MobilenetV3SSDLite-tfkeras

tensorflow keras implement of mobilenet v3 ssdlite, same structure as tensorflow model. some utils for converting ckpt model to keras model,and keras model to pb model.

Environments

• python 3.6
• tensorflow 1.14
• cuda 10
• cudnn 7.6.5
• pycocotools
• tensorflow object detection api

Introductions

overall

• tf ckpt model and keras model have some difference in preprocess phase, model details and anchor settings.
• In this repo, we don't use variance(anchor setting parameter).

model structure

• This model is build by tf.keras.models
• model files in ./models

convert tf ckpt to keras models

• Origin ckpt file's inference file in ./experiments/tfckpt_inference.py
• This repo can convert tf ckpt models to tfkeras h5 models, main file in ./model_transformation_utils/load_weights_tf2keras.py
• Other files in ./model_transformation_utils/ are my other tries , can be understanded by their names.
• keras to pb is work but keras to tflite is not work, because some ops in decodelayer are not supported yet in tflite.

converted model's inference and test

• Code for eval converted model's performance

• At first, use dfsmodel function(line 104) to load ckpt to keras model's weights, otherwise it will not be loaded successfully.

• After first loading phase, you can use save_weights function to save now weights for this keras models.

• Then you can use load_weights to load now weights for inference/test keras models.

• Infer several images by ./tfckpt2keras_inference.py

• Eval performance by ./tfckpt2keras_test.py

keras model's train,inference and test

• You can also use this repo to train your own keras models.
• This repo can be trained by ./tfkeras_train.py
• This repo can be inferenced by ./tfkeras_inference.py
• This repo can be evaled by ./tfkeras_test.py

reference

[1] https://github.com/tensorflow/models/tree/master/research/object_detection

[2] https://github.com/markshih91/mobilenet_v2_ssdlite_keras

[3] https://github.com/Bisonai/mobilenetv3-tensorflow