What should be the output_names of the custom model be?
emotion_labels = get_labels('fer2013')
emotion_model_path = 'trained_models/emotion_models/fer2013_mini_XCEPTION.102-0.66.hdf5'
emotion_classifier = load_model(emotion_model_path, compile=False)
'emotions': {
'model': emotion_classifier ,
'arg_scope': emotion_arg_scope, # what should this be changed to
'num_classes': 7,
'input_name': 'input', # what should this be changed to
'output_names': ['InceptionResnetV2/Logits/Logits/BiasAdd'],, # what should this be changed to
'input_width': 64,
'input_height': 64,
'input_channels': 1,
'preprocess_fn': preprocess_emotion, #preprocessing
'postprocess_fn': postprocess_emotion, #postprocessing
'checkpoint_filename': CHECKPOINT_DIR + 'emotions.ckpt',
'frozen_graph_filename': FROZEN_GRAPHS_DIR + 'emotions.pb',
'trt_convert_status': "works", # what should this be changed to
'plan_filename': PLAN_DIR + 'inception_resnet_v2.plan' # what should this be changed to
}}
Trying the first step tf_to_trt_image_classification/scripts/models_to_frozen_graphs.py
Please guide on the second part of this question Trying to convert emotion detection into TensorRT
What should be the
output_names
of the custom model be?