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DRCaptioning


The instruction of the object-centric caption generation.

Preliminaries

Our model is implemented in Torch, and depends on the following packages:

After installing torch, you can install / update these dependencies by running the following:

luarocks install torch
luarocks install nn
luarocks install image
luarocks install lua-cjson
luarocks install https://raw.githubusercontent.com/qassemoquab/stnbhwd/master/stnbhwd-scm-1.rockspec
luarocks install https://raw.githubusercontent.com/jcjohnson/torch-rnn/master/torch-rnn-scm-1.rockspec

Test

To run the model on new images, use the script run_model.lua. To run the model on a test image, use the following command:

th run_model.lua -input_image /path/to/my/image/file -output_vis_dir /path/to/the/output/folder

If you have an entire directory of images on which you want to run the model, use the -input_dir flag instead:

th run_model.lua -input_dir /path/to/my/image/folder -output_vis_dir /path/to/the/output/folder

Results

The resulting output file format is as follows:

[
	{
		"boxes": [
			[9.4456, 46.8276,569.0354, 368.3203],
			[183.6740, 77.7138, 185.4196, 332.1285],
			[403.1037, 77.593994, 323.3377, 334.4553],
			...
			]
		"captions": [
			  'the man wearing black shirt',
			  'the man has head',
			  'the man wearing a white shirt',
			  ...
			  ]

	}
...
]

Acknowledgements

This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (2017-0-01780, The technology development for event recognition/relational reasoning and learning knowledge based system for video understanding)

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  • Jupyter Notebook 72.6%
  • Lua 22.3%
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