How to run it? Instruction? about deoldify HOT 1 CLOSED

Down towards the bottom of the readme there's this section:

For those wanting to start transforming their own images right away: To start right away with your own images without training the model yourself (understandable)...well, you'll need me to upload pre-trained weights first. I'm working on that now. Once those are available, you'll be able to refer to them in the visualization notebooks. I'd use ColorizationVisualization.ipynb. Basically you'd replace

colorizer_path = IMAGENET.parent/('bwc_rc_gen_192.h5')

With the weight file I upload for the generator (colorizer).

Then you'd just drop whatever images in the /test_images/ folder you want to run this against and you can visualize the results inside the notebook with lines like this:

vis.plot_transformed_image("test_images/derp.jpg", netG, md.val_ds, tfms=x_tfms, sz=500)

I'd keep the size around 500px, give or take, given you're running this on a gpu with plenty of memory (11 GB GeForce 1080Ti, for example). If you have less than that, you'll have to go smaller or try running it on CPU. I actually tried the latter but for some reason it was -really- absurdly slow and I didn't take the time to investigate why that was other than to find out that the Pytorch people were recommending building from source to get a big performance boost. Yeah...I didn't want to bother at that point.

from deoldify.