Abstract
Object Detection is one of the most fundamental and challenging areas in computer vision. A detailed analysis and evaluation is key to understanding the performance of custom Deep Learning models. In this contribution, we present an application which is able to run inference on custom data for models created in different machine learning frameworks (e.g. TensorFlow, PyTorch), visualize the output and evaluate it in detail. Both, the Object Detection models and the data sets, are uploaded and executed locally without leaving the application. Numerous filtering options, for instance filtering on mAP, on NMS or on IoU, are provided.
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Bogomasov, K., Geuer, T., Conrad, S. (2023). InfEval: Application for Object Detection Analysis. In: Kamps, J., et al. Advances in Information Retrieval. ECIR 2023. Lecture Notes in Computer Science, vol 13982. Springer, Cham. https://doi.org/10.1007/978-3-031-28241-6_14
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DOI: https://doi.org/10.1007/978-3-031-28241-6_14
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