If you're new to the project and want to help, but don't know where to start, we have a semi-curated list of issues that should not need deep knowledge of the system. Have a look and see if anything sounds interesting
graph LR
A((Media Files)) --> |background process|B(Worker)
B --> |index| C[(Index Store)]
C -->G
E((Search Query)) --> F(App FE)
F --> |index|G{Similarity Search}
G --> H[Rank Ordered Results]
This project consists of two almost parallel tracks: research
and software
. Research priority is to experiment and get the features working in a notebook, while software
productionizes it. All tasks below are in decreasing order of priority.
- To run using docker compose
- Worker to index images in the background
- Decide and use appropriate similarity search engine
- FE app to view images
- Advanced Search
- Tag pictures
- Get more model outputs (can we augment
CLIP
with object detection andGLOVE
embeddings?) - Detect faces
- Personalised search (tag friends; search by names)
- Negative search ("photos with A and without B")
- Video search (smart sampling frames)
# This repo needs pytorch to be installed
# Hopefully you're using pipenv / virtualenv / anaconda
# so that you don't mess up your package versions
pip install -r requirements.txt
# Running
# 1. Running the ML server
cd ml && python server.py --index-loc ../data/
# 2. Running the notebook
cd nbs && jupyter notebook
# 3. Running the Indexer
#TODO
Whether you are a user or contributor, official support channels include:
- Github Issues: https://github.com/thebayesianconspiracy/scanpix/issues
- Discord:
#scanpix
in The Bayesian Conspiracy Discord
Before opening a new issue or submitting a new pull request, it's helpful to search the project - it's likely that another user has already reported the issue you're facing, or it's a known issue that we're already aware of.