system-one-arcade / README.md
Aurelien-Lac's picture iamleonie's picture
Add Fit Check outfit-scoring demo (#1)
2feaec3
|
Raw History Blame Contribute Delete
2.55 kB
metadata
title: System One Arcade
emoji: 🟣
colorFrom: purple
colorTo: gray
sdk: docker
app_port: 7860
suggested_hardware: l4x1
models:
  - LiquidAI/d1-3B
short_description: Eleven camera, drawing and text demos of d1-3B
pinned: false

System One Arcade

Eleven demos of d1-3B. Each one asks the model a few typed questions about a camera frame, a drawing or a message, and reads the answers from one forward pass.

demo what it shows
Hand Flappy open your palm to fly up, close it to drop
Pong vs the Model the model plays from a text description of the game
Rep Counter counts squats, jumping jacks or arm raises
Keep It Clean pixelates the middle finger, 0.4 s behind the camera
Find It show the camera each object it asks for
Quick Draw it guesses your drawing among 16 words
Red Light, Green Light move on green, freeze on red
Cowboy Duel two players, first finger gun wins
Live Triage six answers about a support message as you type
Fit Check live outfit score with purikura-style doodles
Ask Anything your own yes/no questions about the camera image

Camera frames go to the model on this Space's GPU and are not stored.

Run it locally

Here every frame makes a round trip to the Space's server, about 0.2 s, which the games that react to each frame (Flappy, Pong, Duel, Red Light) can feel. On your own machine a decision comes back in tens of milliseconds.

You need an Apple silicon Mac, or Linux (WSL2 works) with an NVIDIA GPU of 8 GB or more, and Python 3.12 or newer.

git clone https://huggingface.co/spaces/LiquidAI/system-one-arcade
cd system-one-arcade
python3 -m venv .venv && source .venv/bin/activate

On an Apple silicon Mac (PyTorch on mps):

pip install -r requirements-mac.txt
python game/server.py

On an NVIDIA GPU (PyTorch, CUDA graphs):

pip install -r requirements-nvidia.txt
python game/server.py --compile

Open the address it prints; it carries a token, so other machines on your network cannot use the server. The first start downloads the model (6.2 GB) and warms up for a minute or two; if the download asks for a login, run hf auth login first. python game/server.py --help lists the options (port, model, frame size).

Settings:

  • Visibility: private until launch, then public. The server has no token, so anyone who can open the Space can use its GPU;
  • Hardware: an NVIDIA GPU with bfloat16, an L4 or larger;
  • Secret: HF_TOKEN, a token that can read the model.