avlaskin / quicklabel Goto Github PK
View Code? Open in Web Editor NEWTool for image labelling
License: MIT License
Tool for image labelling
License: MIT License
Was actually sitting down to start in on a very similar idea for a library, but instead came across this repository during a cursory scan through PyPI-- love the work you've done with this.
Was hoping to fork and add a few more features, but was wondering if you'd be open to a PR down the road or available to answer questions along the way.
Cheers!
Alright, Round 2!
Main reason I wanted to build out this library a few weeks ago was to have a streamlined way to:
After using the quickLabel
CLI and spitting out our resulting labels.csv
, we should be able to use that file to create a one-call loader for all of our data.
Maybe something like
>> from quickLabel.data.loader import load_data
>> PATH = '/usr/my_proj/data/labels.csv'
>> X, y = load_data(PATH)
>> X.shape
(NUM_IMAGES, X_DIM, Y_DIM, 3)
>> y.shape
(NUM_IMAGES,)
And then you're off doing whatever keras
/pytorch
/sklearn
/etc implementation you're used to doing.
This would essentially mean creating a file under quickLabel/data
called loader.py
that
X
and y
of type np.array
.csv
and per-row:
PIL
for X
(handling the BGR โ RGB conversion)y
How do we want to handle variable-sized images?
For instance, say our data is of all shapes and sizes-- rectangles, squares, similar shapes but different resolutions, etc.
I see three possible solutions, but they both involve a preliminary scan through the data (before loading anything into X
or y
) to get some max_X
, min_X
, max_Y
, min_Y
values, then we use these to:
Or any other ideas you might have here
I'm happy to knock this out over the next week or so, but want to make sure you think this is a good idea before I dive in.
Had success playing with the UI after cloning the repo locally.
But am I missing some command line functionality that I'd get from pip installing? Got v1.0.2
off PyPI, but couldn't get it to work globally like you would, say, cookiecutter or jupyter notebooks.
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