Any Ideas on how to modify Resnet with Images that have 2 channels?

yinterian · November 5, 2017, 3:58pm

In this file all transformations are defined in

fastai/fastai/blob/master/fastai/transforms.py

from .imports import *
from .layer_optimizer import *
from enum import IntEnum

def scale_min(im, targ):
    """ Scales the image so that the smallest axis is of size targ.

    Arguments:
        im (array): image
        targ (int): target size
    """
    r,c,*_ = im.shape
    ratio = targ/min(r,c)
    sz = (scale_to(c, ratio, targ), scale_to(r, ratio, targ))
    return cv2.resize(im, sz)

def zoom_cv(x,z):
    if z==0: return x
    r,c,*_ = im.shape
    M = cv2.getRotationMatrix2D((c/2,r/2),0,z+1.)

This file has been truncated. show original

here are the definition of basic transforms

transforms_basic    = [RandomRotateXY(10), RandomLightingXY(0.05, 0.05)]
transforms_side_on  = transforms_basic + [RandomFlipXY()]
transforms_top_down = transforms_basic + [RandomDihedralXY()]

You can easily make your own list of transforms with your own parameters.

Here is an example:

tfms = tfms_from_model(f_model, sz, aug_tfms=transforms_basic,
                       max_zoom=1.05)