Back to datasets
Dataset assetOpen Source CommunityImage DatasetDomain Adaptation
Office-31, Office-Home, VisDA-2017, DomainNet
Office‑31 consists of 31 office‑object categories, Office‑Home contains 65 everyday‑object categories, VisDA‑2017 is a dataset for visual domain adaptation challenges, and DomainNet is a large‑scale multi‑domain image dataset.
Source
github
Created
Nov 11, 2024
Updated
Dec 6, 2024
Signals
1,006 views
Availability
Linked source ready
Overview
Dataset description and usage context
Dataset Overview
Datasets
-
Office‑31:
- Download link: Office‑31
- Storage path:
data/office/domain_adaptation_images/
-
Office‑Home:
- Download link: Office‑Home
- Storage path:
data/office-home/
-
VisDA‑2017:
- Download link: VisDA‑2017
- Storage path:
data/
-
DomainNet:
- Download link: DomainNet
- Storage path:
data/
Training
- Training Command:
- Example:
python3 main.py --train_batch_size 16 --dataset office --name wa \ --source_list data/office/webcam_list.txt --target_list data/office/amazon_list.txt \ --test_list data/office/amazon_list.txt --num_classes 31 --model_type ViT-B_16 \ --pretrained_dir checkpoint/ViT-B_16.npz --num_steps 5000 --img_size 256 \ --beta 0.1 --gamma 0.2 --use_im --theta 0.1 - All commands are listed in
script.txt.
- Example:
Pre‑trained Models
- ViT‑B_16:
- ImageNet‑21K: ViT‑B_16 (ImageNet‑21K)
- ImageNet: ViT‑B_16 (ImageNet)
- Storage path:
checkpoint/
Need downstream help?
Pair the dataset with AI analysis and content workflows.
Once the source passes your review, move straight into summarization, transformation, report drafting, or presentation generation with the JuheAI toolchain.