Open eVision Deep Learning Studio
Deep Learning training and evaluation application
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Open eVision Deep Learning Studio
Open eVision Deep Learning Studio is an application that assists the user during the creation of the dataset as well as the training and testing of the Deep Learning tools of Open eVision. Open eVision Deep Learning Studio is free and does not require any license. It allows you to test the Deep Learning libraries using your own images. No programming is required.
The Highlight Features
- Ease the evaluation of Open eVision’s Deep Learning tools
- Dataset creation and image annotation for classification, segmentation, and object localization
- Create and configure dataset splits to decide how your images are used
- Manage the data augmentation transformations
- Train your tools in succession thanks to the training queue
- Validation and analysis of the results of the trained tools
- Available on Windows and Linux
- Free of charge
Key Features
Data augmentation
The rich data augmentation capabilities of EasyClassify, EasySegment, and EasyLocate are available in Deep Learning Studio. Tune and visualize the geometric, color, and noise data augmentations. You can create different set of data augmentation settings to experiment how it influence your results.
Annotate your dataset
Deep Learning Studio integrates annotation tools adapted to each library. For classification and unsupervised segmentation, you can quickly assign label to each image. For supervised segmentation, the segmentation editor allows you to draw the ground truth segmentation. For localisation, the object editor allows you to quickly draw the bounding box around each of your objects.
The image editor also allows you to select a region of interest and mask parts of your image
Deep Learning projects
A Deep Learning Studio project manages your dataset and the Deep Learning tools you created. A project is associated with one the Deep Learning tool (EasyClassify, EasySegment Unsupervised, EasySegment Supervised or EasyLocate) and supports all their features.
Within a project, you can create as many tools as you want. It allows you to easily experiment with the parameters of the tools, different split of the dataset, or data augmentation settings.
Configure and train your tools
The rich data augmentation capabilities of EasyClassify, EasySegment, and EasyLocate are available in Deep Learning Studio. Tune and visualize the geometric, color, and noise data augmentations. You can create different set of data augmentation settings to experiment how it influence your results.
Control how your images used
Deep Learning Studio allows you to split your dataset into training, validation, and test sets. You can create multiple dataset splits to experiment and check the performance of tools trained with different set of images.
You can create dataset splits at random or manually select the set of each image.
Validation and result analysis
The validation process is customized for each library to allow you to get the most out of your data. A comprehensive set of metrics, tables, and/or graphs is available to analyze and explore the results of the training process.
Tables and confusion matrixes allow you to filter your results to understand the strengths and weaknesses of the trained models. Score histograms and ROI curves are useful to select a threshold and adapt the trained models to your needs.
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