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Hello,
I trained my model with 2500 images (120000 iteration), but the trained model is **not** giving any predictions on running the code evalMPII.m. I have made the changes for weights.
I tried…
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hi, i want to know what is the matrix shape of pred_keypoints_mpii.mat when you submit to mpii.
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Hi, thanks for your work. However, I can't find the `mpii2coco.py` in `tool` , and I'm confused that how to get the `input pose json`. Would you mind telling me how to get them? Thanks for your time.
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直接调用训练好的duc_se.pth模型,显示的依然是coco数据集的17个关键点,但是opt里面是33,请问我应该怎么显示全部的33个关键点呢,或者只显示mpii的16个关键点,谢谢
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> ~/AttentionalPoolingAction-master/src$ python eval.py --cfg ../experiments/003_MPII_ResNet_withPoseAttention_pretrained.yaml
Traceback (most recent call last):
File "eval.py", line 28, in
…
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**# Thanks for you code! could you give me some advice?**
sun@sunwin:~$ cd /home/sun/pytorch-pose
sun@sunwin:~/pytorch-pose$ ln -s PATH_TO_MPII_IMAGES_DIR data/mpii/images
sun@sunwin:~/pytorch-po…
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在window下,正确配置数据路径,分别使用指令python train.py --dataset 'coco' , python train.py --dataset 'mpii' 进行训练,其他相关配置均正确,报错信息如下:
![4](https://user-images.githubusercontent.com/37854899/57353855-6bdd1a80-719c-11e9-…
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@mpskex
datagen_mpii.py的304行:if bounds[1] > width - 1:
其实应该是 if bounds[1] > height - 1:
不知道我的理解是否有误?
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when I run evaluation code, the output results:Multiple Object Tracking (MOT) metrics: [798/1987]
& MOTA & MOTA & MOTA & MOTA & MOTA & MOTA & MOTA & MOTA & MOTP & Prec …
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