Quantized tflite models for ailia TFLite Runtime

ailia TFLite Runtime is a TensorFlow Lite compatible inference engine. Written in C99, it supports inference in Non-OS and RTOS. It also supports high-speed inference using Intel MKL on a PC. In the Android environment, we provide a Unity Package, which also supports NPU inference using NNAPI.

Run the following command. The Python version is compatible with Windows, macOS, and Linux. It is also planned to support Arm Linux in the future.

pip3 install ailia_tflite

	Model	Reference	Exported From	Supported Ailia Version
	u2net	U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection	TensorFlow	1.1.0

	Model	Reference	Exported From	Supported Ailia Version
	Midas	Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer	Pytorch	1.1.7

	Model	Reference	Exported From	Supported Ailia Version
	BlazeFace	PINTO_model_zoo	TensorFlow	1.0.0

	Model	Reference	Exported From	Supported Ailia Version
	Face Mesh	PINTO_model_zoo	TensorFlow	1.0.0
	face_classification	Real-time face detection and emotion/gender classification	TensorFlow	1.1.1

	Model	Reference	Exported From	Supported Ailia Version
	Blaze Hand	PINTO_model_zoo	TensorFlow	1.0.0

	Model	Reference	Exported From	Supported Ailia Version
	MobileNet	MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications	Keras	1.0.0
	MobileNetV2	MobileNetV2: Inverted Residuals and Linear Bottlenecks	Keras	1.0.0
	ResNet50	tf.keras.applications.resnet50.ResNet50	Keras	1.0.0
	EfficientnetLite	efficientnet-lite-keras	Keras	1.0.0
	SqueezeNet	keras_squeezenet2	Keras	1.0.0
	vgg16	VGG16 - Torchvision	Pytorch	1.1.7 for int8, 1.1.9 for float
	googlenet	GOOGLENET	Pytorch	1.1.10

	Model	Reference	Exported From	Supported Ailia Version
	DeepLabv3+	PINTO_model_zoo	TensorFlow	1.0.0
	HRNet-Semantic-Segmentation	HRNet-Semantic-Segmentation	TensorFlow	1.1.0

	Model	Reference	Exported From	Supported Ailia Version
	YOLOv3 tiny	tensorflow-yolov4-tflite	TensorFlow	1.0.0
	YOLOX	YOLOX	Pytorch	1.1.1
	EfficientDetLite	PINTO_model_zoo	TensorFlow	1.1.3

	Model	Reference	Exported From	Supported Ailia Version
	pose_resnet	Simple Baselines for Human Pose Estimation and Tracking	Pytorch	1.1.7 for int8, 1.1.9 for float

	Model	Reference	Exported From	Supported Ailia Version
	ESPCN	Image Super-Resolution using an Efficient Sub-Pixel CNN	TensorFlow	1.1.0
	srresnet	Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network	Pytorch	1.1.10

You can benchmark with the -b option. You can use the official TensorFlow Lite with the --tflite option.

You can use cui launchar.

python3 launchar.py

See NXP