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A small example package

Project description

Project Details

Pipeline based on GluonCV Fintuning project -



  • 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

Functional Documentation



  • 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


  • Train

gtf.Train(epochs, params_file);


  • Add SSD support
  • Add YoloV3 support
  • Add support for Coco-Type Annotated Datasets
  • Add support for VOC-Type Annotated Dataset
  • Add Faster-RCNN support
  • 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
  • Add Multi-GPU training
  • Auto correct missing or corrupt images - Currently skips them
  • Add Experimental Data Analysis Feature

External Contributors list

Project details

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