Toolkit for coding, including deep learning, image processing, file processing.

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 |- source-code/
 |- bn_details.py
 |- bn_run.py
 |- CrossEntropyLoss.py
 |- regularization.py
 |- SoftMax.py
 | - torch_model/
 |- vgg.py
 |- resnet.py
 |- densenet.py
 |- fcn8s.py
 |- unet.py
 |- pspnet.py
 |- deeplabv3+ (deeplabv3+.py, resnet_deeplab.py, aspp.py, decoder.py)
 |- DualGCN.py
 |- JL_DCF.py
 |- swin transformer (swin_transformer_seg.py, mlp_decoder.py)
 |- torch_template
 |- test_net.py
 |- test.py
 |- train.py
 |- utils/
 |- data
 |- data_config.py
 |- divide_data.py
 |- img_ops.py
 |- imgs2video.py
 |- nms
 |- nms_cpu.py
 |- ...
 |- bbox_iou.py
 |- bbox_iou_python.py
 |- img2video.py
 |- BN_torch.py
 |- count_norm.py
 |- dataset.py
 |- loss.py
 |- seg_transform.py
 |- show_img.py
 |- README.md

source-code/bn_details.py : implementation of BN(BatchNormalization) and analysis of its details.

source-code/bn_run.py : implementation of BN(BatchNormalization) and simulation of running.

source-code/CrossEntropyLoss.py : implementation of custom CrossEntropyLoss and BCELoss.

source-code/regularization.py : implementation of L1/L2 normalization, L1/L2 regularization and Dropout.

source-code/SoftMax.py : implementation of SoftMax function in various version.

model/vgg.py : ICLR(2015) paper.

model/resnet.py : CVPR(2016) paper.

model/densenet.py : CVPR(2017) paper.

model/fcn8s.py : CVPR(2015) paper.

model/unet.py : MICCAI(2015) paper.

model/pspnet.py : CVPR(2017) paper.

model/deeplabv3+ : ECCV(2018) paper.

model/DualGCN.py : BMVC(2019) paper.

model/JL_DCF.py : CVPR(2020) paper.

model/swin transformer : arXiv(2021) paper.

utils/data/count_nrom.py : count the mean and the standard deviation from datasets.

utils/data/data_config.py : config (hyper-)parameters in main.py.

utils/data/dataset.py : implementation of dataset in segmentation.

utils/data/divide_data.py : divide origin data into train and valid set.

utils/data/img_ops.py : resize, hist equalize and blur images using opencv.

utils/data/imgs2video.py : convert images to video and extract images from video.

utils/data/seg_transform.py : implementation of transform module in segmentation.

utils/nms/nms_cpu.py : remove useless bounding-box by nms(Non-maximum suppression).

utils/bbox_iou.py : calculate iou(Intersection-of-Union) between two bounding-box.

utils/bbox_iou_python.py : calculate iou in python version.

utils/imgs2video.py : convert images to video and extract images from video.

utils/logging_util.py : implementation of logging module with formatting.

utils/loss.py : implementation of loss function, including FocalLoss, BinaryDiceLoss.

utils/show_img.py : visualize image in both plt(matplotlib.pyplot) and cv2(opencv).

(Updating...)