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PyTorch_4_Image_Datasets.py
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68 lines (55 loc) · 1.91 KB
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import torch
from torch.utils.data import Dataset
import torchvision.transforms as transforms
import pandas as pd
import os
from PIL import Image
import matplotlib.pyplot as plt
data_dir = ''
csv_file = 'index.csv'
"""
csv_path = os.path.join(data_dir,csv_file)
data_name = pd.read_csv(csv_path)
print(data_name.head(5))
print('File name : {}'.format(data_name.iloc[0,1]))
print('y : {}'.format(data_name.iloc[0,0]))
print('Total rows : {}'.format(data_name.shape[0]))
image_name = data_name.iloc[0,1]
image_path = os.path.join(data_dir,image_name)
image = Image.open(image_path)
plt.imshow(image,cmap='gray', vmin=0, vmax=255)
plt.title(data_name.iloc[0, 0])
plt.show()
"""
class ImageDataset(Dataset):
def __init__(self,data_dir,csv_file,transform = None):
self.data_dir = data_dir
csv_path = os.path.join(self.data_dir,csv_file)
self.data_name = pd.read_csv(csv_path)
self.len = self.data_name.shape[0]
self.transform = transform
def __getitem__(self,idx):
image_path = os.path.join(self.data_dir, self.data_name.iloc[idx,1])
image = Image.open(image_path)
y = self.data_name.iloc[idx,0]
if self.transform:
image = self.transform(image)
return image,y
def __len__(self):
return self.len
"""
my_image_dataset = ImageDataset(data_dir = data_dir,csv_file = csv_file)
image,y = my_image_dataset[0]
plt.imshow(image,cmap='gray', vmin=0, vmax=255)
plt.title(y)
plt.show()
"""
data_transform = transforms.Compose([transforms.CenterCrop(10), transforms.ToTensor()])
my_image_dataset = ImageDataset(data_dir = data_dir,csv_file = csv_file,transform=data_transform)
#my_image_dataset = ImageDataset(data_dir = data_dir,csv_file = csv_file,transform=None)
#print(my_image_dataset[0][0].shape)
image,y = my_image_dataset[1]
print(y)
plt.imshow(transforms.ToPILImage()(image),cmap='gray', vmin=0, vmax=255)
plt.title(y)
plt.show()