efficientnetv2

efficientnetv2

Input

Shape : (1,224,224,3)

Output

class_count=3
+ idx=0
  category=409[analog clock ]
  prob=9.556556701660156
+ idx=1
  category=892[wall clock ]
  prob=7.525008201599121
+ idx=2
  category=426[barometer ]
  prob=4.037744522094727

Usage

Automatically downloads the onnx and prototxt files on the first run. It is necessary to be connected to the Internet while downloading.

For the sample image,

$ python3 efficientnetv2.py

If you want to specify the input image, put the image path after the --input option.

$ python3 efficientnetv2.py --input IMAGE_PATH

By adding the --video option, you can input the video.
If you pass 0 as an argument to VIDEO_PATH, you can use the webcam input instead of the video file.

$ python3 efficientnetv2.py --video VIDEO_PATH

The default setting is to use the optimized model and weights, but you can also switch to the normal model by using the --normal option.

Reference

EfficientNetV2

Model Format

ONNX opset = 11

Framework

Tensorflow

Netron

efficientnetv2-b0.prototxt

efficientnetv2-b1.prototxt

efficientnetv2-b2.prototxt

efficientnetv2-b3.prototxt