TextBPN

Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection； Accepted by ICCV2021.

Note: The complete code (including training and testing) will be released in TextBPN V2. Relevant work is advancing, and those who are interested in our work can pay more attention to the updates here.

1.Prerequisites t

python 3.9;
PyTorch 1.7.0;
Numpy >=1.2.0
CUDA 11.1;
GCC >=10.0;
NVIDIA GPU(with 11G or larger GPU memory for inference);

2.Dataset Links

3.Models

Total-Text model (pretrained on ICDAR2017-MLT)
CTW-1500 model (pretrained on ICDAR2017-MLT)
MSRA-TD500 model (pretrained on ICDAR2017-MLT)

4.Running Evaluation

run:

sh eval.sh

The details are as follows:

#!/bin/bash
##################### Total-Text ###################################
# test_size=[640,1024]--cfglib/option
CUDA_LAUNCH_BLOCKING=1 python eval_textBPN.py --exp_name Totaltext --checkepoch 390 --dis_threshold 0.3 --cls_threshold 0.825 --test_size 640 1024 --gpu 1

###################### CTW-1500 ####################################
# test_size=[640,1024]--cfglib/option
# CUDA_LAUNCH_BLOCKING=1 python eval_textBPN.py --exp_name Ctw1500 --checkepoch 560 --dis_threshold 0.3 --cls_threshold 0.8 --test_size 640 1024 --gpu 1

#################### MSRA-TD500 ######################################
# test_size=[640,1024]--cfglib/option
#CUDA_LAUNCH_BLOCKING=1 python eval_textBPN.py --exp_name TD500 --checkepoch 680 --dis_threshold 0.3 --cls_threshold 0.925 --test_size 640 1024 --gpu 1

TextBPN Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection

Related tags

Overview

TextBPN

1.Prerequisites t

2.Dataset Links

3.Models

4.Running Evaluation

5.Experiments results

Owner

S.X.Zhang

EqGAN - Improving GAN Equilibrium by Raising Spatial Awareness

Neural machine translation between the writings of Shakespeare and modern English using TensorFlow

Dynamical Wasserstein Barycenters for Time Series Modeling

Official implementation of the Neurips 2021 paper Searching Parameterized AP Loss for Object Detection.

A curated list of neural network pruning resources.

A module for solving and visualizing Schrödinger equation.

LiDAR Distillation: Bridging the Beam-Induced Domain Gap for 3D Object Detection

DetCo: Unsupervised Contrastive Learning for Object Detection

Supplemental learning materials for "Fourier Feature Networks and Neural Volume Rendering"

TyXe: Pyro-based BNNs for Pytorch users

PyTorch implementation for NED. It can be used to manipulate the facial emotions of actors in videos based on emotion labels or reference styles.

A machine learning package for streaming data in Python. The other ancestor of River.

AFL binary instrumentation

Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"

Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19)

CasualHealthcare's Pneumonia detection with Artificial Intelligence (Convolutional Neural Network)

Pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"

A geometric deep learning pipeline for predicting protein interface contacts.

Epidemiology analysis package

A code generator from ONNX to PyTorch code