The code about the paper of " Multi-task generative adversarial learning for nuclei segmentation with dual attention and recurrent convolution"

[PatrickWilliams44]

Dear antifen, it is my great honor to see the paper of " Multi-task generative adversarial learning for nuclei segmentation with dual attention and recurrent convolution". In this paper, I see that the code will be available at :https://github.com/antifen/Nuclei-Segmentation. Could you please share your source code? I would be so grateful to see that, thank you very much! Looking forward to your reply!

[antifen]

Dear PatrickWilliams44, thank you for your interest in our research. The code will be uploaded later. I will send it to you by email attachment first, please check the email attachment.

Best regards.

Yours sincerely, Huadeng Wang

------------------ 原始邮件 ------------------ 发件人: "antifen/Nuclei-Segmentation" @.>; 发送时间: 2022年3月9日(星期三) 晚上10:56 @.>; @.***>; 主题: [antifen/Nuclei-Segmentation] The code about the paper of " Multi-task generative adversarial learning for nuclei segmentation with dual attention and recurrent convolution" (Issue #1)

Dear antifen, it is my great honor to see the paper of " Multi-task generative adversarial learning for nuclei segmentation with dual attention and recurrent convolution". In this paper, I see that the code will be available at :https://github.com/antifen/Nuclei-Segmentation. Could you please share your source code? I would be so grateful to see that, thank you very much! Looking forward to your reply!

— Reply to this email directly, view it on GitHub, or unsubscribe. Triage notifications on the go with GitHub Mobile for iOS or Android. You are receiving this because you are subscribed to this thread.Message ID: @.***>

从QQ邮箱发来的超大附件

nuclei_object_contour.rar (109.66M, 2022年04月09日 22:11 到期)进入下载页面：http://mail.qq.com/cgi-bin/ftnExs_download?t=exs_ftn_download&k=7c613530834d179be45071301337004d0251010704040a061f5206560d1a0652035318095404564f070305045751505403540254352e320c470259555c685d00580456446a545d0c460e40421b455310325c&code=2a50572b

[PatrickWilliams44]

Dear antifen,Thank you very much for sharing the code of this research project. I believe it can help me better understand your paper. I kindly ask to be able to contact you by sending an email if I have any questions later. Thank you very much,my gratitude is beyond words!

[PatrickWilliams44]

Dear antifen,I have downloaded the code, but I have some problems when running the "nuclei_train.py", such as missing "gt_op" module in the "from gt_op import gt_to_class" of this code. Can you tell me how to slove it? Thank you again！

[antifen]

Dear Dear PatrickWilliams, you can find file named "gt_op.py" in the folder "train_test". Its code is as follows: import numpy as np import sys sys.path.insert(0, '../src/') sys.path.insert(0, '../lib/')

def gt_to_class(gt):     '''     in this method     :param gt:   N C H W     :return:     N Class H W     '''     gt_arr0 = np.zeros(shape=(gt.shape[0], 1, gt.shape[2], gt.shape[3]))     gt_arr1 = np.zeros(shape=(gt.shape[0], 1, gt.shape[2], gt.shape[3]))     print(np.max(gt), np.min(gt))     gt_arr0[np.where(gt == 0) ] = 1     print('get  2-C ground-truth')     gt_arr1[np.where(gt >0)]   = 1     gt_arr = np.concatenate([gt_arr0, gt_arr1], axis=1)

  Now our code is available at: https://github.com/antifen/Nuclei-Segmentation

Best regards.

@.***  & 13978393767） 桂林电子科技大学计算机与信息安全学院

------------------ 原始邮件 ------------------ 发件人: "antifen/Nuclei-Segmentation" @.>; 发送时间: 2022年3月16日(星期三) 中午12:12 @.>; 抄送: "汪华登@@.**@.>; 主题: Re: [antifen/Nuclei-Segmentation] The code about the paper of " Multi-task generative adversarial learning for nuclei segmentation with dual attention and recurrent convolution" (Issue #1)

Dear antifen,I have downloaded the code, but I have some problems when running the "nuclei_train.py", such as missing "gt_op" module in the "from gt_op import gt_to_class" of this code. Can you tell me how to slove it? Thank you again！

— Reply to this email directly, view it on GitHub, or unsubscribe. Triage notifications on the go with GitHub Mobile for iOS or Android. You are receiving this because you commented.Message ID: @.***>