About FOTS.PyTorch

FOTS Pytorch Implementation

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jiangxiluning

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README.md

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Introduction

This is a PyTorch implementation of FOTS.

[x] ICDAR Dataset
[x] SynthText 800K Dataset
[x] detection branch
[x] recognition branch
[x] eval
[x] multi-gpu training
[x] reasonable project structure
[x] wandb
[x] pytorch_lightning
[x] eval with different scales
[ ] OHEM

Instruction

Requirements

   conda create --name fots --file spec-file.txt
   conda activate fots
   pip install -r reqs.txt

   cd FOTS/rroi_align
   python build.py develop

Training

   # quite easy, for single gpu training set gpus to [0]. 0 is the id of your gpu.
   python train.py -c pretrain.json
   python train.py -c finetune.json

Evaluation

python eval.py 
-c finetune.json
-m <your ckpt>
-i <icdar2015 folder contains train and test>
--detection    
-o ./results
--cuda
--size "1280 720"
--bs 2
--gpu 1

with --detection flag to evaluate detection only or without flag to evaluate e2e

Benchmarking and Models

Belows are E2E Generic benchmarking results on the ICDAR2015. I pretrained on Synthtext (7 epochs). Pretrained model (code: 68ta). Finetuned (5000 epochs) model (code: s38c).