Metadata-Version: 2.1
Name: monk_test1
Version: 0.0.3
Summary: A small example package
Home-page: https://github.com/pypa/sampleproject
Author: Example Author
Author-email: author@example.com
License: UNKNOWN
Description: ## Project Details
        Pipeline based on GluonCV Fintuning project - https://gluon-cv.mxnet.io/build/examples_detection/index.html
        
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        ## Installation
        
        Supports 
        - Python 3.6
        - Python 3.7
            
        `cd installation`
        
        Check the cuda version using the command
        
        `nvcc -V`
        
        Select the right requirements file and run 
        
        `cat <selected requirements file> | xargs -n 1 -L 1 pip install`
        
        For example for cuda 9.0
        
        `cat requirements_cuda9.0.txt | xargs -n 1 -L 1 pip install`
        
        
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        ## Functional Documentation
          [Link](https://abhi-kumar.github.io/1_gluoncv_finetune_docs/)
        
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        ## Pipeline
        
        - Load Dataset
        
        `gtf.Dataset(root_dir, img_dir, anno_file, batch_size=batch_size);`
        
        - Load Model
        
        `gtf.Model(model_name, use_pretrained=pretrained, use_gpu=gpu);`
        
        - Set Hyper-parameter
        
        `gtf.Set_Learning_Rate(0.001);`
        
        - Train
        
        `gtf.Train(epochs, params_file);`
        
        
        
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        ## TODO
        
        - [x] Add SSD support
        - [x] Add YoloV3 support
        - [ ] Add support for Coco-Type Annotated Datasets
        - [x] Add support for VOC-Type Annotated Dataset
        - [ ] Add Faster-RCNN support
        - [x] Test on Kaggle and Colab 
        - [ ] Add validation feature & data pipeline
        - [ ] Add Optimizer selection feature
        - [ ] Enable Learning-Rate Scheduler Support
        - [ ] Enable Layer Freezing
        - [ ] Set Verbosity Levels
        - [ ] Add Project management and version control support (Similar to Monk Classification)
        - [ ] Add Graph Visualization Support
        - [ ] Enable batch proessing at inference
        - [ ] Add feature for top-k output visualization
        - [x] Add Multi-GPU training
        - [ ] Auto correct missing or corrupt images - Currently skips them
        - [ ] Add Experimental Data Analysis Feature
        
        
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        ## External Contributors list 
        
        - https://github.com/THEFASHIONGEEK: Multi GPU feature
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Environment :: GPU :: NVIDIA CUDA :: 9.0
Requires-Python: >=3.6
Description-Content-Type: text/markdown
