nodes/comrender-ComfyUI-NanoSeed
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Added support for more direct inputs, safety filter reduced by default for NB2, some other minor tweaks.
This commit is contained in:
comrender
2026-06-01 16:23:58 +02:00
committed by GitHub
parent 88f8583652
commit ba28e8631b
1 changed files with 105 additions and 67 deletions
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nano_seed.py
+105 -67
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@@ -25,56 +25,78 @@ def tensor2pil(image_tensor):
return Image.fromarray(image, mode='RGB')
# Helper function to convert PIL Image (RGB) back to ComfyUI tensor (B=1, H, W, C)
def pil2tensor(pil_image):
if pil_image is None:
return None
arr = np.array(pil_image).astype(np.float32) / 255.0
arr = arr[np.newaxis, ...]
return torch.from_numpy(arr)
# Main node class
class NanoSeedEdit:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"prompt": ("STRING", {"default": "Edit the image according to this prompt.", "multiline": True}),
"model": (["nano_banana", "nano_banana_pro", "nano_banana_2", "grok_imagine_edit", "seedream_4.5", "qwen_edit_plus", "flux_2_edit", "flux_2_pro", "flux_2_flex"],),
"fal_key": ("STRING", {"default": "your_fal_key_here"}),
},
"optional": {
"image1": ("IMAGE",),
"image2": ("IMAGE",),
"image3": ("IMAGE",),
"image4": ("IMAGE",),
"image5": ("IMAGE",),
"width": ("INT", {"default": 0, "min": 0, "max": 4096, "display": "number"}),
"height": ("INT", {"default": 0, "min": 0, "max": 4096, "display": "number"}),
"num_images": ("INT", {"default": 1, "min": 1, "max": 6}),
"seed": ("INT", {"default": 0, "min": 0, "max": 2**32 - 1}),
"aspect_ratio": (["auto", "21:9", "16:9", "3:2", "4:3", "5:4", "1:1", "4:5", "3:4", "2:3", "9:16", "4:1", "1:4", "8:1", "1:8"], {"default": "auto"}),
"resolution": (["0.5K", "1K", "2K", "4K"], {"default": "1K"}),
"enable_web_search": ("BOOLEAN", {"default": False}),
"thinking_level": (["off", "minimal", "high"], {"default": "off"}),
}
}
def pil2tensor(pil_image):
if pil_image is None:
return None
arr = np.array(pil_image).astype(np.float32) / 255.0
arr = arr[np.newaxis, ...]
return torch.from_numpy(arr)
def tensor2data_uri(image_tensor):
pil_image = tensor2pil(image_tensor)
if pil_image is None:
return None
return pil2data_uri(pil_image)
def pil2data_uri(pil_image):
buffer = BytesIO()
pil_image.save(buffer, format="PNG")
img_str = base64.b64encode(buffer.getvalue()).decode()
return f"data:image/png;base64,{img_str}"
# Main node class
class NanoSeedEdit:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"prompt": ("STRING", {"default": "Edit the image according to this prompt.", "multiline": True}),
"model": (["nano_banana", "nano_banana_pro", "nano_banana_2", "gpt_image_2_edit", "grok_imagine_edit", "seedream_4.5", "qwen_edit_plus", "flux_2_edit", "flux_2_pro", "flux_2_flex"],),
"fal_key": ("STRING", {"default": "your_fal_key_here"}),
},
"optional": {
"image1": ("IMAGE",),
"image2": ("IMAGE",),
"image3": ("IMAGE",),
"image4": ("IMAGE",),
"image5": ("IMAGE",),
"image6": ("IMAGE",),
"image7": ("IMAGE",),
"image8": ("IMAGE",),
"image9": ("IMAGE",),
"image10": ("IMAGE",),
"mask": ("IMAGE",),
"width": ("INT", {"default": 0, "min": 0, "max": 4096, "display": "number"}),
"height": ("INT", {"default": 0, "min": 0, "max": 4096, "display": "number"}),
"num_images": ("INT", {"default": 1, "min": 1, "max": 6}),
"seed": ("INT", {"default": 0, "min": 0, "max": 2**32 - 1}),
"aspect_ratio": (["auto", "21:9", "16:9", "3:2", "4:3", "5:4", "1:1", "4:5", "3:4", "2:3", "9:16", "4:1", "1:4", "8:1", "1:8"], {"default": "auto"}),
"resolution": (["0.5K", "1K", "2K", "4K"], {"default": "1K"}),
"quality": (["low", "medium", "high"], {"default": "high"}),
"enable_web_search": ("BOOLEAN", {"default": False}),
"thinking_level": (["off", "minimal", "high"], {"default": "off"}),
}
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("edited_image",)
FUNCTION = "edit_image"
CATEGORY = "image/edit"
OUTPUT_NODE = True
def edit_image(self, prompt, model, fal_key, image1=None, image2=None, image3=None, image4=None, image5=None,
width=0, height=0, num_images=1, seed=0, aspect_ratio="auto", resolution="1K",
enable_web_search=False, thinking_level="off", acceleration="none"): # Hardcoded to none, kept for compatibility
if fal_key == "your_fal_key_here":
raise ValueError("Please set your fal.ai API key in the node.")
# Collect all non-None images
images = [img for img in [image1, image2, image3, image4, image5] if img is not None]
if not images:
raise ValueError("At least one image input must be connected.")
FUNCTION = "edit_image"
CATEGORY = "image/edit"
OUTPUT_NODE = True
def edit_image(self, prompt, model, fal_key, image1=None, image2=None, image3=None, image4=None, image5=None,
image6=None, image7=None, image8=None, image9=None, image10=None, mask=None,
width=0, height=0, num_images=1, seed=0, aspect_ratio="auto", resolution="1K",
quality="high", enable_web_search=False, thinking_level="off", acceleration="none"): # Hardcoded to none, kept for compatibility
if fal_key == "your_fal_key_here":
raise ValueError("Please set your fal.ai API key in the node.")
# Collect all non-None images
image_inputs = [image1, image2, image3, image4, image5, image6, image7, image8, image9, image10]
images = [img for img in image_inputs if img is not None]
if not images:
raise ValueError("At least one image input must be connected.")
# Convert each to PIL and encode
img_data_uris = []
@@ -89,16 +111,15 @@ class NanoSeedEdit:
# For Flux and Qwen, we usually send image_size in payload, but resizing here
# ensures consistent aspect ratio calculation before sending if needed.
# Nano models ignore this as per original code.
if custom_size:
if model in ["nano_banana", "nano_banana_pro", "nano_banana_2"]:
pass
else:
pil_image = pil_image.resize((width, height), Image.LANCZOS)
buffer = BytesIO()
pil_image.save(buffer, format="PNG")
img_str = base64.b64encode(buffer.getvalue()).decode()
img_data_uris.append(f"data:image/png;base64,{img_str}")
if custom_size:
if model in ["nano_banana", "nano_banana_pro", "nano_banana_2"]:
pass
else:
pil_image = pil_image.resize((width, height), Image.LANCZOS)
img_data_uri = pil2data_uri(pil_image)
if img_data_uri is not None:
img_data_uris.append(img_data_uri)
# Enforce limits (Updated: Removed Flux 2 single image limit)
if model == "seedream_4.5" and len(img_data_uris) + num_images > 15:
@@ -135,16 +156,33 @@ class NanoSeedEdit:
"seed": seed,
"aspect_ratio": aspect_ratio,
"resolution": resolution,
"output_format": "png",
"enable_web_search": enable_web_search,
"limit_generations": True,
"sync_mode": True,
}
if thinking_level != "off":
payload["thinking_level"] = thinking_level
elif model == "grok_imagine_edit":
url = "https://fal.run/xai/grok-imagine-image/edit"
payload = {
"output_format": "png",
"enable_web_search": enable_web_search,
"limit_generations": True,
"safety_tolerance": "6",
"sync_mode": True,
}
if thinking_level != "off":
payload["thinking_level"] = thinking_level
elif model == "gpt_image_2_edit":
url = "https://fal.run/openai/gpt-image-2/edit"
payload = {
"prompt": prompt,
"image_urls": img_data_uris,
"quality": quality,
"num_images": num_images,
"output_format": "png",
"sync_mode": True,
}
if custom_size:
payload["image_size"] = {"width": width, "height": height}
if mask is not None:
mask_data_uri = tensor2data_uri(mask)
if mask_data_uri is not None:
payload["mask_image_url"] = mask_data_uri
elif model == "grok_imagine_edit":
url = "https://fal.run/xai/grok-imagine-image/edit"
payload = {
"prompt": prompt,
"image_urls": img_data_uris[:3],
"num_images": min(num_images, 4),