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import os, sys, random | |
import xml.etree.ElementTree as ET | |
from glob import glob | |
import pandas as pd | |
from shutil import copyfile | |
annotations = glob('BCCD_Dataset/BCCD/Annotations/*.xml') | |
df = [] | |
for file in annotations: | |
#filename = file.split('/')[-1].split('.')[0] + '.jpg' |
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import os | |
import pandas as pd | |
from PIL import Image | |
def crop_cell(row): | |
""" | |
crop_cell(row) | |
given a pd.Series row of the dataframe, load row['filename'] with PIL, |
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#%% IMPORTS | |
import torch | |
import pytorch_lightning as pl | |
import matplotlib.pyplot as plt | |
from pytorch_lightning import Trainer | |
from torch.nn import functional as F | |
import pyro | |
import pyro.distributions as dist | |
# %% |
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#!/bin/bash | |
### steps #### | |
# verify the system has a cuda-capable gpu | |
# download and install the nvidia cuda toolkit and cudnn | |
# setup environmental variables | |
# verify the installation | |
### | |
### to verify your gpu is cuda enable check |