An inceptionv3 model trained on the OpenImages (with weights) , ready to run in Tensorflow.

• Download the main model by running bash download_model.sh
• As a standalone file, run python tag.py <image>
• To use as a module, call predict_on_image(image_path, return_dict={}), to receive the results in return_dict

If you use the OpenImages dataset in your work, please cite it as:

APA-style citation: "Krasin I., Duerig T., Alldrin N., Veit A., Abu-El-Haija S., Belongie S., Cai D., Feng Z., Ferrari V., Gomes V., Gupta A., Narayanan D., Sun C., Chechik G, Murphy K. OpenImages: A public dataset for large-scale multi-label and multi-class image classification, 2016. Available from https://github.com/openimages".

BibTeX

@article{openimages,
  title={OpenImages: A public dataset for large-scale multi-label and multi-class image classification.},
  author={Krasin, Ivan and Duerig, Tom and Alldrin, Neil and Veit, Andreas and Abu-El-Haija, Sami
    and Belongie, Serge and Cai, David and Feng, Zheyun and Ferrari, Vittorio and Gomes, Victor
    and Gupta, Abhinav and Narayanan, Dhyanesh and Sun, Chen and Chechik, Gal and Murphy, Kevin},
  journal={Dataset available from https://github.com/openimages},
  year={2016}
}