3D关键点坐标

[ccchen091]

您好，我想请问一下如何通过你这个模型将检测到的3D关键点坐标保存下来呢.

[ChanglongJiangGit]

您好！感谢您的关注！
如果您需要保存手部的2.5D坐标，那只需要保存'model.py'中的‘pred_keypoints’即可。
由于我们的模型是预测的2.5D坐标，没有预测根节点的绝对坐标或是二者的绝对距离，所以无法得到两手准确的3D坐标。
希望对您有帮助！

[ccchen091]

非常感谢您的回复！ 我还想再问一下您这个2.5D坐标是世界坐标吗？ 同时我还有一个疑惑，就是您这个工作中用的是interhand2.6M数据集，其中的内外参是interhand2.6M数据集给出的吗？

[ChanglongJiangGit]

1、在'model.py'中的‘pred_keypoints’是在图像坐标系下的2.5D坐标，这个参数会反传回dataset.py中进行evaluation，在这个函数中你可以看到跟dataloader的get_item完全相逆的操作，也就是将img坐标系转换到相机坐标系。‘pred_joint_coord_cam’即为相机坐标系下的预测结果，我们也是在这个结果下进行的测试。如果想要世界坐标系下的预测结果，只需要在这个结果的基础上进行cam2world的转换即可。
2、是的，interhand数据集会给出相机的内外参，直接加载即可。

[ccchen091]

感谢您的帮助！祝您工作顺利！

[ccchen091]

您好！又来打扰您了，如果您那有nyu的数据集和hands2017数据集的话可以发给我吗？我在网上找的要不下载不了，要不就是找不到。谢谢！

[ChanglongJiangGit]

您好！
nyu的下载网址：https://jonathantompson.github.io/NYU_Hand_Pose_Dataset.htm#download
hands 2017的下载网址：http://icvl.ee.ic.ac.uk/hands17/challenge/

希望对您有帮助！

[ccchen091]

非常感谢您的回复！！！我自己也有找到这两个网页 要不进不去，要不就是下载不了（我开了梯子的）， 明天我自己再尝试一下！  非常您每次都能很快的回复我.希望您科研顺利! 525935379 ***@***.***  

…

------------------ 原始邮件 ------------------ 发件人: "ChanglongJiangGit/A2J-Transformer" ***@***.***>; 发送时间: 2024年3月5日(星期二) 晚上9:27 ***@***.***>; ***@***.******@***.***>; 主题: Re: [ChanglongJiangGit/A2J-Transformer] 3D关键点坐标 (Issue #21) 您好！ nyu的下载网址：https://jonathantompson.github.io/NYU_Hand_Pose_Dataset.htm#download hands 2017的下载网址：http://icvl.ee.ic.ac.uk/hands17/challenge/ image.png (view on web) 希望对您有帮助！ — Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you authored the thread.Message ID: ***@***.***>

[ccchen091]

您好，又来打扰您了，我想请问以下我在testNYU数据集的时候加载了A2J论文中给出的NYU.pth权重文件以后出现如下的问题，我搜索后发现应该是权重文件不匹配，所以我想来问一下您加载的model_41_wetD_0.0001_depFact_0.5_RegFact_3_rndShft_5.pth这个权重文件是不是就是NYU.pth，如果不是的话您这个权重文件去哪下载？谢谢！！！
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"DepthRegressionModel.bn4.weight", "DepthRegressionModel.bn4.bias", "DepthRegressionModel.bn4.running_mean", "DepthRegressionModel.bn4.running_var", "DepthRegressionModel.bn4.num_batches_tracked", "DepthRegressionModel.output.weight", "DepthRegressionModel.output.bias".

[ccchen091]

您好，我还想问一下我按照A2J的方式处理好NYU数据集以后，运行代码出现这个通道数不匹配问题：RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[4, 1, 176, 176] to have 3 channels, but got 1 channels instead
请问一下这个是为什么呢？并且您有什么好的建议吗？

[ChanglongJiangGit]

您好，model_41_wetD_0.0001_depFact_0.5_RegFact_3_rndShft_5.pth这个文件忘记公布了，稍后会上传，请您留意！您也可以先自行训练，训练出的结果应该不会有多少差别。

对于第二个问题，请问您现在解决了吗？没解决的话是否可以告诉我出现问题的代码位置？谢谢！

[ccchen091]

您好，model_41_wetD_0.0001_depFact_0.5_RegFact_3_rndShft_5.pth这个文件忘记公布了，稍后会上传，请您留意！您也可以先自行训练，训练出的结果应该不会有多少差别。

对于第二个问题，请问您现在解决了吗？没解决的话是否可以告诉我出现问题的代码位置？谢谢！

谢谢您的回复! 目前我们的任务没用上NYU数据集了，所以就没去解决这个问题。

[ccchen091]

您好！我想请问您一个问题，我在您的模型基础上训练了其他数据集（assemblyands），基本上就只改动了数据读取dataset，但是训练完以后，test的指标特别低，mpjpe94，请问一下这个是模型和数据集不适配吗？还是我有什么其他地方没注意的？

[zzsyid]

您好，我在NYU上训练时也出现RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[4, 1, 176, 176] to have 3 channels, but got 1 channels instead，具体问题出现在 File "/A2J-Transformer-main/model.py", line 285, in forward
features, pos = self.backbone(samples)File "/A2J-Transformer-main/dab_deformable_detr/backbone.py", line 90, in forward
xs = self.body(tensor_list.tensors)
是否是NYU数据集还需要额外的预处理或者更改backbone的维度参数呢

[ccchen091]

您好 我想再请教您一个问题 我将您的模型在Interhand2.6M数据集上训练好以后，我拍了一张相同视角的图片进去可视化看效果，按理说我自己拍的图片是不需要内外参数就可以得到不错的可视化效果的是吗？但是事实是我的可视化效果特别差，完全对应不上，请问一下这是什么问题呢？

[ChanglongJiangGit]

您好！我想请问您一个问题，我在您的模型基础上训练了其他数据集（assemblyands），基本上就只改动了数据读取dataset，但是训练完以后，test的指标特别低，mpjpe94，请问一下这个是模型和数据集不适配吗？还是我有什么其他地方没注意的？

这个具体不清楚，建议可视化检查一下代码和数据是否匹配等等

[ChanglongJiangGit]

您好 我想再请教您一个问题 我将您的模型在Interhand2.6M数据集上训练好以后，我拍了一张相同视角的图片进去可视化看效果，按理说我自己拍的图片是不需要内外参数就可以得到不错的可视化效果的是吗？但是事实是我的可视化效果特别差，完全对应不上，请问一下这是什么问题呢？

您好呀，请问一下您可视化的是模型输出的2.5D结果吗？如果模型输出的2.5D结果很差，那这个可能是由于拍摄的图片跟InterHand数据集差异过大导致的；如果模型预测的2.5D结果是正常的，但是转换到相机空间下不正常，那可能是由于相机参数有问题导致的。