mirrors
/
dinov2
mirror of https://github.com/facebookresearch/dinov2.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

fix stuff

pull/422/head
Etienne Guevel 2024-05-26 01:00:55 +02:00
parent 9d6d6d42b5
commit d605692003
2 changed files with 18 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

26
dinov2/data/datasets/custom_image_dataset.py
View File

@ -2,17 +2,19 @@ import os
import pathlib
import random
from typing import List
from omegaconf.listconfig import ListConfig
from torch.utils.data import Dataset
from .decoders import ImageDataDecoder
from PIL import Image
class ImageDataset(Dataset):
def __init__(self, root, transform=None, path_preserved: List[str]=[], frac: float=0.1):
def __init__(self, root, transform=None, path_preserved: List[str]=[], frac: float=0.1, is_valid=True):
self.root = root
self.transform = transform
self.path_preserved = path_preserved if isinstance(path_preserved, list) else [path_preserved]
self.path_preserved = path_preserved if isinstance(path_preserved, (list, ListConfig)) else [path_preserved]
self.frac = frac
self.preserved_images = []
self.is_valid = is_valid
self.images_list = self._get_image_list()
def _get_image_list(self):
@ -22,7 +24,7 @@ class ImageDataset(Dataset):
try:
p = self.root
preserve = p in self.path_preserved
images.extend(self._retrieve_images(p, preserve=preserve, frac=self.frac))
images.extend(self._retrieve_images(p, preserve=preserve, frac=self.frac, is_valid=self.is_valid))
except OSError:
print("The root given is nor a list nor a path")
@ -31,29 +33,32 @@ class ImageDataset(Dataset):
for p in self.root:
try:
preserve = p in self.path_preserved
images.extend(self._retrieve_images(p, preserve=preserve, frac=self.frac))
images.extend(self._retrieve_images(p, preserve=preserve, frac=self.frac, is_valid=self.is_valid))
except OSError:
print(f"the path indicated at {p} cannot be found.")
return images
def _retrieve_images(self, path, is_valid=False, preserve=False, frac=1):
def _retrieve_images(self, path, is_valid=True, preserve=False, frac=1):
images_ini = len(self.preserved_images)
images = []
for root, _, files in os.walk(path):
images_dir = []
for file in files:
if file.lower().endswith(('.png', '.jpg', '.jpeg', '.tiff')):
im = os.path.join(root, file)
if is_valid:
try:
Image.open(os.path.join(root, file))
images_dir.append(os.path.join(root, file))
with open(im, 'rb') as f:
image_data = f.read()
ImageDataDecoder(image_data).decode()
images_dir.append(im)
except OSError:
print(f"Image at path {os.path.join(root, file)} could not be opened.")
print(f"Image at path {im} could not be opened.")
else:
images_dir.append(os.path.join(root, file))
images_dir.append(im)
if preserve:
random.seed(24)
@ -62,6 +67,9 @@ class ImageDataset(Dataset):
self.preserved_images.extend(images_dir[:split_index])
images.extend(images_dir[split_index:])
else:
images.extend(images_dir)
images_end = len(self.preserved_images)
if preserve:
print(f"{images_end - images_ini} images have been saved for the dataset at path {path}")

2
dinov2/train/train.py
View File

@ -200,7 +200,7 @@ def do_train(cfg, model, resume=False):
# save the preserved images
if dataset.preserved_images:
write_list(os.path.join(cfg.train.output_dir, 'preserved_images.pkl'))
write_list(os.path.join(cfg.train.output_dir, 'preserved_images.pkl'), dataset.preserved_images)
# sampler_type = SamplerType.INFINITE
sampler_type = SamplerType.SHARDED_INFINITE # define the sampler to use for fsdp