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pytorch-image-models/timm/data/parsers/parser_image_tar.py

67 lines
2.2 KiB

import os
import io
import torch
import tarfile
from .parser import Parser
from .class_map import load_class_map
from .constants import IMG_EXTENSIONS
from PIL import Image
from timm.utils.misc import natural_key
def extract_tar_info(tarfile, class_to_idx=None, sort=True):
files = []
labels = []
for ti in tarfile.getmembers():
if not ti.isfile():
continue
dirname, basename = os.path.split(ti.path)
label = os.path.basename(dirname)
ext = os.path.splitext(basename)[1]
if ext.lower() in IMG_EXTENSIONS:
files.append(ti)
labels.append(label)
if class_to_idx is None:
unique_labels = set(labels)
sorted_labels = list(sorted(unique_labels, key=natural_key))
class_to_idx = {c: idx for idx, c in enumerate(sorted_labels)}
tarinfo_and_targets = [(f, class_to_idx[l]) for f, l in zip(files, labels) if l in class_to_idx]
if sort:
tarinfo_and_targets = sorted(tarinfo_and_targets, key=lambda k: natural_key(k[0].path))
return tarinfo_and_targets, class_to_idx
class ParserImageTar(Parser):
def __init__(self, root, load_bytes=False, class_map=''):
super().__init__()
class_to_idx = None
if class_map:
class_to_idx = load_class_map(class_map, root)
assert os.path.isfile(root)
self.root = root
with tarfile.open(root) as tf: # cannot keep this open across processes, reopen later
self.samples, self.class_to_idx = extract_tar_info(tf, class_to_idx)
self.imgs = self.samples
self.tarfile = None # lazy init in __getitem__
self.load_bytes = load_bytes
def __getitem__(self, index):
if self.tarfile is None:
self.tarfile = tarfile.open(self.root)
tarinfo, target = self.samples[index]
iob = self.tarfile.extractfile(tarinfo)
img = iob.read() if self.load_bytes else Image.open(iob).convert('RGB')
return img, target
def __len__(self):
return len(self.samples)
def _filename(self, index, basename=False, absolute=False):
filename = self.samples[index][0].name
if basename:
filename = os.path.basename(filename)
return filename