Ailia input shape : (1,3,224,224)
Range : [-1.0, 1.0]
+ idx=0
category=409 [ analog clock ]
prob=9.720746994018555
+ idx=1
category=892 [ wall clock ]
prob=6.404201030731201
+ idx=2
category=426 [ barometer ]
prob=4.357946395874023
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 efficientnet.py
If you want to specify the model, put b0 or b7 after the --model option.
you can select efficientnet-b0 or efficientnet-b7.
efficientnet-b0 is faster than efficientnet-b7 but lower precision.
$ python3 efficientnet.py --model b0
or
$ python3 efficientnet.py --model b7
If you want to specify the input image, put the image path after the --input option.
$ python3 efficientnet.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 efficientnet.py --video VIDEO_PATH
A PyTorch implementation of EfficientNet
ONNX opset = 10
Pytorch 1.1.0