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Crowd Counting Code Framework (C3-Framework)

Input

Input

(Image from https://www.kaggle.com/tthien/shanghaitech)

Shape : (batch, 3, height, width)

Output (the desity maps)

Output

Shape : (batch, 1, height, width)

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 c-3-framework.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 c-3-framework.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 c-3-framework.py --video VIDEO_PATH

By adding the model name after the --model option, you can specify the model.
The model name is selected from 'alexnet', 'vgg', 'vgg_decoder', 'resnet50', 'resnet101', 'csrnet', 'sanet'.

$ python3 c-3-framework.py --model alexnet

Reference

Framework

Pytorch

Model Format

ONNX opset=11

Netron

AlexNet.onnx.prototxt

VGG.onnx.prototxt

VGG_DECODER.onnx.prototxt

ResNet50.onnx.prototxt

ResNet101.onnx.prototxt

CSRNet.onnx.prototxt

SANet.onnx.prototxt