Open zeng-zr opened 9 months ago
I’m using 100 labeled frames from my videos(4 cameras, duplicated 1 to match weights for 5cam) to finetune a 5cam dannce MAX model following these advice: (https://github.com/spoonsso/dannce/issues/62#issuecomment-904950551) but the predict results are bad.
new_n_channels_out: 14 batch_size: 4 epochs: 600 net_type: AVG train_mode: new_n_channels_out: 14 batch_size: 4 epochs: 600 net_type: AVG train_mode: 'finetune' #dannce_finetune_weights: ./DANNCE/weights/weights.rat.AVG.MONO/ # doesn't work due to layers mismatch? try duplicating views manully dannce_finetune_weights: ./DANNCE/weights/weights.rat.AVG.MONO.5cams/ # During prediction, will look for the last epoch weights saved to ./DANNCE/train_results/. To load in a different weights file, add the path here # Note that this must be a FULL MODEL file, not just weights. dannce_predict_model: './DANNCE/train_results/AVG_5cams/fullmodel_weights/fullmodel_end.hdf5' predict_mode: torch exp: - label3d_file: '1_0223_5cams_dannce.mat' com_file: './COM/predict_results/train_3cams/com3d.mat' #for dannce training - label3d_file: '2_0221_5cams_dannce.mat' com_file: './COM/predict_results/train_3cams/com3d.mat' # used 9000frames vid com_file: './COM/predict_results/train_3cams/com3d.mat' num_validation_per_exp: 0 augment_brightness: True n_rand_views: None gpu_id: "2" n_views: 5 comthresh: 0.2 loss: mask_nan_l1_loss crop_height: [0, 2048] crop_width: [0, 2432] vol_size: 150 nvox: 96 max_num_samples: 1500 dannce_finetune_weights: ./DANNCE/weights/weights.rat.AVG.MONO.5cams/ dannce_predict_model: './DANNCE/train_results/AVG_5cams/fullmodel_weights/fullmodel_end.hdf5' predict_mode: torch exp: - label3d_file: '1_0223_5cams_dannce.mat' com_file: './COM/predict_results/train_3cams/com3d.mat' #for dannce training - label3d_file: '2_0221_5cams_dannce.mat' com_file: './COM/predict_results/train_3cams/com3d.mat' # used 9000frames video com_file: './COM/predict_results/train_3cams/com3d.mat' num_validation_per_exp: 0 augment_brightness: True n_rand_views: None n_views: 5 comthresh: 0.2 loss: mask_nan_l1_loss crop_height: [0, 2048] crop_width: [0, 2432] vol_size: 150 nvox: 96 max_num_samples: 1500 mono : True
training.csv
I label 1 frame every 30 frames , and the above picture is the predict result of the first frame of the video, which I also labeled. Should I shorten the label frame interval to get better result?
I’m using 100 labeled frames from my videos(4 cameras, duplicated 1 to match weights for 5cam) to finetune a 5cam dannce MAX model following these advice: (https://github.com/spoonsso/dannce/issues/62#issuecomment-904950551) but the predict results are bad.
I label 1 frame every 30 frames , and the above picture is the predict result of the first frame of the video, which I also labeled. Should I shorten the label frame interval to get better result?