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import numpy as np
import os
import cv2
from PIL import Image
from torchvision import transforms
import pandas as pd
class dataLoader:
def __init__(self, path):
self.path = path
self.img_path = path + 'images/'
self.caption_path = path + 'captions.csv'
self.img_list = os.listdir(self.img_path)
self.caption_dict = self.get_caption_dict()
self.transform = transforms.Compose([
transforms.Resize((224, 224)),
transforms.ToTensor()
])
def get_caption_dict(self):
caption_dict = {}
df = pd.read_csv(self.caption_path, delimiter=',')
for i in range(len(df)):
img_name = df.iloc[i, 0]
caption = df.iloc[i, 1]
caption_dict[img_name] = caption
return caption_dict
def get_image(self, img_name):
img = Image.open(self.img_path + img_name)
img = self.transform(img)
return img
def get_caption(self, img_name):
return self.caption_dict[img_name]
def get_batch(self, batch_size):
batch = np.random.choice(self.img_list, batch_size)
images = []
captions = []
for img_name in batch:
images.append(self.get_image(img_name))
captions.append(self.get_caption(img_name))
return images, captions
def get_all(self):
images = []
captions = []
for img_name in self.img_list:
images.append(self.get_image(img_name))
captions.append(self.get_caption(img_name))
return images, captions |