diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..3e8f5e2 --- /dev/null +++ b/.gitignore @@ -0,0 +1,2 @@ +/__pycache__/ +/models/*.bin \ No newline at end of file diff --git a/IPAdapterPlus.py b/IPAdapterPlus.py new file mode 100644 index 0000000..c1956ad --- /dev/null +++ b/IPAdapterPlus.py @@ -0,0 +1,212 @@ +import torch +import os + +import comfy.utils +import comfy.model_management + +from torch import nn +from transformers import CLIPVisionModelWithProjection + +MODELS_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "models") + +# attention_channels +SD_V12_CHANNELS = [320] * 4 + [640] * 4 + [1280] * 4 + [1280] * 6 + [640] * 6 + [320] * 6 + [1280] * 2 +SD_XL_CHANNELS = [640] * 8 + [1280] * 40 + [1280] * 60 + [640] * 12 + [1280] * 20 + +def get_filename_list(path): + return [f for f in os.listdir(path) if f.endswith('.bin')] + +class ImageProjModel(nn.Module): + def __init__(self, cross_attention_dim=1024, clip_embeddings_dim=1024, clip_extra_context_tokens=4): + super().__init__() + + self.cross_attention_dim = cross_attention_dim + self.clip_extra_context_tokens = clip_extra_context_tokens + self.proj = nn.Linear(clip_embeddings_dim, self.clip_extra_context_tokens * cross_attention_dim) + self.norm = nn.LayerNorm(cross_attention_dim) + + def forward(self, image_embeds): + embeds = image_embeds + clip_extra_context_tokens = self.proj(embeds).reshape(-1, self.clip_extra_context_tokens, self.cross_attention_dim) + clip_extra_context_tokens = self.norm(clip_extra_context_tokens) + return clip_extra_context_tokens + +class To_KV(nn.Module): + def __init__(self, cross_attention_dim): + super().__init__() + + channels = SD_XL_CHANNELS if cross_attention_dim == 2048 else SD_V12_CHANNELS + self.to_kvs = nn.ModuleList([torch.nn.Linear(cross_attention_dim, channel, bias=False) for channel in channels]) + + def load_state_dict(self, state_dict): + # input -> output -> middle + for i, key in enumerate(state_dict.keys()): + self.to_kvs[i].weight.data = state_dict[key] + +''' +code from I'm using the code from: +https://github.com/comfyanonymous/ComfyUI/blob/a74c5dbf3764fa598b58da8c88da823aaf8364fa/comfy/model_patcher.py#L64 +''' +def set_model_patch_replace(model, patch, block_name, number, index, name="attn2"): + to = model.model_options["transformer_options"] + if "patches_replace" not in to: + to["patches_replace"] = {} + if name not in to["patches_replace"]: + to["patches_replace"][name] = {} + to["patches_replace"][name][(block_name, number, index)] = patch + +class IPAdapter(nn.Module): + def __init__(self, ipadapter_model, clip_embeddings_dim, dtype=torch.float16, device="cuda", num_tokens=4): + super().__init__() + + self.ipadapter_model = ipadapter_model + self.device = device + #self.num_tokens = num_tokens + self.dtype = dtype + + self.cross_attention_dim = self.ipadapter_model["ip_adapter"]["1.to_k_ip.weight"].shape[1] + self.clip_extra_context_tokens = num_tokens + + self.image_proj_model = ImageProjModel( + cross_attention_dim=self.cross_attention_dim, + clip_embeddings_dim=clip_embeddings_dim, + clip_extra_context_tokens=self.clip_extra_context_tokens + ) + + self.image_proj_model.load_state_dict(self.ipadapter_model["image_proj"]) + self.ip_layers = To_KV(self.cross_attention_dim) + self.ip_layers.load_state_dict(self.ipadapter_model["ip_adapter"]) + + @torch.inference_mode() + def get_image_embeds(self, clip_image_embeds): + image_prompt_embeds = self.image_proj_model(clip_image_embeds) + uncond_image_prompt_embeds = self.image_proj_model(torch.zeros_like(clip_image_embeds)) + return image_prompt_embeds, uncond_image_prompt_embeds + +class IPAdapterModelLoader: + @classmethod + def INPUT_TYPES(s): + return {"required": { "ipadapter_file": (get_filename_list(MODELS_DIR), )}} + + RETURN_TYPES = ("IPADAPTER",) + FUNCTION = "load_ipadapter_model" + + CATEGORY = "loaders" + + def load_ipadapter_model(self, ipadapter_file): + ckpt_path = os.path.join(MODELS_DIR, ipadapter_file) + + model = comfy.utils.load_torch_file(ckpt_path, safe_load=True) + keys = model.keys() + + if not "ip_adapter" in keys: + raise Exception("invalid IPAdapter model {}".format(ckpt_path)) + + return (model,) + +class IPAdapterApply: + @classmethod + def INPUT_TYPES(s): + return {"required": {"model": ("MODEL", ), + "ipadapter": ("IPADAPTER", ), + "clip_vision_output": ("CLIP_VISION_OUTPUT", ), + "weight": ("FLOAT", { "default": 1.0, "min": -1, "max": 3, "step": 0.1 }), + }} + RETURN_TYPES = ("MODEL",) + FUNCTION = "apply_ipadapter" + CATEGORY = "conditioning/ipadapter" + + def apply_ipadapter(self, model, ipadapter, clip_vision_output, weight): + self.dtype = model.model.diffusion_model.dtype + self.device = comfy.model_management.get_torch_device() + self.weight = weight + + clip_embeddings = clip_vision_output.image_embeds.to(self.device, dtype=self.dtype) + clip_embeddings_dim = clip_embeddings.shape[1] + + self.sdxl = clip_embeddings_dim == 1280 # is there a better way? + + self.ipadapter = IPAdapter( + ipadapter, + clip_embeddings_dim, + dtype=self.dtype, + device=self.device + ).to(self.device, dtype=self.dtype) + + self.image_prompt_embeds, self.uncond_image_prompt_embeds = self.ipadapter.get_image_embeds(clip_embeddings) + self.image_prompt_embeds = self.image_prompt_embeds.to(self.device, dtype=self.dtype) + self.uncond_image_prompt_embeds = self.uncond_image_prompt_embeds.to(self.device, dtype=self.dtype) + self.cond_uncond_image_emb = None + + work_model = model.clone() + + if not self.sdxl: + number = 0 # index of to_kvs + for id in [1,2,4,5,7,8]: # id of input_blocks that have cross attention + work_model.set_model_attn2_replace(self.patch_forward(number), "input", id) + number += 1 + for id in [3,4,5,6,7,8,9,10,11]: # id of output_blocks that have cross attention + work_model.set_model_attn2_replace(self.patch_forward(number), "output", id) + number += 1 + work_model.set_model_attn2_replace(self.patch_forward(number), "middle", 0) + else: + number = 0 + for id in [4,5,7,8]: # id of input_blocks that have cross attention + block_indices = range(2) if id in [4, 5] else range(10) # transformer_depth + for index in block_indices: + set_model_patch_replace(work_model, self.patch_forward(number), "input", id, index) + number += 1 + for id in range(6): # id of output_blocks that have cross attention + block_indices = range(2) if id in [3, 4, 5] else range(10) # transformer_depth + for index in block_indices: + set_model_patch_replace(work_model, self.patch_forward(number), "output", id, index) + number += 1 + for index in range(10): + set_model_patch_replace(work_model, self.patch_forward(number), "middle", 0, index) + number += 1 + + return (work_model, ) + + def patch_forward(self, number): + device = self.device.type + def forward(n, context_attn2, value_attn2, extra_options): + org_dtype = n.dtype + with torch.autocast(device, dtype=self.dtype): + q = n + k = context_attn2 + v = value_attn2 + b, _, _ = q.shape + + if self.cond_uncond_image_emb is None or self.cond_uncond_image_emb.shape[0] != b: + self.cond_uncond_image_emb = torch.cat([self.uncond_image_prompt_embeds.repeat(b//2, 1, 1), self.image_prompt_embeds.repeat(b//2, 1, 1)], dim=0) + + # k, v for ip_adapter + ip_k = self.ipadapter.ip_layers.to_kvs[number*2](self.cond_uncond_image_emb) + ip_v = self.ipadapter.ip_layers.to_kvs[number*2+1](self.cond_uncond_image_emb) + + q, k, v, ip_k, ip_v = map( + lambda t: t.view(b, -1, extra_options["n_heads"], extra_options["dim_head"]).transpose(1, 2), + (q, k, v, ip_k, ip_v), + ) + + out = nn.functional.scaled_dot_product_attention(q, k, v, attn_mask=None, dropout_p=0.0, is_causal=False) + out = out.transpose(1, 2).reshape(b, -1, extra_options["n_heads"] * extra_options["dim_head"]) + + # output of ip_adapter + ip_out = nn.functional.scaled_dot_product_attention(q, ip_k, ip_v, attn_mask=None, dropout_p=0.0, is_causal=False) + ip_out = ip_out.transpose(1, 2).reshape(b, -1, extra_options["n_heads"] * extra_options["dim_head"]) + + out = out + ip_out * self.weight + + return out.to(dtype=org_dtype) + return forward + +NODE_CLASS_MAPPINGS = { + "IPAdapterModelLoader": IPAdapterModelLoader, + "IPAdapterApply": IPAdapterApply, +} + +NODE_DISPLAY_NAME_MAPPINGS = { + "IPAdapterModelLoader": "Load IPAdapter Model", + "IPAdapterApply": "Apply IPAdapter", +} \ No newline at end of file diff --git a/IPAdapter_workflow.json b/IPAdapter_workflow.json new file mode 100644 index 0000000..9831923 --- /dev/null +++ b/IPAdapter_workflow.json @@ -0,0 +1,610 @@ +{ + "last_node_id": 19, + "last_link_id": 30, + "nodes": [ + { + "id": 12, + "type": "VAEDecode", + "pos": [ + 1430, + 320 + ], + "size": { + "0": 140, + "1": 50 + }, + "flags": {}, + "order": 10, + "mode": 0, + "inputs": [ + { + "name": "samples", + "type": "LATENT", + "link": 12 + }, + { + "name": "vae", + "type": "VAE", + "link": 13 + } + ], + "outputs": [ + { + "name": "IMAGE", + "type": "IMAGE", + "links": [ + 14 + ], + "shape": 3, + 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"Node name for S&R": "KSampler" + }, + "widgets_values": [ + 11, + "fixed", + 20, + 7, + "dpmpp_2m", + "karras", + 1 + ] + }, + { + "id": 1, + "type": "CLIPVisionLoader", + "pos": [ + 30, + 90 + ], + "size": { + "0": 315, + "1": 58 + }, + "flags": {}, + "order": 0, + "mode": 0, + "outputs": [ + { + "name": "CLIP_VISION", + "type": "CLIP_VISION", + "links": [ + 1 + ], + "shape": 3, + "slot_index": 0 + } + ], + "properties": { + "Node name for S&R": "CLIPVisionLoader" + }, + "widgets_values": [ + "IP-Adapter_sd15_pytorch_model.bin" + ] + } + ], + "links": [ + [ + 1, + 1, + 0, + 2, + 0, + "CLIP_VISION" + ], + [ + 2, + 6, + 0, + 2, + 1, + "IMAGE" + ], + [ + 6, + 7, + 1, + 8, + 0, + "CLIP" + ], + [ + 7, + 7, + 1, + 9, + 0, + "CLIP" + ], + [ + 11, + 11, + 0, + 10, + 3, + "LATENT" + ], + [ + 12, + 10, + 0, + 12, + 0, + "LATENT" + ], + [ + 13, + 7, + 2, + 12, + 1, + "VAE" + ], + [ + 14, + 12, + 0, + 13, + 0, + "IMAGE" + ], + [ + 20, + 8, + 0, + 10, + 1, + "CONDITIONING" + ], + [ + 21, + 9, + 0, + 10, + 2, + "CONDITIONING" + ], + [ + 27, + 3, + 0, + 17, + 1, + "IPADAPTER" + ], + [ + 28, + 2, + 0, + 17, + 2, + "CLIP_VISION_OUTPUT" + ], + [ + 29, + 17, + 0, + 10, + 0, + "MODEL" + ], + [ + 30, + 7, + 0, + 17, + 0, + "MODEL" + ] + ], + "groups": [], + "config": {}, + "extra": {}, + "version": 0.4 +} \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..f288702 --- /dev/null +++ b/LICENSE @@ -0,0 +1,674 @@ + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If the program does terminal interaction, make it output a short +notice like this when it starts in an interactive mode: + + Copyright (C) + This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w' and `show c' should show the appropriate +parts of the General Public License. Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/README.md b/README.md index cfaa7be..f3c94cc 100644 --- a/README.md +++ b/README.md @@ -1,2 +1,30 @@ -# ComfyUI IPAdapter Plus +# ComfyUI_IPAdapter_Plus ComfyUI reference implementation for [IPAdapter](https://github.com/tencent-ailab/IP-Adapter/tree/6fb9d3554a5c774f41e187e8fdbc7b9a1db8c2e3) models. + +The code is mostly taken from the original IPAdapter repository and [laksjdjf's](https://github.com/laksjdjf/IPAdapter-ComfyUI/tree/main) implementation, all credit goes to them. I just made the extension closer to ComfyUI philosophy. + +Example workflow + +![IPAdapter Example workflow](./ipadapter_workflow.png) + +## Installation + +Download or git clone this repository inside `ComfyUI/custom_nodes/` directory. + +The pre-trained models are available on [huggingface](https://huggingface.co/h94/IP-Adapter), download and place them in the `ComfyUI/custom_nodes/ComfyUI_IPAdapter_Plus/models` directory. + +For SD1.5 you need: + +- [ip-adapter_sd15.bin](https://huggingface.co/h94/IP-Adapter/resolve/main/models/ip-adapter_sd15.bin) +- [ip-adapter-plus_sd15.bin](https://huggingface.co/h94/IP-Adapter/resolve/main/models/ip-adapter-plus_sd15.bin) +- [ip-adapter-plus-face_sd15.bin](https://huggingface.co/h94/IP-Adapter/resolve/main/models/ip-adapter-plus-face_sd15.bin) + +For SDXL you need: +- [ip-adapter_sdxl.bin](https://huggingface.co/h94/IP-Adapter/resolve/main/sdxl_models/ip-adapter_sdxl.bin) + +Additionally you need the clip vision models: + +- SD 1.5: [pytorch_model.bin](https://huggingface.co/h94/IP-Adapter/resolve/main/models/image_encoder/pytorch_model.bin) +- SDXL: [pytorch_model.bin](https://huggingface.co/h94/IP-Adapter/resolve/main/sdxl_models/image_encoder/pytorch_model.bin) + +You can rename them to something easier to remember (eg: `ip-adapter_sd15-image-encoder.bin`) and place them under `ComfyUI/models/clip_vision/`. \ No newline at end of file diff --git a/__init__.py b/__init__.py new file mode 100644 index 0000000..cdd2511 --- /dev/null +++ b/__init__.py @@ -0,0 +1,3 @@ +from .IPAdapterPlus import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS + +__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS'] diff --git a/ipadapter_workflow.png b/ipadapter_workflow.png new file mode 100644 index 0000000..c51fcff Binary files /dev/null and b/ipadapter_workflow.png differ diff --git a/models/put_ipadapter_models_here.txt b/models/put_ipadapter_models_here.txt new file mode 100644 index 0000000..e69de29