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meshed-memory-transformer reviews and mentions
- [D] Data transfer(image features) between different models in separate docker containers
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[R] end-to-end image captioning
I could use some up-to-date models (e.g, this one: https://github.com/aimagelab/meshed-memory-transformer), but all those I looked into require pre-processing step of features/bounding-boxes generation. The problem is that I can't use an off-the shelf bounding-box extraction model as it would not perform well on the dataset I have (images are not like COCO at all). So I was wondering if there is a relatively up-to-date architecture that I can use that will not require this processing step. That is, an implementation that requires only inputs (images) and outputs (sentences).
Stats
aimagelab/meshed-memory-transformer is an open source project licensed under BSD 3-clause "New" or "Revised" License which is an OSI approved license.
The primary programming language of meshed-memory-transformer is Python.
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