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Project Details

Pipeline based on Pytorch RetinaFace project - https://github.com/biubug6/Pytorch_Retinaface


Supported Models

  • mobilenet
  • resnet


Installation

Supports

  • Python 3.6
  • Cuda 9.0, 10.0 (Other cuda version support is experimental)

cd installation

cat requirements.txt | xargs -n 1 -L 1 pip install




Pipeline

  • Load Dataset

gtf.Train_Dataset(img_dir, anno_file);

  • Dataset params

gtf.Dataset_Params(batch_size=32, num_workers=4);

  • Load Model

gtf.Model_Params(model_type="mobilenet", use_gpu=True, resume_from=None);

  • Set Hyper Parameters

gtf.Hyper_Parameters(lr=0.0001, momentum=0.9, weight_decay=0.0005, gamma=0.1);

gtf.Training_Params(num_epochs=20, output_dir="weights_trained");

  • Train

gtf.Train();




TODO

  • Add support for Coco-Type Annotated Datasets
  • Add support for VOC-Type Annotated Dataset
  • 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