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pip install vitables vitables xxxx.h5 HDFVIEW

deblur first version:

  1. blur input
  2. eventloss like eventac or e2vid better method: read both in one train loop, get a hrbrid loss to consider both blur and event better method have finished, colmap dataset,with images(e2vid or other event to gray) and blurryImages

存在两个问题:1位姿能否和真实对上,要求imgaes两次训练读同一个 2 仿真event与真实event能否对上,判断方式如下: 如果e2vid选则前一个作为真值,那么eventloss的仿真做差要变成i+1 - i 如果e2vid选当前作为真值,那么eventloss的仿真做差要变成i - (i-1) 可是火车又是i+1-i,真玄学.指标显示,i+1-i好像才是对的。。。。相信指标,眼睛真会骗人

eventloss时间不应该过长,大部分时间不要启用虽然能训练很多轮,但似乎后边变化不大了 让C偏大,效果显著的好 最终训练时,崩溃的那几帧要排除掉,效果肯定更好!很简单,如果index =xx, index =1 写论文时colmap模块要改成标定模块 目前的做法会让其棱角更分母,如有不妥,只进行最后一步训练即可 测试时同时把5,...等图一起输出了

真实数据应该也能做好,之前做不好还是因为位姿不对,rgb和event是不对应的,用rgb标的位姿给event用,问题比较大,用e2vid标还标不好,因此blender数据集很重要 两步式不仅能使其更容易找到最优点,而且速度也很快,不然即使weight给0,也很拖慢计算速度 训练可以统一记作8000+2000,事实上微调时2000后边也不咋变了 基本做完了,可以记录ssim,psnr,LPIPS了。至于怎样微调更好,就要根据实际表现了,训练一次不到7分钟,应该还好办 3000+1000 is better

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