This is the Windows app named MMClassification whose latest release can be downloaded as MMPreTrainReleasev1.0.1.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named MMClassification with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS:
MMClassification
DESCRIPTION:
MMClassification is an open-source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. Supports DenseNet, VAN and PoolFormer, and provide pre-trained models. Supports training on IPU. Supports a series of CSP networks, such as CSP-ResNet, CSP-ResNeXt and CSP-DarkNet. MMClassification is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedback. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to re-implement existing methods and develop their own new classifiers. MMClassification mainly uses python files as configs. The design of our configuration file system integrates modularity and inheritance, facilitating users to conduct various experiments.
Features
- The master branch works with PyTorch 1.5+
- Various backbones and pretrained models
- Bag of training tricks
- Large-scale training configs
- High efficiency and extensibility
- Powerful toolkits
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/mmclassification.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.