Apolloscape dataset for localization task.
Exploring localization task on Apolloscape dataset.
Read my blog post about PoseNet implementation details https://capsulesbot.com/blog/2018/08/24/apolloscape-posenet-pytorch.html
ECCV2018 Self-localization on-the-fly challenge task details.
NOTE: This repository is a work in progress.
Prerequisites
Dataset reader based on Pytorch 0.4.1 Dataset. To install all dependencies:
pip install -r requirements.txt
Data
Download Apolloscape data from page and unpack it to a folder. Examples below assume that data folder symbolically linked to apolloscape-loc/data/apolloscape.
mkdir ./data
ln -s <DATA FOLDER>/apolloscape ./data
Sample data file for zpark road provided in localization challenge section supported automatically (it has different folder names, files order and pose data files format)
Python Notebook example
See roads and record graphs in Apolloscape_View_Records Notebook
PoseNet training, error calculation and result visualization in Apolloscape_PoseNet
Show/Save path and sample images by record id
python plot_dataset.py --data ./data/apolloscape --road road03_seg --record Record018
Generate video of the path by record id
python plot_dataset.py --data ./data/apolloscape --road road03_seg --record Record018 --video
Train PoseNet convnet on ZPark road
python train.py --data ./data/apolloscape --road zpark-sample --checkpoint-save 50 --fig-save 1 --epochs 2000 --lr 1e-5 --experiment zpark_posenet_L1 --feature-net resnet34 --feature-net-pretrained --learn-beta
Training process:
Training and validation results:
TODO:
- VidLoc implementation
- [Optional] Prepare data for eval script
- SfM / 3D Reconstruction pipeline
- WGAN for generating new samples
- Qt/OpenGL visualizations