resi
Datasets
All datasets matching “resi”imagenet_1k_resized_256
Dataset Card for "imagenet_1k_resized_256"
Dataset summary
The same ImageNet dataset but all the smaller side resized to 256.
A lot of pretraining workflows contain resizing images to 256 and random cropping to 224x224, this is why 256 is chosen.
The resized dataset can also be downloaded much faster and consume less space than the original one.
See here for detailed readme.
Dataset Structure
Below is the example of one row of data. Note that the labels in… See the full description on the dataset page: https://huggingface.co/datasets/evanarlian/imagenet_1k_resized_256.resisc45
RESISC45
Overview
Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset('tanganke/resisc45')
Dataset Information
The dataset is divided into the following splits:
Training set: Contains 18,900 examples, used for model training.
Test set: Contains 6,300 examples, used for model evaluation and benchmarking.
The dataset also includes the following augmented sets, which can be used for testing the model's robustness to… See the full description on the dataset page: https://huggingface.co/datasets/tanganke/resisc45.ek100_resized_jpgavm_residential_dataresisc45
Description
RESISC45 dataset is a publicly available benchmark for Remote Sensing Image Scene Classification (RESISC), created by Northwestern Polytechnical University (NWPU). This dataset contains 31,500 images, covering 45 scene classes with 700 images in each class.
The dataset does not have any default splits. Train, validation, and test splits were based on these definitions here… See the full description on the dataset page: https://huggingface.co/datasets/timm/resisc45.total-131-lambda02-residual-s_signal_type6-jh-epoch4
total-131-lambda02-residual-s_signal_type6-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3765625
Action score: 0.4171875
Valid samples: 320/320