HRNet about deep-learning-for-image-processing HOT 3 OPEN

老师，我这里对我的数据和标签进行了调整，都弄成了384x288的尺寸大小，但是在评估的时候使用coco的标准，coco2017人体关键点检测是17个，我这里不是17,只有8个，我在coco_eval里面做了调整还是出现这个问题，请问老师有何高见 Traceback (most recent call last):
File "/media/cmf/EEA2072AA206F73D/VOS_related_Project/KeyPoint/HRNet/train_multi_GPU.py", line 272, in
main(args)
File "/media/cmf/EEA2072AA206F73D/VOS_related_Project/KeyPoint/HRNet/train_multi_GPU.py", line 164, in main
key_info = utils.evaluate(model, data_loader_test, device=device,
File "/home/cmf/anaconda3/envs/xmem-repro/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, kwargs)
File "/media/cmf/EEA2072AA206F73D/VOS_related_Project/KeyPoint/HRNet/train_utils/train_eval_utils.py", line 115, in evaluate
coco_info = key_metric.evaluate()
File "/media/cmf/EEA2072AA206F73D/VOS_related_Project/KeyPoint/HRNet/train_utils/coco_eval.py", line 128, in evaluate
self.coco_evaluator.evaluate()
File "/home/cmf/anaconda3/envs/xmem-repro/lib/python3.9/site-packages/pycocotools/cocoeval.py", line 148, in evaluate
self.ious = {(imgId, catId): computeIoU(imgId, catId)
File "/home/cmf/anaconda3/envs/xmem-repro/lib/python3.9/site-packages/pycocotools/cocoeval.py", line 148, in
self.ious = {(imgId, catId): computeIoU(imgId, catId)
File "/home/cmf/anaconda3/envs/xmem-repro/lib/python3.9/site-packages/pycocotools/cocoeval.py", line 229, in computeOks
e = (dx2 + dy**2) / vars / (gt['area']+np.spacing(1)) / 2
ValueError: operands could not be broadcast together with shapes (8,) (17,)

from deep-learning-for-image-processing.

不支持动态分辨率哦，你可以看下train.py文件，--fixed-size写死的是256x192，你可以根据你自己的数据集修改下--fixed-size

from deep-learning-for-image-processing.

老师您好，这个问题我也注意到了，但我还有个问题，就是说如果我数据集分辨率是1280x720的话，我对应的关键点标注信息也是对应1280x720的，如果我对数据集原始图片进行resize变成384x288或者256x192那么我的标签如何处理，或者我在数据增强那里，对输入到网络的图片大小进行resize那么标签应该如何处理！感谢老师！恳请给个意见

from deep-learning-for-image-processing.