Metadata-Version: 2.1
Name: monk-pytorch-cpu
Version: 0.0.1
Summary: Monk Classification - CPU - backends - pytorch
Home-page: https://github.com/Tessellate-Imaging/monk_v1
Author: Tessellate Imaging
Author-email: abhishek@tessellateimaging.com
License: UNKNOWN
Description: # monk_v1 [![Tweet](https://img.shields.io/twitter/url/https/github.com/tterb/hyde.svg?style=social)](http://twitter.com/share?text=Check%20out%20Monk:%20An%20Open%20Source%20Unified%20Wrapper%20for%20Computer%20Vision&url=https://github.com/Tessellate-Imaging/monk_v1&hashtags=MonkAI,OpenSource,UnifiedWrapper,DeepLEarning,ComputerVision,TessellateImaging) [![](http://hits.dwyl.io/Tessellate-Imaging/monk_v1.svg)](http://hits.dwyl.io/Tessellate-Imaging/monk_v1)  ![](https://tokei.rs/b1/github/Tessellate-Imaging/monk_v1) ![](https://tokei.rs/b1/github/Tessellate-Imaging/monk_v1?category=files)
        
        
        [Website](https://monkai.org/)
        
        #### Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.
        [![Version](https://img.shields.io/badge/version-v1.0-lightgrey)](https://github.com/Tessellate-Imaging/monk_v1) &nbsp; &nbsp;
        [![Build_Status](https://img.shields.io/badge/build-passing-green)](https://github.com/Tessellate-Imaging/monk_v1)
        
        
        # Table of Contents
          - [Sample Showcase](#1)
          - [Installation](#2)
          - [Study Roadmaps, Examples, and Tutorials](#3)
          - [Documentation](#4)
          - [TODO](#5)
        
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        <a id="1"></a>
        ## Sample Showcase
        
        #### Create an image classification experiment.
        - Load foldered dataset
        - Set number of epochs
        - Run training
        
        ```python
        ptf = prototype(verbose=1)
        ptf.Prototype("sample-project-1", "sample-experiment-1")
        ptf.Default(dataset_path="./dataset_cats_dogs_train/", 
                        model_name="resnet18", freeze_base_network=True, num_epochs=2)
        ptf.Train()
        ```
        
        #### Inference
        
        ```python
        img_name = "./monk/datasets/test/0.jpg";
        predictions = ptf.Infer(img_name=img_name, return_raw=True);
        print(predictions)
        ```
        
        
        #### Compare Experiments
        
        - Add created experiments with different hyperparameters
        - Generate comparison plots
        
        ```python
        ctf = compare(verbose=1);
        ctf.Comparison("Sample-Comparison-1");
        ctf.Add_Experiment("sample-project-1", "sample-experiment-1");
        ctf.Add_Experiment("sample-project-1", "sample-experiment-2");
            .
            . 
            .
        ctf.Generate_Statistics();
        ```
        
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        <a id="2"></a>
        ## Installation
        
        Support for
          - OS
              - Ubuntu 16.04
              - Ubuntu 18.04
              - Mac OS
              - Windows 
          - Python
              - Version 3.6
              - Version 3.7
          - Cuda
              - Version 9.0
              - Version 9.2
              - Version 10.0
              - Version 10.1
        
        For Installation instructions visit: [Link](https://github.com/Tessellate-Imaging/monk_v1/tree/master/installation)
        
        
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        <a id="3"></a>
        ## Study Roadmaps
        
        
          - [Getting started with Monk](https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/1_getting_started_roadmap)
          - [Python sample examples](https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/python_sample_examples)
          - [Image Processing and Deep Learning](https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/3_image_processing_deep_learning_roadmap)
          - [Transfer Learning](https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/2_transfer_learning_roadmap)
          - [Image classification zoo](https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/4_image_classification_zoo)
        
        
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        <a id="4"></a>
        ## Documentation
        
        - [List of available models, layers, blocks, optimizers](https://github.com/Tessellate-Imaging/monk_v1/tree/master/monk)
        
        - [Functional Documentation](https://abhi-kumar.github.io/monk_v1_docs/) (Will be merged with Latest docs soon)
            - Main Prototype Functions
                - [Mxnet Backend](https://abhi-kumar.github.io/monk_v1_docs/gluon_prototype.html)
                - [Pytorch Backend](https://abhi-kumar.github.io/monk_v1_docs/pytorch_prototype.html)
                - [Keras Backend](https://abhi-kumar.github.io/monk_v1_docs/keras_prototype.html)
                - [Comparison](https://abhi-kumar.github.io/monk_v1_docs/compare_prototype.html)
            - [System Functions](https://abhi-kumar.github.io/monk_v1_docs/system/index.html)
            - [Mxnet Backend base Functions](https://abhi-kumar.github.io/monk_v1_docs/gluon/index.html)
            - [Pytorch Backend base Functions](https://abhi-kumar.github.io/monk_v1_docs/pytorch/index.html)
            - [Keras Backend base Funtions](https://abhi-kumar.github.io/monk_v1_docs/tf_keras_1/index.html)
        
        - Features and Functions (In development):
            - [Introduction](https://clever-noyce-f9d43f.netlify.com/#/introduction)
            - [Setup](https://clever-noyce-f9d43f.netlify.com/#/setup/setup)
            - [Quick Mode](https://clever-noyce-f9d43f.netlify.com/#/quick_mode/quickmode_pytorch)
            - [Update Mode](https://clever-noyce-f9d43f.netlify.com/#/update_mode/update_dataset)
            - [Expert Mode](https://clever-noyce-f9d43f.netlify.com/#/expert_mode)
            - [Hyper Parameter Analyser](https://clever-noyce-f9d43f.netlify.com/#/hp_finder/model_finder)
            - [Compare Experiments](https://clever-noyce-f9d43f.netlify.com/#/compare_experiment)
            - [Resume Training](https://clever-noyce-f9d43f.netlify.com/#/resume_training)
        
        - [Complete Latest Docs](https://li8bot.github.io/monkai/#/home) (In Progress)
        
        
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        <a id="5"></a>
        ## TODO-2020
        
        ### TODO-2020 - Features
        - [x] Model Visualization
        - [ ] Pre-processed data visualization
        - [ ] Learned feature visualization
        - [ ] NDimensional data input - npy - hdf5 - dicom - tiff
        - [x] Multi-label Image Classification
        - [x] Custom model development
        
        
        
        ### TODO-2020 - General
        - [ ] Incorporate pep coding standards
        - [x] Functional Documentation
        - [x] Tackle Multiple versions of libraries
        - [x] Add unit-testing
        - [ ] Contribution guidelines
        
        
        ### TODO-2020 - Backend Support
        
        - [ ] Tensorflow 2.0
        - [ ] Chainer
        
        
        ### TODO-2020 - External Libraries
        - [ ] TensorRT Acceleration
        - [ ] Intel Acceleration
        - [ ] Echo AI - for Activation functions
        
        
        
        
        ## Copyright
        
        Copyright 2019 onwards, Tessellate Imaging Private Limited Licensed under the Apache License, Version 2.0 (the "License"); you may not use this project's files except in compliance with the License. A copy of the License is provided in the LICENSE file in this repository.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
