About

zk-MNIST: web frontend app + Jupyter notebook with ML model generation Authors: @horacepan @sunfishstanford @henripal

You can play with the webapp demo at: https://zkmnist.netlify.app/ (Note: mobile browsers not supported; wallet connected to Goerli testnet required to demonstrate ZK verifier.) Tutorial blog post: https://hackmd.io/Y7Y79_MtSoKdHNAEfZRXUg

This project is part of 0xPARC's winter 2021 applied zk learning group, and draws heavily from 0xJOF's zk learning in public repo and Wei Jie Koh's zk nft mint repo

Current Functionality:

1. draw a digit or select an image of a hand-drawn digit
2. pass the digit through 2 conv layers and 2 FC layers in browser, generating a dim 84 embedding
3. generate a zkSNARK proof in browser that the embedding represents a given digit
4. verify proof on-chain using ethers + snarkjs

How to run it locally:

Prerequisites: global install of circom 2.0

1. git clone the repo
2. cd into the directory
3. npm i to install dependencies
4. generate powers of tau yarn zk:ptau
5. compile circuits: (yarn zk:compile doesn't work) 5a) cd zk 5b) zsh compile.sh 5c) cd .. (back to main directory) 5d) copy over some of the wasm files mkdir public/static mkdir public/static/js cp node_modules/onnxruntime-web/dist/*.wasm public/static/js/
6. compile the contracts npx hardhat compile
7. start a local ether node: npx hardhat node
8. switch to another terminal
9. deploy the smart contract npx hardhat run scripts/deploy.js --network localhost
10. make a note of where the contract address has been deployed
11. edit verifierAddress in ./src/config.js
12. start web app npm start

Development loop:

ZK circuits

All zk circuits are in the zk directory.

1. generate basic powers of tau phase 1 with yarn zk:ptau
2. compile the circuits, generate the solidty validator with yarn zk:compile (but see 5a/5b above)