Kornia vs Xcessiv
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A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python. | It is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. |
Fully define your data source, cross-validation process, relevant metrics, and base learners with Python code;Any model following the Scikit-learn API can be used as a base learner;Task queue based architecture lets you take full advantage of multiple cores and embarrassingly parallel hyperparameter searches;Direct integration with TPOT for automated pipeline construction;Automated hyperparameter search through Bayesian optimization;Easy management and comparison of hundreds of different model-hyperparameter combinations;Automatic saving of generated secondary meta-features;Stacked ensemble creation in a few clicks;Automated ensemble construction through greedy forward model selection;Export your stacked ensemble as a standalone Python file to support multiple levels of stacking | Perform feature detection; Perform data augmentation in the GPU;
Perform image filtering and edge detection;
Differentiable computer vision library |
Statistics | |
GitHub Stars 1.3K | GitHub Stars 10.8K |
GitHub Forks 105 | GitHub Forks 1.1K |
Stacks 0 | Stacks 14 |
Followers 7 | Followers 6 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Xcessiv, Kornia?
Cloudinary
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imgix
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TensorFlow
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OpenCV
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scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
ImageKit
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Keras
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Kubeflow
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TensorFlow.js
Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
