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MVTEC Deep Learning Tool 23.11 Full Version x64 windows 深度学习工具dlt-23.11完整版
文件名: dlt-23.11.zip
文件大小: 2520374897 字节 (2.35 GB)
修改日期: 2023-11-22 21:06
MD5: 5769a748a2a340464b3582e74c34dae6
SHA1: 00a1156560850593f9f320bb68cf6d2b818e070d
SHA256: 86e86ae11be087e97203aa1b9be81ce045f2a4c8ddc9aa95a3e34cea5ad80dc7
CRC32: fa9a7afc
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--来自百度网盘超级会员V6的分享
深度学习工具的发布说明This document provides the release notes for MVTec Deep Learning Tool 23.11, as released on 2023-11-23. The license of version 23.11 is valid until 2025-12-31. Version 23.11 Early AdopterNew Features- The DLT now supports the evaluation of Semantic Segmentation projects.
- The DLT now is based on HALCON 23.05 Progress.
- It is now possible to optimize and calibrate deep learning models for int8. Currently, only the TensorRT plugin allows exporting models for int8. The number of used calibration images can be configured before evaluation and model export.
- The DLT now supports a basic pan gesture for laptop touchpads on the Image page.
Resolved Issues and Improvements- The restricted domain was not displayed correctly in full image view. This problem has been fixed.
- After switching the confusion matrix view to the vertical layout, the confusion matrix could look broken if there was very little space. This problem has been fixed.
- In Anomaly Detection projects, changing the ground truth class of an image via the Image Details view on the Evaluation page could set a different image as the current image, even if the image remained in the current image list. This problem has been fixed.
- When changing to a page that does not support image filters, the quick text filter content was lost. This problem has been fixed.
- If on the Evaluation page the class of the inspected item was changed, it could happen that the anomaly state icon was not updated accordingly. This problem has been fixed.
- When leaving the edit mode for a mask, it could happen that the wrong editing mode was activated but not highlighted when changing to edit mode again. Now, the pen mode is always activated when entering the edit mode.
- If the confusion matrix on the Evaluation page is larger than the available space, only a part of the actual matrix can be displayed. In this case, it was not possible to drag the visible part of the matrix by clicking anywhere other than the horizontal summary rows below the matrix. The problem has been fixed.
- For GC-AD projects, it was not possible to set a patch size larger than 256. This problem has been fixed.
- When a new Semantic Segmentation project was created by importing the dataset file of an Instance Segmentation project, one of the existing classes was selected as background class. Thereby, the labels of that class could be lost. This problem has been fixed. Now, a new background class will always be created in this case.
- When creating a split in an Anomaly Detection project, the table with the suggested split distribution suggested 100 anomaly images for validation even if the whole dataset contained less than 100 anomaly images. This visualization problem has been fixed. Now, the validation entry for anomaly images does not show more images than the dataset contains.
- For Anomaly Detection projects, unlabeled images were marked as 'good' on the Evaluation page. This problem has been fixed.
- The DLT could crash when the Shift key was pressed in the Comment area on the Image page, e.g., when entering uppercase letters or special characters. This problem has been fixed.
- For Object Detection, Instance Segmentation, and Semantic Segmentation projects, the DLT could crash when creating a split with zero test images. This problem has been fixed.
- When importing an incompatible dataset into an existing project, the error message has been improved. Now, the best fitting method is shown in the error message.
- For projects of type anomaly detection, wrong tooltips were displayed when hovering over the confusion matrix in some cases. This problem has been fixed.
- The displayed number of used images in the split creation dialog was not correct in some cases. This problem has been fixed.
- If in an Anomaly Detection project a lot of images including a lot of unlabeled images were evaluated, the DLT could crash. This problem has been fixed.
- The filename of the current model did not have the suffix ".hdl". This problem has been fixed.
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