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asvcode / seedling-resnet101-Copy1.ipynb
Created December 29, 2017 06:53 — forked from anonymous/seedling-resnet101-Copy1.ipynb
fastai/courses/dl1/seedling-resnet101-Copy1.ipynb
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import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from torch.autograd import Variable
pretrained_settings = {
'nasnetalarge': {
'imagenet': {
'url': 'http://data.lip6.fr/cadene/pretrainedmodels/nasnetalarge-a1897284.pth',
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absl-py==0.6.1
asn1crypto==0.24.0
astor==0.7.1
attrs==18.2.0
backcall==0.1.0
bcolz==1.2.1
beautifulsoup4==4.6.3
bleach==3.0.2
bokeh==1.0.1
boto==2.49.0
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scaled = scaled_px(patient6)
crop = scaled[280:400,300:450]
show_image(crop, cmap='bone');
from fastai.vision.all import *
from fastai.medical.imaging import *
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = (7,7)
source = 'D:/Datasets/rsna_pulmonary'
files = get_dicom_files(source)
patient6 = files[6].dcmread()