nodes/ritik-devsecops-ComfyUI-Floyo-Flux2-API-node
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Simplify Flux2 edit inputs to image tensors only

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RITIK
2025-11-26 14:25:25 +05:30
parent a9aef31f67
commit 4320810db7
2 changed files with 34 additions and 55 deletions
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README.md
+2 -2
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@@ -39,8 +39,8 @@ Repo layout (mirrors Floyo Seed API style):
- **Output:** `image` (IMAGE tensor ready for Save Image)
### FLUX.2 [pro] Image Edit (`Flux2ProImageEdit`)
- **Inputs (required):** `prompt`, `input_image` (IMAGE tensor) or `input_image_url` (URL). If both are set, URL wins.
- **Inputs (optional):** `input_image_2` … `input_image_8` (IMAGE tensors) and matching `input_image_2_url` … `input_image_8_url`. URLs win over tensors. Keep total refs <= 8. `width`, `height` (0 = match input), `seed` (`-1` = random), `safety_tolerance`, `output_format`
- **Inputs (required):** `prompt`, `input_image` (IMAGE tensor)
- **Inputs (optional):** `input_image_2` … `input_image_8` (IMAGE tensors, keep total refs <= 8). `width`, `height` (0 = match input), `seed` (`-1` = random), `safety_tolerance`, `output_format`
- **Output:** `image` (IMAGE tensor ready for Save Image)
## Usage Notes
nodes/flux2_node.py
+32 -53
View File
@@ -4,7 +4,6 @@ from .flux2_utils import (
Flux2API,
download_image_to_tensor,
image_tensor_to_base64,
merge_reference_images,
)
from .flux2_utils import _blank_image_tensor as _blank_image
@@ -95,29 +94,19 @@ class Flux2ProImageEdit:
@classmethod
def INPUT_TYPES(cls):
base_image_inputs = {
"input_image": ("IMAGE", {"tooltip": "Base image (connect IMAGE)."}),
"input_image_url": ("STRING", {"default": "", "tooltip": "Base image URL (used if set)."}),
}
optional_refs = {}
for idx in range(2, 9):
optional_refs[f"input_image_{idx}"] = (
"IMAGE",
{"tooltip": f"Optional reference image #{idx}."},
)
optional_refs[f"input_image_{idx}_url"] = (
"STRING",
{"default": "", "tooltip": f"Optional reference image URL #{idx}."},
)
return {
"required": {
"prompt": ("STRING", {"multiline": True, "default": "", "tooltip": "Describe the edit you want."}),
**base_image_inputs,
"input_image": ("IMAGE", {"tooltip": "Base image."}),
},
"optional": {
**optional_refs,
"input_image_2": ("IMAGE", {"tooltip": "Optional reference image #2."}),
"input_image_3": ("IMAGE", {"tooltip": "Optional reference image #3."}),
"input_image_4": ("IMAGE", {"tooltip": "Optional reference image #4."}),
"input_image_5": ("IMAGE", {"tooltip": "Optional reference image #5."}),
"input_image_6": ("IMAGE", {"tooltip": "Optional reference image #6."}),
"input_image_7": ("IMAGE", {"tooltip": "Optional reference image #7."}),
"input_image_8": ("IMAGE", {"tooltip": "Optional reference image #8."}),
"width": ("INT", {"default": 0, "min": 0, "max": 2048, "step": 16, "tooltip": "Override width (0 = keep). Multiple of 16."}),
"height": ("INT", {"default": 0, "min": 0, "max": 2048, "step": 16, "tooltip": "Override height (0 = keep). Multiple of 16."}),
"seed": ("INT", {"default": -1, "min": -1, "max": 0xFFFFFFFF, "tooltip": "-1 = random. Any other integer is reproducible."}),
@@ -135,21 +124,13 @@ class Flux2ProImageEdit:
self,
prompt: str,
input_image,
input_image_url: str = "",
input_image_2=None,
input_image_2_url: str = "",
input_image_3=None,
input_image_3_url: str = "",
input_image_4=None,
input_image_4_url: str = "",
input_image_5=None,
input_image_5_url: str = "",
input_image_6=None,
input_image_6_url: str = "",
input_image_7=None,
input_image_7_url: str = "",
input_image_8=None,
input_image_8_url: str = "",
width: int = 0,
height: int = 0,
seed: int = -1,
@@ -161,37 +142,35 @@ class Flux2ProImageEdit:
if resolution_error:
return (f"Error: {resolution_error}",)
def resolve_image(source_tensor, source_url: str) -> Optional[str]:
if source_url and source_url.strip():
return source_url.strip()
if source_tensor is not None:
try:
return image_tensor_to_base64(source_tensor, format="PNG")
except Exception as exc:
print(f"Warning: failed to convert image tensor to base64: {exc}")
return None
return None
def resolve_image(source_tensor) -> Optional[str]:
if source_tensor is None:
return None
try:
return image_tensor_to_base64(source_tensor, format="PNG")
except Exception as exc:
print(f"Warning: failed to convert image tensor to base64: {exc}")
return None
base_image_value = resolve_image(input_image, input_image_url)
base_image_value = resolve_image(input_image)
if not base_image_value:
return ("Error: Provide a base image tensor or URL.",)
return ("Error: Provide a base image.",)
additional_images: List[str] = []
ref_pairs = [
(input_image_2, input_image_2_url),
(input_image_3, input_image_3_url),
(input_image_4, input_image_4_url),
(input_image_5, input_image_5_url),
(input_image_6, input_image_6_url),
(input_image_7, input_image_7_url),
(input_image_8, input_image_8_url),
reference_payload = {"input_image": base_image_value}
refs = [
input_image_2,
input_image_3,
input_image_4,
input_image_5,
input_image_6,
input_image_7,
input_image_8,
]
for tensor_val, url_val in ref_pairs:
resolved = resolve_image(tensor_val, url_val)
additional_images.append(resolved if resolved else "")
reference_payload = merge_reference_images(base_image_value, additional_images)
for idx, tensor_val in enumerate(refs, start=2):
resolved = resolve_image(tensor_val)
if resolved:
reference_payload[f"input_image_{idx}"] = resolved
payload = {
"prompt": prompt,