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medsam_lite-0424's Introduction

  • ๐Ÿ‘‹ Hi, Iโ€™m @mykcs

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colabไฝฟ็”จ ๆœๅŠกๅ™จไฝฟ็”จ

gradio ไฝฟ็”จhugging faceๆ‰˜็ฎก

่ฎก็ฎ—ๆœบๅ›พๅฝขๅญฆ

WWDC ๅญฆ็”ŸๆŒ‘ๆˆ˜

  • ๐ŸŒฑ Iโ€™m currently learning ...

cv ๅ›พๅƒๅˆ†ๅ‰ฒ Mamba

kaggle

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[email protected]

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medsam_lite-0424's Issues

RuntimeError:An attempt has been made to start a new process before the 

RuntimeError: 
        An attempt has been made to start a new process before the
        current process has finished its bootstrapping phase.
 
        This probably means that you are not using fork to start your
        child processes and you have forgotten to use the proper idiom
        in the main module:
 
            if __name__ == '__main__':
                freeze_support()
                ...
 
        The "freeze_support()" line can be omitted if the program
        is not going to be frozen to produce an executable.

MedSAM Lite size: 9791300 Finetuning with pretrained weights lite_medsam.pth - ๆ‰“ๅฐไบ†10ๆฌก

log

/Users/myk/anaconda3/envs/env-MedSAM-0422/bin/python /Users/myk/PyPjcts/MedSAM_lite-0424/train_mps-1.py 
Finetuning with pretrained weights lite_medsam.pth
MedSAM Lite size: 9791300
wandb: Currently logged in as: mykcs (team-mykcs). Use `wandb login --relogin` to force relogin
wandb: Tracking run with wandb version 0.16.6
wandb: Run data is saved locally in /Users/myk/PyPjcts/MedSAM_lite-0424/wandb/run-20240424_023431-1m08ghs8
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run run-0424-2
wandb: โญ๏ธ View project at https://wandb.ai/team-mykcs/MedSAM-lite
wandb: ๐Ÿš€ View run at https://wandb.ai/team-mykcs/MedSAM-lite/runs/1m08ghs8
  0%|          | 0/906 [00:00<?, ?it/s]Finetuning with pretrained weights lite_medsam.pth
MedSAM Lite size: 9791300
Finetuning with pretrained weights lite_medsam.pth
MedSAM Lite size: 9791300
Finetuning with pretrained weights lite_medsam.pth
MedSAM Lite size: 9791300
Finetuning with pretrained weights lite_medsam.pth
MedSAM Lite size: 9791300
Finetuning with pretrained weights lite_medsam.pth
MedSAM Lite size: 9791300
Finetuning with pretrained weights lite_medsam.pth
MedSAM Lite size: 9791300
Finetuning with pretrained weights lite_medsam.pth
MedSAM Lite size: 9791300
Finetuning with pretrained weights lite_medsam.pth
MedSAM Lite size: 9791300
Epoch 1 at 2024-04-24 02:47:22, loss: 0.0689: 100%|โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆ| 906/906 [13:27<00:00,  1.12it/s]
Traceback (most recent call last):
  File "/Users/myk/PyPjcts/MedSAM_lite-0424/train_mps-1.py", line 535, in <module>
    main()
  File "/Users/myk/PyPjcts/MedSAM_lite-0424/train_mps-1.py", line 515, in main
    "best_loss": best_loss,
UnboundLocalError: local variable 'best_loss' referenced before assignment
wandb: 
wandb: Run history:
wandb:   ce_loss_weight โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–
wandb: epoch_loss[step] โ–„โ–‚โ–โ–ƒโ–โ–„โ–‚โ–ˆโ–โ–„โ–โ–‚โ–‚โ–†โ–ƒโ–„โ–…โ–‚โ–ƒโ–ƒโ–‚โ–ƒโ–ƒโ–„โ–ƒโ–โ–โ–‚โ–‚โ–ƒโ–‚โ–‚โ–‡โ–†โ–„โ–„โ–„โ–„โ–…โ–‚
wandb:           iou_gt โ–
wandb:  iou_loss_weight โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–
wandb:             l_ce โ–‚โ–‚โ–‚โ–โ–โ–โ–‚โ–‚โ–โ–ƒโ–โ–โ–‚โ–ƒโ–ƒโ–โ–ƒโ–โ–ƒโ–‚โ–‚โ–โ–โ–„โ–โ–โ–โ–‚โ–‚โ–โ–โ–‚โ–ˆโ–โ–โ–‚โ–โ–‚โ–ƒโ–…
wandb:            l_iou โ–‚โ–‚โ–‚โ–โ–โ–‚โ–โ–…โ–โ–‚โ–โ–โ–โ–ƒโ–‚โ–ƒโ–‚โ–โ–โ–ƒโ–โ–‚โ–โ–โ–โ–โ–โ–‚โ–‚โ–โ–‚โ–โ–ˆโ–‚โ–‚โ–โ–ƒโ–‚โ–ƒโ–
wandb:            l_seg โ–„โ–‚โ–โ–ƒโ–โ–„โ–‚โ–ˆโ–โ–„โ–โ–‚โ–‚โ–†โ–ƒโ–„โ–…โ–‚โ–ƒโ–ƒโ–‚โ–ƒโ–„โ–„โ–„โ–โ–โ–‚โ–‚โ–ƒโ–‚โ–‚โ–…โ–†โ–„โ–„โ–„โ–„โ–…โ–‚
wandb:             loss โ–„โ–‚โ–โ–ƒโ–โ–„โ–‚โ–ˆโ–โ–„โ–โ–‚โ–‚โ–†โ–ƒโ–„โ–…โ–‚โ–ƒโ–ƒโ–‚โ–ƒโ–ƒโ–„โ–ƒโ–โ–โ–‚โ–‚โ–ƒโ–‚โ–‚โ–‡โ–†โ–„โ–„โ–„โ–„โ–…โ–‚
wandb:      loss.item() โ–„โ–‚โ–โ–ƒโ–โ–„โ–‚โ–ˆโ–โ–„โ–โ–‚โ–‚โ–†โ–ƒโ–„โ–…โ–‚โ–ƒโ–ƒโ–‚โ–ƒโ–ƒโ–„โ–ƒโ–โ–โ–‚โ–‚โ–ƒโ–‚โ–‚โ–‡โ–†โ–„โ–„โ–„โ–„โ–…โ–‚
wandb:        mask_loss โ–„โ–‚โ–โ–ƒโ–โ–„โ–‚โ–ˆโ–โ–„โ–โ–‚โ–‚โ–†โ–ƒโ–„โ–…โ–‚โ–ƒโ–ƒโ–‚โ–ƒโ–„โ–„โ–„โ–โ–โ–‚โ–‚โ–ƒโ–‚โ–‚โ–†โ–†โ–„โ–„โ–„โ–„โ–…โ–‚
wandb:  seg_loss_weight โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–โ–
wandb: 
wandb: Run summary:
wandb:   ce_loss_weight 1.0
wandb: epoch_loss[step] 0.0689
wandb:           iou_gt 0.84615
wandb:  iou_loss_weight 1.0
wandb:             l_ce 0.00062
wandb:            l_iou 0.00346
wandb:            l_seg 0.06482
wandb:             loss 0.0689
wandb:      loss.item() 0.0689
wandb:        mask_loss 0.06544
wandb:  seg_loss_weight 1.0
wandb: 
wandb: ๐Ÿš€ View run run-0424-2 at: https://wandb.ai/team-mykcs/MedSAM-lite/runs/1m08ghs8
wandb: โญ๏ธ View project at: https://wandb.ai/team-mykcs/MedSAM-lite
wandb: Synced 6 W&B file(s), 0 media file(s), 2 artifact file(s) and 0 other file(s)
wandb: Find logs at: ./wandb/run-20240424_023431-1m08ghs8/logs

่ฟ›็จ‹ๅทฒ็ป“ๆŸ๏ผŒ้€€ๅ‡บไปฃ็ ไธบ 1

to jupyter notebook

ๅ…ˆๆŠŠ from segment_anything.modeling import MaskDecoder, PromptEncoder, TwoWayTransformer
่ฟ™็ฑป่ฏญๅฅๆ”นๆˆipynb้‡Œ็š„็ฑป

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image

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