mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2025-12-17 18:13:01 +08:00
Merge branch 'master' into dr-support-pip-cm
This commit is contained in:
Dr.Lt.Data
commit
b69ef5f869
@ -148,6 +148,8 @@ class PerformanceFeature(enum.Enum):
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parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: fp16_accumulation fp8_matrix_mult cublas_ops")
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parser.add_argument("--mmap-torch-files", action="store_true", help="Use mmap when loading ckpt/pt files.")
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parser.add_argument("--dont-print-server", action="store_true", help="Don't print server output.")
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parser.add_argument("--quick-test-for-ci", action="store_true", help="Quick test for CI.")
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parser.add_argument("--windows-standalone-build", action="store_true", help="Windows standalone build: Enable convenient things that most people using the standalone windows build will probably enjoy (like auto opening the page on startup).")
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@ -1277,6 +1277,7 @@ def res_multistep(model, x, sigmas, extra_args=None, callback=None, disable=None
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phi1_fn = lambda t: torch.expm1(t) / t
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phi2_fn = lambda t: (phi1_fn(t) - 1.0) / t
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old_sigma_down = None
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old_denoised = None
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uncond_denoised = None
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def post_cfg_function(args):
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@ -1304,9 +1305,9 @@ def res_multistep(model, x, sigmas, extra_args=None, callback=None, disable=None
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x = x + d * dt
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else:
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# Second order multistep method in https://arxiv.org/pdf/2308.02157
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t, t_next, t_prev = t_fn(sigmas[i]), t_fn(sigma_down), t_fn(sigmas[i - 1])
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t, t_old, t_next, t_prev = t_fn(sigmas[i]), t_fn(old_sigma_down), t_fn(sigma_down), t_fn(sigmas[i - 1])
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h = t_next - t
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c2 = (t_prev - t) / h
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c2 = (t_prev - t_old) / h
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phi1_val, phi2_val = phi1_fn(-h), phi2_fn(-h)
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b1 = torch.nan_to_num(phi1_val - phi2_val / c2, nan=0.0)
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@ -1326,6 +1327,7 @@ def res_multistep(model, x, sigmas, extra_args=None, callback=None, disable=None
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old_denoised = uncond_denoised
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else:
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old_denoised = denoised
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old_sigma_down = sigma_down
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return x
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@torch.no_grad()
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@ -19,6 +19,7 @@ import torch.nn.functional as F
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from torch import nn
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import comfy.model_management
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from comfy.ldm.modules.attention import optimized_attention
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class Attention(nn.Module):
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def __init__(
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@ -326,10 +327,6 @@ class CustomerAttnProcessor2_0:
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Processor for implementing scaled dot-product attention (enabled by default if you're using PyTorch 2.0).
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"""
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def __init__(self):
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if not hasattr(F, "scaled_dot_product_attention"):
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raise ImportError("AttnProcessor2_0 requires PyTorch 2.0, to use it, please upgrade PyTorch to 2.0.")
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def apply_rotary_emb(
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self,
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x: torch.Tensor,
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@ -435,13 +432,9 @@ class CustomerAttnProcessor2_0:
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attention_mask = attention_mask.view(batch_size, attn.heads, -1, attention_mask.shape[-1])
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# the output of sdp = (batch, num_heads, seq_len, head_dim)
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# TODO: add support for attn.scale when we move to Torch 2.1
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hidden_states = F.scaled_dot_product_attention(
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query, key, value, attn_mask=attention_mask, dropout_p=0.0, is_causal=False
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)
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hidden_states = hidden_states.transpose(1, 2).reshape(batch_size, -1, attn.heads * head_dim)
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hidden_states = hidden_states.to(query.dtype)
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hidden_states = optimized_attention(
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query, key, value, heads=query.shape[1], mask=attention_mask, skip_reshape=True,
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).to(query.dtype)
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# linear proj
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hidden_states = attn.to_out[0](hidden_states)
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@ -28,6 +28,9 @@ import logging
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import itertools
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from torch.nn.functional import interpolate
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from einops import rearrange
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from comfy.cli_args import args
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MMAP_TORCH_FILES = args.mmap_torch_files
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ALWAYS_SAFE_LOAD = False
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if hasattr(torch.serialization, "add_safe_globals"): # TODO: this was added in pytorch 2.4, the unsafe path should be removed once earlier versions are deprecated
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@ -67,8 +70,12 @@ def load_torch_file(ckpt, safe_load=False, device=None, return_metadata=False):
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raise ValueError("{}\n\nFile path: {}\n\nThe safetensors file is corrupt/incomplete. Check the file size and make sure you have copied/downloaded it correctly.".format(message, ckpt))
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raise e
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else:
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torch_args = {}
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if MMAP_TORCH_FILES:
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torch_args["mmap"] = True
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if safe_load or ALWAYS_SAFE_LOAD:
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pl_sd = torch.load(ckpt, map_location=device, weights_only=True)
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pl_sd = torch.load(ckpt, map_location=device, weights_only=True, **torch_args)
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else:
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pl_sd = torch.load(ckpt, map_location=device, pickle_module=comfy.checkpoint_pickle)
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if "global_step" in pl_sd:
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@ -81,7 +81,6 @@ class RecraftStyle:
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class RecraftIO:
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STYLEV3 = "RECRAFT_V3_STYLE"
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SVG = "SVG" # TODO: if acceptable, move into ComfyUI's typing class
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COLOR = "RECRAFT_COLOR"
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CONTROLS = "RECRAFT_CONTROLS"
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@ -234,9 +234,7 @@ def download_and_process_images(image_urls):
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class IdeogramV1(ComfyNodeABC):
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"""
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Generates images synchronously using the Ideogram V1 model.
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Images links are available for a limited period of time; if you would like to keep the image, you must download it.
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Generates images using the Ideogram V1 model.
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"""
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def __init__(self):
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@ -365,9 +363,7 @@ class IdeogramV1(ComfyNodeABC):
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class IdeogramV2(ComfyNodeABC):
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"""
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Generates images synchronously using the Ideogram V2 model.
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Images links are available for a limited period of time; if you would like to keep the image, you must download it.
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Generates images using the Ideogram V2 model.
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"""
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def __init__(self):
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@ -536,10 +532,7 @@ class IdeogramV2(ComfyNodeABC):
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class IdeogramV3(ComfyNodeABC):
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"""
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Generates images synchronously using the Ideogram V3 model.
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Supports both regular image generation from text prompts and image editing with mask.
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Images links are available for a limited period of time; if you would like to keep the image, you must download it.
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Generates images using the Ideogram V3 model. Supports both regular image generation from text prompts and image editing with mask.
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"""
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def __init__(self):
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@ -184,6 +184,33 @@ def validate_image_result_response(response) -> None:
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raise KlingApiError(error_msg)
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def validate_input_image(image: torch.Tensor) -> None:
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"""
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Validates the input image adheres to the expectations of the Kling API:
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- The image resolution should not be less than 300*300px
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- The aspect ratio of the image should be between 1:2.5 ~ 2.5:1
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See: https://app.klingai.com/global/dev/document-api/apiReference/model/imageToVideo
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"""
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if len(image.shape) == 4:
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height, width = image.shape[1], image.shape[2]
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elif len(image.shape) == 3:
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height, width = image.shape[0], image.shape[1]
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else:
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raise ValueError("Invalid image tensor shape.")
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# Ensure minimum resolution is met
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if height < 300:
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raise ValueError("Image height must be at least 300px")
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if width < 300:
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raise ValueError("Image width must be at least 300px")
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# Ensure aspect ratio is within acceptable range
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aspect_ratio = width / height
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if aspect_ratio < 1 / 2.5 or aspect_ratio > 2.5:
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raise ValueError("Image aspect ratio must be between 1:2.5 and 2.5:1")
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def get_camera_control_input_config(
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tooltip: str, default: float = 0.0
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) -> tuple[IO, InputTypeOptions]:
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@ -530,7 +557,10 @@ class KlingImage2VideoNode(KlingNodeBase):
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return {
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"required": {
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"start_frame": model_field_to_node_input(
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IO.IMAGE, KlingImage2VideoRequest, "image"
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IO.IMAGE,
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KlingImage2VideoRequest,
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"image",
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tooltip="The reference image used to generate the video.",
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),
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"prompt": model_field_to_node_input(
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IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
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@ -607,9 +637,10 @@ class KlingImage2VideoNode(KlingNodeBase):
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auth_token: Optional[str] = None,
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) -> tuple[VideoFromFile]:
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validate_prompts(prompt, negative_prompt, MAX_PROMPT_LENGTH_I2V)
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validate_input_image(start_frame)
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if camera_control is not None:
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# Camera control type for image 2 video is always simple
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# Camera control type for image 2 video is always `simple`
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camera_control.type = KlingCameraControlType.simple
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initial_operation = SynchronousOperation(
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@ -1,6 +1,7 @@
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from __future__ import annotations
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from inspect import cleandoc
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from comfy.utils import ProgressBar
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from comfy_extras.nodes_images import SVG # Added
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from comfy.comfy_types.node_typing import IO
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from comfy_api_nodes.apis.recraft_api import (
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RecraftImageGenerationRequest,
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@ -28,9 +29,6 @@ from comfy_api_nodes.apinode_utils import (
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resize_mask_to_image,
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validate_string,
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)
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import folder_paths
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import json
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import os
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import torch
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from io import BytesIO
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from PIL import UnidentifiedImageError
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@ -162,102 +160,6 @@ class handle_recraft_image_output:
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raise Exception("Received output data was not an image; likely an SVG. If you used style_id, make sure it is not a Vector art style.")
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class SVG:
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"""
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Stores SVG representations via a list of BytesIO objects.
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"""
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def __init__(self, data: list[BytesIO]):
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self.data = data
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def combine(self, other: SVG):
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return SVG(self.data + other.data)
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@staticmethod
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def combine_all(svgs: list[SVG]):
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all_svgs = []
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for svg in svgs:
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all_svgs.extend(svg.data)
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return SVG(all_svgs)
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class SaveSVGNode:
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"""
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Save SVG files on disk.
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"""
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def __init__(self):
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self.output_dir = folder_paths.get_output_directory()
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self.type = "output"
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self.prefix_append = ""
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RETURN_TYPES = ()
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DESCRIPTION = cleandoc(__doc__ or "") # Handle potential None value
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FUNCTION = "save_svg"
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CATEGORY = "api node/image/Recraft"
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OUTPUT_NODE = True
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"svg": (RecraftIO.SVG,),
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"filename_prefix": ("STRING", {"default": "svg/ComfyUI", "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."})
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},
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"hidden": {
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"prompt": "PROMPT",
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"extra_pnginfo": "EXTRA_PNGINFO"
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}
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}
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def save_svg(self, svg: SVG, filename_prefix="svg/ComfyUI", prompt=None, extra_pnginfo=None):
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filename_prefix += self.prefix_append
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full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
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results = list()
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# Prepare metadata JSON
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metadata_dict = {}
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if prompt is not None:
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metadata_dict["prompt"] = prompt
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if extra_pnginfo is not None:
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metadata_dict.update(extra_pnginfo)
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# Convert metadata to JSON string
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metadata_json = json.dumps(metadata_dict, indent=2) if metadata_dict else None
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for batch_number, svg_bytes in enumerate(svg.data):
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filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
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file = f"{filename_with_batch_num}_{counter:05}_.svg"
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# Read SVG content
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svg_bytes.seek(0)
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svg_content = svg_bytes.read().decode('utf-8')
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# Inject metadata if available
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if metadata_json:
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# Create metadata element with CDATA section
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metadata_element = f""" <metadata>
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<![CDATA[
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{metadata_json}
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]]>
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</metadata>
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"""
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# Insert metadata after opening svg tag using regex
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import re
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svg_content = re.sub(r'(<svg[^>]*>)', r'\1\n' + metadata_element, svg_content)
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# Write the modified SVG to file
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with open(os.path.join(full_output_folder, file), 'wb') as svg_file:
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svg_file.write(svg_content.encode('utf-8'))
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results.append({
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"filename": file,
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"subfolder": subfolder,
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"type": self.type
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})
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counter += 1
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return { "ui": { "images": results } }
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class RecraftColorRGBNode:
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"""
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Create Recraft Color by choosing specific RGB values.
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@ -796,8 +698,8 @@ class RecraftTextToVectorNode:
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Generates SVG synchronously based on prompt and resolution.
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"""
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RETURN_TYPES = (RecraftIO.SVG,)
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DESCRIPTION = cleandoc(__doc__ or "") # Handle potential None value
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RETURN_TYPES = ("SVG",) # Changed
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DESCRIPTION = cleandoc(__doc__ or "") if 'cleandoc' in globals() else __doc__ # Keep cleandoc if other nodes use it
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FUNCTION = "api_call"
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API_NODE = True
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CATEGORY = "api node/image/Recraft"
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@ -918,8 +820,8 @@ class RecraftVectorizeImageNode:
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Generates SVG synchronously from an input image.
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"""
|
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RETURN_TYPES = (RecraftIO.SVG,)
|
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DESCRIPTION = cleandoc(__doc__ or "") # Handle potential None value
|
||||
RETURN_TYPES = ("SVG",) # Changed
|
||||
DESCRIPTION = cleandoc(__doc__ or "") if 'cleandoc' in globals() else __doc__ # Keep cleandoc if other nodes use it
|
||||
FUNCTION = "api_call"
|
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API_NODE = True
|
||||
CATEGORY = "api node/image/Recraft"
|
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@ -1193,7 +1095,6 @@ NODE_CLASS_MAPPINGS = {
|
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"RecraftStyleV3InfiniteStyleLibrary": RecraftStyleInfiniteStyleLibrary,
|
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"RecraftColorRGB": RecraftColorRGBNode,
|
||||
"RecraftControls": RecraftControlsNode,
|
||||
"SaveSVG": SaveSVGNode,
|
||||
}
|
||||
|
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# A dictionary that contains the friendly/humanly readable titles for the nodes
|
||||
@ -1213,5 +1114,4 @@ NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"RecraftStyleV3InfiniteStyleLibrary": "Recraft Style - Infinite Style Library",
|
||||
"RecraftColorRGB": "Recraft Color RGB",
|
||||
"RecraftControls": "Recraft Controls",
|
||||
"SaveSVG": "Save SVG",
|
||||
}
|
||||
|
||||
@ -10,6 +10,9 @@ from PIL.PngImagePlugin import PngInfo
|
||||
import numpy as np
|
||||
import json
|
||||
import os
|
||||
import re
|
||||
from io import BytesIO
|
||||
from inspect import cleandoc
|
||||
|
||||
from comfy.comfy_types import FileLocator
|
||||
|
||||
@ -190,10 +193,109 @@ class SaveAnimatedPNG:
|
||||
|
||||
return { "ui": { "images": results, "animated": (True,)} }
|
||||
|
||||
class SVG:
|
||||
"""
|
||||
Stores SVG representations via a list of BytesIO objects.
|
||||
"""
|
||||
def __init__(self, data: list[BytesIO]):
|
||||
self.data = data
|
||||
|
||||
def combine(self, other: 'SVG') -> 'SVG':
|
||||
return SVG(self.data + other.data)
|
||||
|
||||
@staticmethod
|
||||
def combine_all(svgs: list['SVG']) -> 'SVG':
|
||||
all_svgs_list: list[BytesIO] = []
|
||||
for svg_item in svgs:
|
||||
all_svgs_list.extend(svg_item.data)
|
||||
return SVG(all_svgs_list)
|
||||
|
||||
class SaveSVGNode:
|
||||
"""
|
||||
Save SVG files on disk.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self.output_dir = folder_paths.get_output_directory()
|
||||
self.type = "output"
|
||||
self.prefix_append = ""
|
||||
|
||||
RETURN_TYPES = ()
|
||||
DESCRIPTION = cleandoc(__doc__ or "") # Handle potential None value
|
||||
FUNCTION = "save_svg"
|
||||
CATEGORY = "image/save" # Changed
|
||||
OUTPUT_NODE = True
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"svg": ("SVG",), # Changed
|
||||
"filename_prefix": ("STRING", {"default": "svg/ComfyUI", "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."})
|
||||
},
|
||||
"hidden": {
|
||||
"prompt": "PROMPT",
|
||||
"extra_pnginfo": "EXTRA_PNGINFO"
|
||||
}
|
||||
}
|
||||
|
||||
def save_svg(self, svg: SVG, filename_prefix="svg/ComfyUI", prompt=None, extra_pnginfo=None):
|
||||
filename_prefix += self.prefix_append
|
||||
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
|
||||
results = list()
|
||||
|
||||
# Prepare metadata JSON
|
||||
metadata_dict = {}
|
||||
if prompt is not None:
|
||||
metadata_dict["prompt"] = prompt
|
||||
if extra_pnginfo is not None:
|
||||
metadata_dict.update(extra_pnginfo)
|
||||
|
||||
# Convert metadata to JSON string
|
||||
metadata_json = json.dumps(metadata_dict, indent=2) if metadata_dict else None
|
||||
|
||||
for batch_number, svg_bytes in enumerate(svg.data):
|
||||
filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
|
||||
file = f"{filename_with_batch_num}_{counter:05}_.svg"
|
||||
|
||||
# Read SVG content
|
||||
svg_bytes.seek(0)
|
||||
svg_content = svg_bytes.read().decode('utf-8')
|
||||
|
||||
# Inject metadata if available
|
||||
if metadata_json:
|
||||
# Create metadata element with CDATA section
|
||||
metadata_element = f""" <metadata>
|
||||
<![CDATA[
|
||||
{metadata_json}
|
||||
]]>
|
||||
</metadata>
|
||||
"""
|
||||
# Insert metadata after opening svg tag using regex with a replacement function
|
||||
def replacement(match):
|
||||
# match.group(1) contains the captured <svg> tag
|
||||
return match.group(1) + '\n' + metadata_element
|
||||
|
||||
# Apply the substitution
|
||||
svg_content = re.sub(r'(<svg[^>]*>)', replacement, svg_content, flags=re.UNICODE)
|
||||
|
||||
# Write the modified SVG to file
|
||||
with open(os.path.join(full_output_folder, file), 'wb') as svg_file:
|
||||
svg_file.write(svg_content.encode('utf-8'))
|
||||
|
||||
results.append({
|
||||
"filename": file,
|
||||
"subfolder": subfolder,
|
||||
"type": self.type
|
||||
})
|
||||
counter += 1
|
||||
return { "ui": { "images": results } }
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"ImageCrop": ImageCrop,
|
||||
"RepeatImageBatch": RepeatImageBatch,
|
||||
"ImageFromBatch": ImageFromBatch,
|
||||
"SaveAnimatedWEBP": SaveAnimatedWEBP,
|
||||
"SaveAnimatedPNG": SaveAnimatedPNG,
|
||||
"SaveSVGNode": SaveSVGNode,
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user