https://github.com/europanite/image_ai_offline_distillation
image_ai_offline_distillation
https://github.com/europanite/image_ai_offline_distillation
distillation distillation-loss distillation-model expo image image-ai image-processing jest lightweight pytest python typescript
Last synced: about 5 hours ago
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image_ai_offline_distillation
- Host: GitHub
- URL: https://github.com/europanite/image_ai_offline_distillation
- Owner: europanite
- License: apache-2.0
- Created: 2026-05-11T11:10:00.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2026-05-11T13:24:57.000Z (about 2 months ago)
- Last Synced: 2026-05-11T13:34:37.739Z (about 2 months ago)
- Topics: distillation, distillation-loss, distillation-model, expo, image, image-ai, image-processing, jest, lightweight, pytest, python, typescript
- Language: Python
- Homepage: https://europanite.github.io/image_ai_offline_distillation/
- Size: 249 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md
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README
---
layout: page
title: "🇺🇸 English"
permalink: /
lang: en
---
# [Image Offline Distillation](https://github.com/europanite/image_ai_offline_distillation "Image Offline Distillation")
[](https://opensource.org/licenses/Apache-2.0)
[](https://www.python.org/)
[](https://github.com/europanite/image_ai_offline_distillation/actions/workflows/codeql.yml)
[](https://github.com/europanite/image_ai_offline_distillation/actions/workflows/lint.yml)
[](https://github.com/europanite/image_ai_offline_distillation/actions/workflows/ci.yml)
[](https://github.com/europanite/image_ai_offline_distillation/actions/workflows/pytest.yml)
🇺🇸 English |
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A small container for **offline knowledge distillation**.
The project keeps a simple full-stack shape:
- **Backend**: FastAPI + PyTorch + torchvision
- **Frontend**: Expo / React Native Web
- **Container**: Docker Compose
```text
public ImageNet teacher model
-> run once on images
-> save teacher logits
-> train a small CNN student from cached logits
-> compare teacher/student agreement
```
The default teacher is `torchvision.models.resnet18` with public ImageNet weights. You can also use `resnet50` or `mobilenet_v3_large`.
The student is a tiny CNN that outputs the same 1000 ImageNet logits. It is trained to imitate the teacher's softened probability distribution.
## Why this is offline distillation
The key artifact is:
```text
artifacts/teacher_logits_train.pt
```
After this file is created, the student can be trained without calling the teacher model again.
## Dataset modes
| Dataset | Purpose |
| --- | --- |
| `cifar10` | Downloads CIFAR-10 and resizes it to ImageNet input size. |
| `image_folder` | Uses your own unlabeled images under `data/images`. |
For a real experiment, put images here:
```text
data/images/
```
Nested folders are allowed. Labels are not required.
## Start
```bash
docker compose up --build
```
> The frontend service uses Expo Web with Docker `network_mode: host` so that `expo start --web --localhost --port 8081` is reachable from the host browser. This is intended for Linux Docker environments.
Open:
```text
Frontend: http://localhost:8081
Backend: http://localhost:8000/docs
```
## Run from API
```bash
curl -X POST http://localhost:8000/api/v1/distillation/run-all \
-H 'Content-Type: application/json' \
-d '{
"teacher": "resnet18",
"dataset": "fake",
"samples": 128,
"batch_size": 16,
"epochs": 2,
"learning_rate": 0.001,
"temperature": 3.0,
"device": "cpu"
}'
```
## Run from CLI
```bash
docker compose run --rm backend python /app/cli.py run-all \
--teacher resnet18 \
--dataset fake \
--samples 128 \
--batch-size 16 \
--epochs 2 \
--temperature 3.0 \
--device cpu
```
For your own image folder:
```bash
docker compose run --rm backend python /app/cli.py run-all \
--teacher resnet18 \
--dataset image_folder \
--samples 256 \
--epochs 3 \
--device cpu
```
## Outputs
```text
artifacts/
├── teacher_logits_train.pt
├── teacher_cache_metadata.json
├── student_model.pt
└── report.json
```
`report.json` includes:
- `teacher_student_top1_agreement`
- `distillation_kl`
- `student_parameters`
- training loss history
## Tests
```bash
docker compose -f docker-compose.test.yml run --rm backend_test
docker compose -f docker-compose.yml -f docker-compose.test.yml run --rm frontend_test
```