Geometry Group at Oxford. The framework allows you to add an extra lay…
andumorie/uipath-face-recognition-framework
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
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 project also uses ideas from the paper "Deep Face Recognition" from the Visual Geometry Group at Oxford. The framework allows you to add an extra lay…
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published