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ACFormer

Code for Affine-Consistent Transformer for Multi-Class Cell Nuclei Detection (ICCV 2023)

(Continually updating ...)

Overall Framework

Requisities

-python=3.8

-pytorch=1.12.1+cu102

Installation

Install mmcv using mim

pip install -U openmim
mim install mmcv-full==1.6.1

Git clone acformer

git clone https://github.com/LL3RD/ACFormer.git

Install

cd ACFormer
cd thirdparty/mmdetection 
python -m pip install -e .
cd ../.. 
python -m pip install -e .

Dataset

Lizard Dataset

Your can download Original Lizard from the official website or Preprocessed Lizard that is converted to hovernet consep format and split into patches.

CoNSeP Dataset

Your can download 20x CoNSeP Dataset from here.

Main Result

Lizard Dataset

Method F1d F1c Model Weights Config Files
ACFormer 0.782 0.557 Checkpoint Config

CoNSeP Dataset

Method F1d F1c Model Weights Config Files
ACFormer 0.739 0.613 Checkpoint Config

Evaluation

Modify your dataset path and checkpoint path in tools/inference_lizard.py and run

python tools/inference_lizard.py
python tools/inference_consep.py

Acknowledgement

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Code for Affine-Consistent Transformer for Multi-Class Cell Nuclei Detection (ICCV 2023)

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