A Question about fine-tuning

[FengWei2000]

I'm focusing on the fine-tuning work of img2pose。I refer to the steps you suggested on issues in github to fine tuned based on the model“img2pose_v1.pth”you provided. However，the head pose estimation were worse after the fine-tuning than before. my steps are as follows:
1、use the 300wlp annotations "300W_LP_annotations_train.txt" you provided in github and dowload 300wlp datasets on the official website.
2、use the json_loader_300wlp.py in your codes to create "300W_LP_annotations_train.lmdb", "300W_LP_annotations_train_pose_mean.npy" and "300W_LP_annotations_train_pose_stddev.npy" by execute "convert_json_list_to_lmdb.py"
3、in models.py change rpn_batch_size_per_image to 2 (proposals), and box_detections_per_img to 4 (head samples)。
4、 use "300W_LP_annotations_train.lmdb" to train without augmentations, use "300W_LP_annotations_train_pose_mean.npy" and "300W_LP_annotations_train_pose_stddev.npy" as pose_mean and pose_stddev.
5、 lr = 0.001 for 2 epochs
6、Other parameters are set as follows:      
"--pose_mean", "./datasets/lmdb/WIDER_train_annotations_pose_mean.npy",
                "--pose_stddev", "./datasets/lmdb/WIDER_train_annotations_pose_stddev.npy",
                "--pretrained_path", "./models/img2pose_v1.pth",
                "--workspace", "./workspace/",
                "--train_source", "./datasets/lmdb/300W_LP_annotations_train.lmdb",
                "--prefix", "trial_1",
                "--batch_size", "2",
                "--max_size", "1400",

however, after 2 epochs，the head pose estimation were worse , and the MAE in aflw2000 is "Yaw: 20.656 Pitch: 17.178 Roll: 13.957 MAE: 17.264; H. Trans.: 0.179 V. Trans.: 0.363 Scale: 1.465 MAE: 0.669".
I don't know which step went wrong. I would appreciate it if you could help me.

[vitoralbiero]

@FengWei2000

Sorry for the late reply. Could you please try the same thing you did, but instead of using pose mean and stddev from 300W-LP, use the same one as you used for training (WIDER)?

Let me know what the outcome of that is.

[vitoralbiero]

Closing this issue, if you still have problems, please re-open it.