Unofficial implementation of MobileNetV3 architecture described in paper Searching for MobileNetV3.
Unofficial implementation of MobileNetV3 architecture described in paper Searching for MobileNetV3.
This repository contains small and large MobileNetV3 architecture implemented using TensforFlow with tf.keras
API.
pip install -r requirements.txt
from mobilenetv3_factory import build_mobilenetv3
model = build_mobilenetv3(
"small",
input_shape=(224, 224, 3),
num_classes=1001,
width_multiplier=1.0,
)
from mobilenetv3_factory import build_mobilenetv3
model = build_mobilenetv3(
"large",
input_shape=(224, 224, 3),
num_classes=1001,
width_multiplier=1.0,
)
python train.py \
--model_type small \
--width_multiplier 1.0 \
--height 128 \
--width 128 \
--dataset cifar10 \
--lr 0.01 \
--optimizer rmsprop \
--train_batch_size 256 \
--valid_batch_size 256 \
--num_epoch 10 \
--logdir logdir
python train.py \
--model_type small \
--width_multiplier 1.0 \
--height 128 \
--width 128 \
--dataset mnist \
--lr 0.01 \
--optimizer rmsprop \
--train_batch_size 256 \
--valid_batch_size 256 \
--num_epoch 10 \
--logdir logdir
python evaluate.py \
--model_type small \
--width_multiplier 1.0 \
--height 128 \
--width 128 \
--dataset cifar10 \
--valid_batch_size 256 \
--model_path mobilenetv3_small_cifar10_10.h5
python evaluate.py \
--model_type small \
--width_multiplier 1.0 \
--height 128 \
--width 128 \
--dataset mnist \
--valid_batch_size 256 \
--model_path mobilenetv3_small_mnist_10.h5
Graph, training and evaluaion metrics are saved to TensorBoard event file uder directory specified with --logdir` argument during training. You can launch TensorBoard using following command.
tensorboard --logdir logdir