ssd_keras
efficientnet-lite-keras
| ssd_keras | efficientnet-lite-keras | |
|---|---|---|
| 4 | 1 | |
| 1,846 | 38 | |
| - | - | |
| 0.0 | 0.0 | |
| about 2 years ago | about 1 year ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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ssd_keras
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Failed to get convolution algorithm. This is probably because cuDNN failed to initialize,
In Tensorflow/ Keras when running the code from https://github.com/pierluigiferrari/ssd_keras, use the estimator: ssd300_evaluation. I received this error.
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Shared weights between different implementations
Yeah, the order of axes was different between those 2. Another guy used https://github.com/pierluigiferrari/ssd_keras https://github.com/uhfband/keras2caffe/blob/master/keras2caffe/convert.py probably not much actual use but maybe some more reassurance?
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Simplest way to deploy Keras NN model into C++?
Don't know about simplest, but we either used caffe or tensorrt, it is maybe a bit difficult to use but I'd actually say simple fast GPU inference is what it's geared towards. There is a keras -> caffe converter https://github.com/pierluigiferrari/ssd_keras here, I think. Caffe is a c++ lib, typical, with dependencies and all. I've never heard anything of tensorflow running on c++. But with tensorrt you should get an "artifact" that you'd load, no matter where it comes from
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ValueError: Layer model expects 1 input(s), but it received 2 input tensors. Help?
Tensorflow V1 Keras code (original repo): Github Repo
efficientnet-lite-keras
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[P] EfficientNet-lite in Keras (functional API).
Github Link
What are some alternatives?
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