Comments (12)
Great idea. We will try it, or the pull request from your side is also very welcomed.
from editanything.
This would be wild!
from editanything.
Great idea. We will try it, or the pull request from your side is also very welcomed.
Would totally contribute if I could, but I come from Swift/iOS world, and super limited with Python : /
from editanything.
Hi again @gasvn!
I saw you added this:
Generate semantic labels for each SAM mask.
python sam2semantic.py
would it be possible to train the ControlNet with those segmentation labels for each prompt?
from editanything.
That's possible. We are working on it. For now, you can try our new gradio demo. It combines the inpainting and edit anything, so it can achieve most of the editing ability on a part under the guidance of text prompt.
https://huggingface.co/spaces/shgao/EditAnything
from editanything.
thanks @gasvn , just tested your demo, super cool! looking forward to test multi prompt train/inference! ; )
from editanything.
Hi @gasvn, any news on the segmented training? : )
from editanything.
Hi @gasvn, any news on the segmented training? : )
There is a concern about segmented training. I am afraid that lacking training data would makes the model collapse. So the segment with text prompt would be an important issue. For now, I am using blip2 generated text prompt. But I am not sure if this is suitable for stable diffusion. Any suggestions? Thanks~
from editanything.
I think the dataset would be:
Input image
Segmented masks
Prompt for each segmented mask (either manual label or automatically generated by OpenCLIP, Blip, etc)
then you have both text, image and segmentation as conditioning.
I have a dataset that like this that I could test. Do you see how I could test to train a model with this kind of setup?
from editanything.
Hi @gasvn, I did some research on this...
Abut "segment with text prompt" we could do a test with JSON COCO dataset:
https://cocodataset.org/#home
I want to give this. shot, but not sure if its currently possible to train with JSON -> image pairs?
from editanything.
training with text JSON -> image pairs is possible. I think it's needed to slightly change the controlnet to make each segment region has a unique text prompt instead of using just global text prompt.
from editanything.
hi @gasvn , any plans for multiple prompt per mask segment ?
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Related Issues (20)
- sam2image.py can run on the gui,but when i click run,the html is always circling, and there is no log in the script HOT 1
- Filenotfound error HOT 1
- AttributeError: module 'keras.backend' has no attribute 'is_tensor' HOT 2
- serializer = serializing.COMPONENT_MAPPING[type]() KeyError: 'dataset' HOT 1
- 我部署时怎么提示app.py和editany_lora等文件里好多代码都是错的 HOT 1
- Colors for SAM mask based ControlNet during training
- How to install this project in a1111 sd webui?
- App.py run error
- fix demo HOT 2
- why should generate the mask again? HOT 1
- Unable to reproduce the dog's head example when using the same example image
- Replace pytorch 2.1+cu12.1 is ok? I found now version is 1.13, is too low
- Are we going to support SDXL-Turbo? HOT 2
- Weights creation HOT 3
- Has the author of this repository given up? HOT 3
- Which scripts if for Haircut editing? HOT 2
- ValueError at runtime HOT 2
- What is TEXT_ENCODER_TARGET_MODULES in utils/train_dreambooth_lora_inpaint.py HOT 1
- Why there is no strength parameter for StableDiffusionInpaintPipleline? HOT 3
- How to train text encoder for dreambooth inpaint lora?
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