支持范围

运行以下代码，查看Spike-Zoo支持的 模型、数据集 和 指标:

import spikezoo as sz
print(sz.METHODS)
print(sz.DATASETS)
print(sz.METRICS)

支持的模型:

Models	Source
tfp, tfi	Spike camera and its coding methods
spk2imgnet	Spk2ImgNet: Learning to Reconstruct Dynamic Scene from Continuous Spike Stream
wgse	Learning Temporal-Ordered Representation for Spike Streams Based on Discrete Wavelet Transforms
ssml	Self-Supervised Mutual Learning for Dynamic Scene Reconstruction of Spiking Camera
ssir	Spike Camera Image Reconstruction Using Deep Spiking Neural Networks
bsf	Boosting Spike Camera Image Reconstruction from a Perspective of Dealing with Spike Fluctuations
stir	Spatio-Temporal Interactive Learning for Efficient Image Reconstruction of Spiking Cameras
base, spikeclip	Rethinking High-speed Image Reconstruction Framework with Spike Camera

支持的数据集:

Datasets	Source
base	Spike-Zoo: A Toolbox for Spike-to-Image Reconstruction
reds_base	Spk2ImgNet: Learning to Reconstruct Dynamic Scene from Continuous Spike Stream
uhsr	Recognizing Ultra-High-Speed Moving Objects with Bio-Inspired Spike Camera
realworld	recVidarReal2019, momVidarReal2021 in SpikeCV (https://github.com/Zyj061/SpikeCV)
szdata	SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams

支持的指标:

Spike-Zoo目前支持的指标范围如下：

["psnr", "ssim", "lpips", "mse", "niqe", "brisque", "piqe", "liqe_mix", "clipiqa"]

• "psnr", "ssim", "mse" 指标计算的代码来源于 skimage 库。

• "lpips" 指标计算的代码来源于 lpips 库。

• "niqe", "brisque", "piqe", "liqe_mix", "clipiqa" 等非参考指标计算的代码来源于 pyiqa 库。本仓库通过直接调用 pyiqa 接口实现非参考指标计算，理论上该仓库支持的指标本仓库均支持。