I'm seeking the trained model of ResNet or ResNetXt for tensorflow.
Can anyone offer me a link to download it?
Thanks in advance.
Here it is. article, code, link to pre-trained model and the accuracy on ImageNet test set.
https://github.com/tensorflow/models/tree/master/research/slim#pre-trained-models
Related
How do I find more info on how the ssd_mobilenet_v1 tflite model on TFHub was trained?
Was it trained in such a way that made it easy to convert it to tflite by avoiding certain ops not supported by tflite? Or was it trained normally, and then converted using the tflite converter with TF Select and the tips on this github issue?
Also, does anyone know if there's an equivalent mobilenet tflite model trained on OpenImagesV6? If not, what's the best starting point for training one?
I am not sure about about the exact origin of the model, but looks like it does have TFLite-compatible ops. From my experience, the best place to start for TFLite-compatible SSD models is with the TF2 Detection Zoo. You can convert any of the SSD models using these instructions.
To train your own model, you can follow these instructions that leverage Google Cloud.
I am using deepLab to generate semantic segmentation masked images for a video in cityscapes datasets. So, I started with the pre-trained model xception65_cityscapes_trainfine provided on the modelzoo and trained it further on the dataset.
I am curious to know How I can start training it from scratch? and not end up just using the pre-trained model? could anyone suggest a direction on How I can achieve it?
Any contribution from the community will be helpful and appreciated.
Is there any version of the Inception model for ImageNet training coded without TensorFlow's Slim? I would like to make adjustments to the code but I'm not familiar with Slim...
Thank you!
I want to implements a faster-rcnn model using distributed tensorflow, But I have difficult to load a pretrained vgg model,How to do it? thanks
The TensorFlow tutorial on retraining inception is a good start to read. Then try to reproduce what it does starting from an already trained vgg model.
I have a resnet model trained in caffe. I want to try that with show_and_tell instead of inception_v3 image model.
What is the best way to convert the model form caffe to tensorflow
model ?
How would I go about switching the inception model to resnet
?
I'm not sure about the "best" way, but there are some tools that seem to address this, like https://github.com/ethereon/caffe-tensorflow