chore: migrate rust/face-recognition to icp-cli

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Author: marc0olo

.github/workflows/face-recognition.yml

@@ -0,0 +1,28 @@
+name: face-recognition
+
+on:
+  push:
+    branches: [master]
+  pull_request:
+    paths:
+      - rust/face-recognition/**
+      - .github/workflows/face-recognition.yml
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  rust-face-recognition:
+    runs-on: ubuntu-24.04
+    container: ghcr.io/dfinity/icp-dev-env-rust:1.0.0
+    env:
+      ICP_CLI_GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+    steps:
+      - uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1
+      - name: Deploy and test
+        working-directory: rust/face-recognition
+        run: |
+          icp network start -d
+          icp deploy
+          make test

.github/workflows/rust-face-recognition-example.yaml

@@ -1,4 +1,3 @@
-.dfx/
 build/
 node_modules/
 dist/
@@ -8,6 +7,7 @@ _MACOSX
 target/
 *.old.did
 .idea
-src/backend/assets/version-RFB-320.onnx
-src/backend/assets/facerec.onnx
-.env
+backend/assets/version-RFB-320.onnx
+backend/assets/facerec.onnx
+frontend/src/bindings/
+.icp/cache/

rust/face-recognition/.cargo/config.toml

@@ -1,3 +1,3 @@
 [workspace]
-members = ["src/backend"]
+members = ["backend"]
 resolver = "2"

rust/face-recognition/.gitignore

@@ -0,0 +1,34 @@
+.PHONY: test upload-models
+
+test:
+	@echo "=== Test 1: clear_face_detection_model_bytes returns unit ==="
+	@result=$$(icp canister call backend clear_face_detection_model_bytes '()') && \
+	  echo "$$result" && \
+	  echo "PASS" || (echo "FAIL" && exit 1)
+
+	@echo "=== Test 2: clear_face_recognition_model_bytes returns unit ==="
+	@result=$$(icp canister call backend clear_face_recognition_model_bytes '()') && \
+	  echo "$$result" && \
+	  echo "PASS" || (echo "FAIL" && exit 1)
+
+	@echo "=== Test 3: append_face_detection_model_bytes accepts bytes ==="
+	@result=$$(icp canister call backend append_face_detection_model_bytes '(blob "\00\01\02")') && \
+	  echo "$$result" && \
+	  echo "PASS" || (echo "FAIL" && exit 1)
+
+	@echo "=== Test 4: run_detection returns Err when model is not set up ==="
+	@result=$$(icp canister call --query backend run_detection '()') && \
+	  echo "$$result" && \
+	  echo "$$result" | grep -q 'Err' && \
+	  echo "PASS" || (echo "FAIL" && exit 1)
+
+# Upload ONNX model files to the canister incrementally.
+# Requires: ic-file-uploader (cargo install ic-file-uploader)
+# First download the models: ./download-face-detection-model.sh
+# and obtain face-recognition.onnx (see README), then run: make upload-models
+upload-models:
+	icp canister call backend clear_face_detection_model_bytes '()'
+	icp canister call backend clear_face_recognition_model_bytes '()'
+	ic-file-uploader backend append_face_detection_model_bytes version-RFB-320.onnx
+	ic-file-uploader backend append_face_recognition_model_bytes face-recognition.onnx
+	icp canister call backend setup_models '()'

rust/face-recognition/Cargo.toml

@@ -1,96 +1,94 @@
 # ICP face recognition
 
-This is an ICP smart contract runs face detection and face recognition of user's photo that can be uploaded either from a camera or a local file.
+This is an ICP smart contract that runs face detection and face recognition on user photos that can be uploaded either from a camera or a local file.
 
 The smart contract consists of two canisters:
 
-- The backend canister embeds the [the Tract ONNX inference engine](https://github.com/sonos/tract) with two ONNX models. One model is used to detect a face in the photo and return its bounding box. Another model is used for computing face embeddings.
-- The frontend canister contains the Web assets such as HTML, JS, CSS that are served to the browser.
+- The **backend canister** embeds the [Tract ONNX inference engine](https://github.com/sonos/tract) with two ONNX models. One model is used to detect a face in the photo and return its bounding box. Another model is used for computing face embeddings.
+- The **frontend canister** contains the Web assets such as HTML, JS, and CSS that are served to the browser.
 
-# Models
+## Models
 
 The smart contract uses two models: one for detecting the face and another for recognizing the face.
 
-## Face detection
+Since the models are large, they cannot be embedded into the Wasm binary of the smart contract. Instead they must be uploaded separately after deployment.
 
-A face detection model finds the bounding box of a face in the image.
-You can download [Ultraface](https://github.com/onnx/models/tree/main/validated/vision/body_analysis/ultraface) - ultra-lightweight face detection model - [[here](https://github.com/onnx/models/blob/bec48b6a70e5e9042c0badbaafefe4454e072d08/validated/vision/body_analysis/ultraface/models/version-RFB-320.onnx)].
+### Face detection
 
-Alternatively, you can run
+A face detection model finds the bounding box of a face in the image.
+You can download [Ultraface](https://github.com/onnx/models/tree/main/validated/vision/body_analysis/ultraface) — ultra-lightweight face detection model — by running:
 
-```
+```bash
 ./download-face-detection-model.sh
 ```
 
-## Face recognition
+### Face recognition
 
 A face recognition model computes a vector embedding of an image with a face.
 You can obtain a pretrained model from [facenet-pytorch](https://github.com/timesler/facenet-pytorch) as follows.
 
-- #### Step 1: Install `python` and `pip`: https://packaging.python.org/en/latest/tutorials/installing-packages/.
+1. Install `python` and `pip`: https://packaging.python.org/en/latest/tutorials/installing-packages/
 
-- #### Step 2: Install `facenet-pytorch` and  `torch`:
+2. Install `facenet-pytorch`, `torch`, and `onnx`:
 
-```
-pip install facenet-pytorch
-pip install torch
-pip install onnx
-```
+   ```bash
+   pip install facenet-pytorch
+   pip install torch
+   pip install onnx
+   ```
 
-- #### Step 3: Export ONNX model. Start a python shell and run the following commands or create a python file and run it:
+3. Export the ONNX model. Start a Python shell and run:
 
-```
-import torch
-import facenet_pytorch
-resnet = facenet_pytorch.InceptionResnetV1(pretrained='vggface2').eval()
-input = torch.randn(1, 3, 160, 160)
-torch.onnx.export(resnet, input, "face-recognition.onnx", verbose=False, opset_version=11)
-```
+   ```python
+   import torch
+   import facenet_pytorch
+   resnet = facenet_pytorch.InceptionResnetV1(pretrained='vggface2').eval()
+   input = torch.randn(1, 3, 160, 160)
+   torch.onnx.export(resnet, input, "face-recognition.onnx", verbose=False, opset_version=11)
+   ```
 
-- #### Step 4: This should produce `face-recognition.onnx`. Copy the file to the root of this repository.
+   This produces `face-recognition.onnx`. Copy the file to the root of this repository.
 
-## Prerequisites
+## Build and deploy from the command line
 
-- [x] Install the [IC
-  SDK](https://internetcomputer.org/docs/current/developer-docs/getting-started/install). For local testing, `dfx >= 0.22.0` is required.
-- [x] Clone the example dapp project: `git clone https://github.com/dfinity/examples`
-- [x] Install `wasi2ic`: Follow the steps in https://github.com/wasm-forge/wasi2ic and make sure that `wasi2ic` binary is in your `$PATH`.
-- [x] Install `wasm-opt`: `cargo install wasm-opt`
+### Prerequisites
 
-## Build the application
+- Node.js
+- icp-cli: `npm install -g @icp-sdk/icp-cli @icp-sdk/ic-wasm`
 
-```
-dfx start --background
-dfx deploy
+### Install
+
+```bash
+git clone https://github.com/dfinity/examples
+cd examples/rust/face-recognition
 ```
 
-If the deployment is successful, the it will show the `frontend` URL.
-Open that URL in browser to interact with the smart contract.
+### Deploy and test
 
-## Chunk uploading of models
+```bash
+icp network start -d
+icp deploy
+make test
+icp network stop
+```
 
-Since the models are large, they cannot be embedded into the Wasm binary of the smart contract.
-Instead they should be uploaded separately.
+Run `npm run dev` from the `frontend/` directory for hot reload during frontend development.
 
-[DecideAI](https://decideai.xyz/) implemented a tool for incremental uploading of models: https://github.com/modclub-app/ic-file-uploader/tree/main.
+### Upload the ONNX models
 
-You can install the tool with
+After deploying, upload the ONNX models to the canister using [ic-file-uploader](https://github.com/modclub-app/ic-file-uploader/tree/main):
 
-```
+```bash
 cargo install ic-file-uploader
+make upload-models
 ```
 
-Afterwards, execute the `upload-models-to-canister.sh` script, which runs the following commands:
-
-```
-dfx canister call backend clear_face_detection_model_bytes
-dfx canister call backend clear_face_recognition_model_bytes
-ic-file-uploader backend append_face_detection_model_bytes version-RFB-320.onnx
-ic-file-uploader backend append_face_recognition_model_bytes face-recognition.onnx
-dfx canister call backend setup_models
-```
+Once the models are uploaded, open the frontend URL in your browser to interact with the smart contract.
 
 ## Credits
 
 Thanks to [DecideAI](https://decideai.xyz/) for discussions and providing [ic-file-uploader](https://github.com/modclub-app/ic-file-uploader/tree/main).
 
+## Security considerations and best practices
+
+See the [ICP security best practices](https://docs.internetcomputer.org/guides/security/overview).

rust/face-recognition/Makefile

@@ -1,7 +1,7 @@
 [package]
-edition = "2021"
 name = "backend"
 version = "1.1.0"
+edition = "2021"
 
 [lib]
 crate-type = ["cdylib"]
@@ -19,4 +19,3 @@ prost = "0.11.0"
 prost-types = "0.11.0"
 serde = { version = "1.0", features = ["derive"] }
 tract-onnx = { git = "https://github.com/sonos/tract", rev = "2a2914ac29390cc08963301c9f3d437b52dd321a" }
-