guoqincode / Open-AnimateAnyone

Unofficial Implementation of Animate Anyone
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I got decent results, but some of the samples were in the wrong color #76

Closed luyvlei closed 7 months ago

luyvlei commented 8 months ago

Hello, @guoqincode! The samples in the test set worked fine, but with pure black clothes, I often got black and white results. Have you ever run into similar problems. a051f8f4-8433-4bc0-9c66-2d9c79528b9e ac028ea6-2cdd-45d2-8ed1-3752bd5b71b0

Here is the reference image, could you run your ckpt to see if the color is normal? ref_final2

MrYYYYYYYYYYY commented 8 months ago

video 1 looks pretty good 👍 !how many steps you trained the stage 1 ? I trained 13000 steps but still can‘t control the pose :( .

saidkaban commented 8 months ago

Hello @luyvlei, the results are indeed pretty decent. Could you please share what steps do I need to follow to get such results? Thanks so much in advance.

guoqincode commented 8 months ago

You can retrain the last layer of the animatediff from zero initialization.

luyvlei commented 8 months ago

You can retrain the last layer of the animatediff from zero initialization.

@guoqincode But in stage1, the color is already wrong. In stage one the color will random whitening but in stage two, it almost be pure white. I have tried to zero init the proj_out layer parameters of animatediff ckpt and got the result above, still not satisfactory. Here is my wechat number 15365532260, cloud you add me? I want to communicate with you.

luyvlei commented 8 months ago

Hello @luyvlei, the results are indeed pretty decent. Could you please share what steps do I need to follow to get such results? Thanks so much in advance.

Just following the paper, 30000step for stage1(bs64) and 10000step for stage2(bs4) is enough.

luyvlei commented 8 months ago

video 1 looks pretty good 👍 !how many steps you trained the stage 1 ? I trained 13000 steps but still can‘t control the pose :( .

I have a version of my own implementation that poseguider will work in about 2000 steps, but it does not seems to be much different from this code's implementation

hkunzhe commented 7 months ago

Hello @luyvlei, the results are indeed pretty decent. Could you please share what steps do I need to follow to get such results? Thanks so much in advance.

Just following the paper, 30000step for stage1(bs64) and 10000step for stage2(bs4) is enough.

Did you use the mixed precision training?

luyvlei commented 7 months ago

Hello @luyvlei, the results are indeed pretty decent. Could you please share what steps do I need to follow to get such results? Thanks so much in advance.

Just following the paper, 30000step for stage1(bs64) and 10000step for stage2(bs4) is enough.

Did you use the mixed precision training?

Yes, fp16

MrYYYYYYYYYYY commented 7 months ago

video 1 looks pretty good 👍 !how many steps you trained the stage 1 ? I trained 13000 steps but still can‘t control the pose :( .

I have a version of my own implementation that poseguider will work in about 2000 steps, but it does not seems to be much different from this code's implementation

thanks for reply,using hack training can solve my problem~

LeonJoe13 commented 7 months ago

video 1 looks pretty good 👍 !how many steps you trained the stage 1 ? I trained 13000 steps but still can‘t control the pose :( .

I have a version of my own implementation that poseguider will work in about 2000 steps, but it does not seems to be much different from this code's implementation

thanks for reply,using hack training can solve my problem~

hello sir, could you tell me how to run stage 1 inference? I used train_hack.py to train, and I modifed like this:

from models.PoseGuider import PoseGuider

from hack_poseguider import Hack_PoseGuider as PoseGuider

from diffusers.models import UNet2DConditionModel

from hack_unet2d import Hack_UNet2DConditionModel as UNet2DConditionModel thank you a lot!

// I figured out, I forget to change the poseguider channel to 320

LeonJoe13 commented 7 months ago

Hello, @guoqincode! The samples in the test set worked fine, but with pure black clothes, I often got black and white results. Have you ever run into similar problems. a051f8f4-8433-4bc0-9c66-2d9c79528b9e a051f8f4-8433-4bc0-9c66-2d9c79528b9e ac028ea6-2cdd-45d2-8ed1-3752bd5b71b0 ac028ea6-2cdd-45d2-8ed1-3752bd5b71b0

Here is the reference image, could you run your ckpt to see if the color is normal? ref_final2

hi sir, could you tell me do you change any part of the train_hack.py? I trained 1 stage in 8 A100 with 30000 steps, but the face is terrible, could you tell me some details about your training?

luyvlei commented 7 months ago

hi sir, could you tell me do you change any part of the train_hack.py? I trained 1 stage in 8 A100 with 30000 steps, but the face is terrible, could you tell me some details about your training?

By increasing the resolution and change the vae, the face can be improved

chlinfeng1997 commented 7 months ago

hi sir, could you tell me do you change any part of the train_hack.py? I trained 1 stage in 8 A100 with 30000 steps, but the face is terrible, could you tell me some details about your training?

By increasing the resolution and change the vae, the face can be improved

Hello, I would like to ask specifically, does increasing the resolution mean increasing the resolution during training or during inference?