efficientdet

EfficientDet

Input

(Image from https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch/blob/master/test/img.png)

Output

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 efficientdet.py

If you want to specify the input image, put the image path after the --input option.
You can use --savepath option to change the name of the output file to save.

$ python3 efficientdet.py --input IMAGE_PATH --savepath SAVE_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 efficientdet.py --video VIDEO_PATH

By adding the model name after the --model option, you can specify the model.
The model name is selected from 'd0', 'd1', 'd2', 'd3', 'd4', 'd5', 'd6', 'd0hd', 'd1hd', 'd2hd', 'd3hd', 'd4hd'.

$ python3 efficientdet.py --model d0hd

Reference

• Yet Another EfficientDet Pytorch Convert ONNX TVM
• EfficientDet
• EfficientDet: Scalable and Efficient Object Detection, in PyTorch
• Yet Another EfficientDet Pytorch

Framework

Pytorch

Model Format

ONNX opset=11

Netron

efficientdet-d0.onnx.prototxt efficientdet-d1.onnx.prototxt efficientdet-d2.onnx.prototxt efficientdet-d3.onnx.prototxt efficientdet-d4.onnx.prototxt efficientdet-d5.onnx.prototxt efficientdet-d6.onnx.prototxt efficientdet-d0hd.onnx.prototxt efficientdet-d1hd.onnx.prototxt efficientdet-d2hd.onnx.prototxt efficientdet-d3hd.onnx.prototxt efficientdet-d4hd.onnx.prototxt