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MLCV Project

Setup

Download a subset of the data and place them in data

Download the checkpoints and place them in checkpoints

Testing

Place any images of class 'classname' in 'data/png/classname'. For example, interpolating two images of broccoli should be placed in 'data/png/broccoli'. Images should be 256 x 256 and grayscale.

Make sure to set the batch size equal to the number of images. For example, if interpolating between 5 images, run:

python3 test.py --batch-size 5 --img-class broccoli

When running interpolation, outputs will be saved to 'results/test'.

Changing Interpolation

On lines 92-93 in 'test.py'

y = linear(encoded, ibf=20, ease=sigmoid)
y = catmullRom(encoded, ibf=20, ease=sigmoid)

You can configure the spatial interpolation (linear/catmulRom), the number of inbetween frames (ibf) and the easing amount (linear/sigmoid). For the linear call, you may also pass in a set of interpolation points p. For example,

y = linear(encoded, ibf=20, ease=sigmoid, p=[(0.2,-1), (0.8,2), (1,1)])

Will run linear spatial interpolation with sigmoid easing with anticipation and follow-through.

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