Argus solution Quick, Draw! Doodle Recognition Challenge

Source code of 50th place solution for Quick, Draw! Doodle Recognition Challenge by Argus team (Ruslan Baikulov, Nikolay Falaleev).

Solution

We used PyTorch 1.0.0 with framework Argus and CNN architectures from pytorch-cnn-finetune.

Key points:

• Train SE-ResNet-50
• Use simplified data
• Encode time to RGB with color map from pyplot
• Country embeddings
• Gradient accumulation

Quick setup and start

Requirements

• Nvidia drivers, CUDA >= 9, cuDNN >= 7
• Docker, nvidia-docker

The provided dockerfile is supplied to build image with cuda support and cudnn.

Preparations

• Clone the repo, build docker image.

  git clone https://github.com/lRomul/argus-quick-draw.git
  cd argus-quick-draw
  make build

• Download and extract dataset

Run

• Run docker container

make run

• Train model

python train.py

• Predict test and make submission

python predict.py