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import os
def get_dataset_info(args, split):
if args.EVAL_DATASET == 'pascal':
# data_dir = 'data/PF-dataset-PASCAL'
data_dir = '../../Datasets/PF-dataset-PASCAL'
categories = sorted(os.listdir(os.path.join(data_dir, 'Annotations')))
# elif args.EVAL_DATASET == 'ap10k':
# data_dir = 'data/ap-10k'
# categories = []
# subfolders = os.listdir(os.path.join(data_dir, 'ImageAnnotation'))
# # Handle AP10K_EVAL test settings
# if args.AP10K_EVAL_SUBSET == 'intra-species':
# categories = [folder for subfolder in subfolders for folder in os.listdir(os.path.join(data_dir, 'ImageAnnotation', subfolder))]
# elif args.AP10K_EVAL_SUBSET == 'cross-species':
# categories = [subfolder for subfolder in subfolders if len(os.listdir(os.path.join(data_dir, 'ImageAnnotation', subfolder))) > 1]
# split += '_cross_species'
# elif args.AP10K_EVAL_SUBSET == 'cross-family':
# categories = ['all']
# split += '_cross_family'
# categories = sorted(categories)
# if split == 'val':
# # remove category "king cheetah" from categories, since it is not present in the validation set
# categories.remove('king cheetah')
elif args.EVAL_DATASET == 'spair': # SPair
# data_dir = 'data/SPair-71k'
data_dir = '../../Datasets/SPair-71k'
categories = sorted(os.listdir(os.path.join(data_dir, 'ImageAnnotation')))
return data_dir, categories, split
# SPair-71k dataset for batch processing
from PIL import Image
from torch.utils.data import Dataset
class VLDataset(Dataset):
"""A simple dataset to wrap a list of images and prompts for the DataLoader."""
def __init__(self, images, prompts):
self.images = images
self.prompts = prompts
def __len__(self):
return len(self.images)
def __getitem__(self, idx):
# The DataLoader will call this for each item
return self.images[idx], self.prompts[idx]
class VLDatasetPaired(Dataset):
"""A simple dataset to wrap a list of images and prompts for the DataLoader."""
def __init__(self, source_imgs, target_imgs, prompts):
self.source_imgs = source_imgs
self.target_imgs = target_imgs
self.prompts = prompts
def __len__(self):
return len(self.source_imgs)
def __getitem__(self, idx):
# The DataLoader will call this for each item
return self.source_imgs[idx], self.target_imgs[idx], self.prompts[idx] |