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Dataset, necessary Scripts and trained SSD Model for detecting Hands in Realtime.

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deeptraining_hands

This is a collection of scripts to setup datasets and/or to convert files of certain boundingbox-annotation formats into another
Run one or several scripts to get to your desired training format.

Note: Some of the scripts use packages provided by tensorflow's API
So make sure to include tensorflow/models/research to your PYTHONPATH

To Set Up the Oxford- and/or Egohands Dataset, run:

egohands_setup.py
oxfordhands_setup.py

Example: to get from .mat annotations to a tensorflow runnable .record file, run:

mat_to_xml.py
xml_to_csv.py
csv_img_to_tfrecord.py

All scripts create/support following folder structure to be able to support tensorflow aswell as yolo-darknet projects:

.
├── data
│   ├── train 
│   │   ├── annotations
│   │   │   ├── mat
│   │   │   │   ├──file1.mat
│   │   │   │   └── ...
│   │   │   └── xml
│   │   │       ├──file1.xml
│   │   │       └── ...
│   │   ├── labels
│   │   │   ├──file1.txt
│   │   │   └── ...
│   │   └── images
│   │       ├──file1.jpg
│   │       └── ...
│   ├── eval
│   │   └── ...
│   │
│   ├── train_labels.csv
│   ├── eval_labels.csv
│   ├── label_map.pbtxt
│   ├── train.record
│   ├── eval.record
│   ├── train.txt
│   └── eval.txt
│   
└── model

See howto_tf and howto_yolo for information how to train on yolo or tensorflow

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