Playful interface for the COCO dataset.
coco | ||
www | ||
coco.sql | ||
create_shapes.py | ||
generate_lonely_segments.py | ||
plottingdata_coco.service | ||
README.md | ||
requirements.txt | ||
server.py | ||
tools.py |
- server.py
- Server for the web interface
- create_shapes.py
- Create an svg file per image, with classes on the shapes according to their classes
- zoom_animation.py
- Create svg frames for a category. Ordered by the area of the shapes.
- generate_lonely_segments.py
- Find and download the images with only one object in them.
- tools.py
- Turn a COCO json file (eg
instances_val2017.json
) into a database format (egcoco_train.db
)
Build array of images sorted by size:
python zoom_animation.py --annotations ../../datasets/COCO/annotations/instances_train2017.json --output zoom --category_id 18
Turn into png
cd zoom/dog
for file in *.svg; do inkscape -z -f "${file}" -w 640 -e "../dog_png/${file}.png"; done
Turn png into mp4
cd ../dog_png
#ffmpeg -r 1 -i %d_*.png -pix_fmt yuv420p bloch2.mp4
ffmpeg -f image2 -pattern_type glob -i '*.png' ../dog.mp4
To run as server:
cp plottingdata_coco.service /etc/systemd/system/
systemctl daemon-reload
systemctl enable plottingdata_coco.service
systemctl start plottingdata_coco.service
rsync . --exclude zoom --exclude venv --exclude archive -av here.rubenvandeven.com:/home/ruben/coco/ --exclude shapes --exclude lonely --exclude .git --exclude __pycache__ --info progress2