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I'm working with an object detection model and I would like to use TensorFlow version of SSD-MobileNet. I saw the Caffe version and tried to retrain it, but the results were very poor. After training for 100 hours the mAP was still less than 0.03. I tried to tweak the learning rate and aspect ratios to better suit my dataset (my objects are mostly squares), but that didn't help. Then I switched to TensorFlow Object Detection API to see if there is a problem in my dataset. However, after training for just 6 hours I already got a mAP of 0.5. I also noticed that the TensorFlow version is also much faster on my machine; (0.6 sec / iteration) vs (2 sec / iteration) on caffe. So the TensorFlow version works much better and I'd like to use that instead if possible.
Is there any way to convert the model to NCS? And if direct conversion from TensorFlow to NCS is not possible, would it be possible to convert the model to Caffe format and then to NCS? Or could I just copy the TensorFlow model weights to the equivalent Caffe model?