Johnny Fernandes
126 lines
3.8 KiB
Markdown
126 lines
3.8 KiB
Markdown
# DRL_PROJ — DeepFake Detection
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Deep learning project for binary deepfake detection on the DeepFakeFace dataset.
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## Project structure
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```
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DRL_PROJ/
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classifier/ ← discriminative model (real vs. fake classifier)
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src/ ← model definitions, training, evaluation, preprocessing
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configs/ ← experiment configs organised by phase
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phase1/ ← baseline models (SimpleCNN, ResNet18)
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phase2/ ← architecture sweep (ResNet variants, face-crop)
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phase3/ ← EfficientNet, ViT, frequency-aware training
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phase4/ ← ensemble strategies
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tools/ ← analyse.py, ensemble.py, inference.py, facecrop.py
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notebooks/ ← EDA, preprocessing, evaluation, GradCAM
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outputs/ ← models, logs, figures (gitignored except .pt/.json)
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run.py ← main training entry point
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generator/ ← generative model (GAN / VAE / diffusion) — in progress
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pipeline/ ← Vast.ai ephemeral GPU orchestration
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data/ ← dataset root (gitignored)
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cropped/ ← MTCNN pre-cropped faces (gitignored)
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classifier/ ← bbox crops for the classifier
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generator/ ← landmark-aligned crops for the generator
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```
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## Setup
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Create a local environment when you want to run the code directly on a machine you control:
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```bash
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python3 -m venv .venv
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source .venv/bin/activate
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python -m pip install --upgrade pip setuptools wheel
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python -m pip install -r requirements.txt
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```
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## Local Training
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```bash
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python3 classifier/run.py classifier/configs/phase2/p2_resnet18_facecrop.json
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python3 classifier/run.py classifier/configs/phase3/p3_efficientnet_b0.json
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```
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## Ephemeral Vast.ai Pipeline
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The deployment/orchestration path now lives under [`pipeline/`](/run/host/mnt/shared/UP/DRL/DRL_PROJ/pipeline/README.md).
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One-time setup:
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```bash
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cat > pipeline/.env <<'EOF'
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VAST_API_KEY=<your-api-key>
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VAST_SSH_PRIVATE_KEY=/home/your-user/.ssh/id_ed25519
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EOF
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```
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End-to-end ephemeral run:
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```bash
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python3 -m pipeline run classifier/configs/phase2/p2_resnet18_facecrop.json --upload-data
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```
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Interactive offer selection:
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```bash
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python3 -m pipeline offers --select-offer
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```
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You can override the ranking mode per run:
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```bash
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python3 -m pipeline offers --sort price
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python3 -m pipeline offers --sort performance
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python3 -m pipeline offers --sort performance --price 0.14
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```
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You can also filter by region:
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```bash
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python3 -m pipeline offers --select-offer --region europe
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python3 -m pipeline offers --select-offer --region Portugal
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python3 -m pipeline offers --select-offer --region US
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python3 -m pipeline offers --select-offer --region europe --price 0.14
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```
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To inspect which region strings are currently available from the search results:
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```bash
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python3 -m pipeline offers --list-regions
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```
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That command:
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- ensures your SSH public key is registered with Vast.ai
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- searches offers using the filters in `pipeline/defaults/vast.json`
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- creates an instance
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- waits for SSH readiness
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- syncs the repo
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- uploads `data/` when `--upload-data` is set
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- runs `python3 classifier/run.py ...`
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- downloads `classifier/outputs/`
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- for generator runs, rsyncs `generator/outputs/` back every 50 epochs and again at completion
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- destroys the instance automatically unless `--keep-on-failure` is set
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Useful commands:
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```bash
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python3 -m pipeline up
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python3 -m pipeline status <instance_id>
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python3 -m pipeline down <instance_id>
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```
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To override the default Vast search/runtime settings, copy `pipeline/defaults/vast.json`, edit it, and pass:
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```bash
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python3 -m pipeline run classifier/configs/phase3/p3_efficientnet_b0.json --pipeline-config /path/to/vast.override.json
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```
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The default policy in `pipeline/defaults/vast.json` now targets:
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- `1x` GPU
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- `RTX 3090` or `RTX 3090 Ti`
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- `<= $0.20/hour`
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- sorted by `dlperf` descending
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- uses `vastai/pytorch:latest` as the default image
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