Parsagh1383/FE-CLIP_Reproduction_Checkpoint

FE-CLIP Reproduction Checkpoints: MVTec AD & VisA

This repository provides PyTorch checkpoints from an independent reconstruction of:

FE-CLIP: Frequency Enhanced CLIP Model for Zero-Shot Anomaly Detection and Segmentation
Tao Gong, Qi Chu, Bin Liu, Wei Zhou, and Nenghai Yu
ICCV 2025, pages 21220–21230.

• Official paper
• Supplementary material

These are independently reproduced research checkpoints. They are not official checkpoints released by the FE-CLIP authors, and this repository is not affiliated with the original authors.

Repository Contents

The trained checkpoints are distributed as a single archive:

FE-CLIP.zip

Archive information:

Property	Value
Compressed size	1,824,019,956 bytes
Displayed size	Approximately 1.82 GB
Uncompressed size	Approximately 1.85 GiB
PyTorch checkpoints	18
Training-history files	2
SHA-256	7821723A70AD54720F78D46F46D0E812F26B0D394280C8EAA5D8A76A19751499

The ZIP contains the following structure:

FE-CLIP/
├── train_on_mvtec_seed_111/
│   ├── feclip_train_on_mvtec_epoch_01.pth
│   ├── feclip_train_on_mvtec_epoch_02.pth
│   ├── feclip_train_on_mvtec_epoch_03.pth
│   ├── feclip_train_on_mvtec_epoch_04.pth
│   ├── feclip_train_on_mvtec_epoch_05.pth
│   ├── feclip_train_on_mvtec_epoch_06.pth
│   ├── feclip_train_on_mvtec_epoch_07.pth
│   ├── feclip_train_on_mvtec_epoch_08.pth
│   ├── feclip_train_on_mvtec_epoch_09.pth
│   └── history.json
└── train_on_visa_seed_111/
    ├── feclip_train_on_visa_epoch_01.pth
    ├── feclip_train_on_visa_epoch_02.pth
    ├── feclip_train_on_visa_epoch_03.pth
    ├── feclip_train_on_visa_epoch_04.pth
    ├── feclip_train_on_visa_epoch_05.pth
    ├── feclip_train_on_visa_epoch_06.pth
    ├── feclip_train_on_visa_epoch_07.pth
    ├── feclip_train_on_visa_epoch_08.pth
    ├── feclip_train_on_visa_epoch_09.pth
    └── history.json

Each checkpoint is approximately 105 MiB.

Which Checkpoint Should I Use?

For normal evaluation, use the final epoch-9 checkpoint.

Target dataset	Checkpoint to use
MVTec AD	train_on_visa_seed_111/feclip_train_on_visa_epoch_09.pth
VisA	train_on_mvtec_seed_111/feclip_train_on_mvtec_epoch_09.pth
Other zero-shot datasets	Start with the MVTec-trained epoch-9 checkpoint

This direction is intentional. FE-CLIP follows a cross-dataset zero-shot anomaly-detection protocol:

• The MVTec-trained checkpoint is evaluated on VisA and other target datasets.
• The VisA-trained checkpoint is evaluated on MVTec AD.
• No training images from the target dataset should be used during zero-shot evaluation.

Epochs 1–8 are included for learning-curve analysis, ablation studies, checkpoint selection, and resuming experiments.

Download and Extract

Hugging Face CLI

Replace the repository name below with the actual repository ID:

hf download Parsagh1383/YOUR_REPOSITORY_NAME FE-CLIP.zip --local-dir .

Extract it with:

unzip FE-CLIP.zip

Python

from pathlib import Path
from zipfile import ZipFile