Nerf or Nothin' Neural Network
The universal binary image classifier.
With conda (4.8.2):
conda env create -f env.yml
conda activate NNNN
A workflow is available to create new labeled data. Save images to data/
. The script util/labeler.py
uses OpenCV
to allow the user to select bounding rectangle around any / all / no targets in the images. Images are then downsampled such that max(height, width) = 500 and updated within data/
. Bounding rectangle information is saved to data/truth/ground_truth_0.csv
, and original images are saved to data/originals/
.
A small sample of true negative images are included in data/
, taken from the PASCAL Visual Object Classes Challenge.
To label new data, simply save the images to data/
and run:
cd util
python labeler.py
This will only offer images not in data/truth/ground_truth_0.csv
for bounding rectangle selection.
To re-label data or label a specific new image (or both), pass the -f
argument with the file names:
cd util
python labeler.py -f 0.jpeg 3.jpeg
- Do the actual work of building / training model.