I have made a model to classify different categories of ships(yacht,catamaran,rubber boat) in Python and i hit a 70% accuracy in training so now i have my weights.hdf5 file.Now i need to object detection the images i used with boundaries boxes and rectangles to find the different ships in each image, like a Yolo pretrained model but with my own weights that i trained for classes,so that the detector is going to find the ship in the image and display is's label with is's probability, etc yacht(70.0% )rubber boat(65.0%)... Can anyone with some more experience drive me to achieving this task?
You should be able to use
keras.models.load_model to load the
hdf5 model file. See also the tensorflow documentation.
# saving the model model = ... # Get model (Sequential, Functional Model, or Model subclass) model.save('weights.hdf5') # loading the model from tensorflow import keras model = keras.models.load_model('weights.hdf5')