Radek Osmulski radekosmulski

radekosmulski / train_on_CIFAR10_fastai_only_simple.py

Created June 21, 2019 15:24

	from fastai.vision import *
	from fastai.script import *
	from torch import nn
	from fastai.metrics import top_k_accuracy

	path = untar_data(URLs.CIFAR)
	data = ImageDataBunch.from_folder(path, valid='test')

	class block(nn.Module):
	def __init__(self, n_in, n_out, two_d=True):

radekosmulski / train_on_CIFAR10_fastai_only.py

Last active August 17, 2019 09:31

train on CIFAR10 in console using fastai

	from fastai.vision import *
	from fastai.script import *
	from torch import nn
	from fastai.metrics import top_k_accuracy

	path = untar_data(URLs.CIFAR)
	data = ImageDataBunch.from_folder(path, valid='test')

	class block(nn.Module):
	def __init__(self, n_in, n_out, two_d=True):

radekosmulski / train_on_CIFAR10.py

Created June 20, 2019 19:29

training on CIFAR10 using fastai from the command line

	import fire
	import fastai
	from fastai.vision import *
	from torch import nn
	from fastai.metrics import top_k_accuracy

	path = untar_data(URLs.CIFAR)
	data = ImageDataBunch.from_folder(path, valid='test')

	class block(nn.Module):

radekosmulski / object_detection_data.py

Last active April 9, 2018 16:10

	class ConcatDataset(Dataset):
	"""Concatenates a dataset and an iterable of appropriate size."""
	def __init__(self, ds, y2):
	assert(len(ds)==len(y2))
	self.ds,self.y2 = ds,y2
	def __len__(self): return len(self.ds)
	def __getitem__(self, i):
	x,y = self.ds[i]
	return (x, (self.y2[i],y))
	def denorm(self, im): return self.ds.denorm(im)