Lightweight-human-pose-estimation.pytorch: train No.3

I ran into this problem during training, and I commented out this line of code in train.py(#evaluate(val_labels, val_output_name, val_images_folder, net)).Is this line of code commented out, so there is no result? Do you have any solutions?

Hello,I have seen your previous reply. Now I am making 19 key points and have modified the code. The data sets I used are from Val2017 and Train2017 downloaded from the official website of Coco. Do you mean that I need to re-label the data? Isn't the data set downloaded from the official website of Coco already marked?

Hi! First of all check if provided pre-trained model works for validation. This will say if validation works. Then check output file with prediction results from your checkpoint. If it is empty, then such error may occur. So, if it is empty, try to visualize the avg_heatmaps to see if anything was detected. Loss curves are here: #10, yours look reasonable.

Hi! First of all check if provided pre-trained model works for validation. This will say if validation works. Then check output file with prediction results from your checkpoint. If it is empty, then such error may occur. So, if it is empty, try to visualize the avg_heatmaps to see if anything was detected. Loss curves are here: #10, yours look reasonable.

Thank you for your prompt reply. Thank you for your advice. I'll have a try. I also want to ask you two question. Firstly, the key points I want to set now is 20, and I want to add a waist node. I would like to ask you if I can directly use the COCO data set? However, the COCO data set only annotates 18 key points. If I want to set 20 key points, do I need to annotate the COCO data set again?
Secondly,the key points can be detected if only the third step is carried out,?or the key points and connections can be detected only after the complete training steps have been carried out?
Looking forward to your reply! Thank you!

Yes, you should label somehow waist for the persons, either manually or compute from existing ones. Keypoints can be detected after the third step (you see, there is validation step during training, so after some initial iterations, e.g. 5000, keypoints are detected, try to visualize the heatmaps).

Yes, you should label somehow waist for the persons, either manually or compute from existing ones. Keypoints can be detected after the third step (you see, there is validation step during training, so after some initial iterations, e.g. 5000, keypoints are detected, try to visualize the heatmaps).
Thank you for your prompt reply. I get it!