💾 CR Image Output¶
Documentation¶
- Class name:
CR Image Output - Category:
🧩 Comfyroll Studio/✨ Essential/📦 Core - Output node:
True
The CR Image Output node is designed to facilitate the output of images within a computational graph, providing a streamlined way to export, display, or further process images generated or modified by preceding nodes. It abstracts the complexities involved in handling image data, ensuring that images are appropriately formatted and ready for use or display.
Input types¶
Required¶
images- The 'images' parameter represents the image data to be outputted. It plays a crucial role in determining the content and format of the output, affecting how images are processed and presented in the final output.
- Comfy dtype:
IMAGE - Python dtype:
torch.Tensor
output_type- Specifies the type of output operation to perform with the images, such as saving to disk or displaying.
- Comfy dtype:
COMBO[STRING] - Python dtype:
str
filename_prefix- A prefix to be added to the filenames of saved images, allowing for organized and identifiable output.
- Comfy dtype:
STRING - Python dtype:
str
prefix_presets- Predefined prefix options that can be selected for convenience and standardization.
- Comfy dtype:
COMBO[STRING] - Python dtype:
List[str]
file_format- The format in which the images will be saved, such as PNG or JPEG.
- Comfy dtype:
COMBO[STRING] - Python dtype:
str
Optional¶
trigger- A control signal that triggers the output operation, ensuring that images are processed and saved/displayed at the correct time.
- Comfy dtype:
BOOLEAN - Python dtype:
bool
Output types¶
trigger- Comfy dtype:
BOOLEAN - Indicates the completion of the output operation, potentially used to trigger subsequent nodes in the computational graph.
- Python dtype:
bool
- Comfy dtype:
Usage tips¶
- Infra type:
GPU - Common nodes: unknown
Source code¶
class CR_ImageOutput:
def __init__(self):
self.output_dir = folder_paths.get_output_directory()
self.type = "output"
@classmethod
def INPUT_TYPES(cls):
presets = ["None", "yyyyMMdd"]
return {"required":
{"images": ("IMAGE", ),
"output_type": (["Preview", "Save", "UI (no batch)"],),
"filename_prefix": ("STRING", {"default": "CR"}),
"prefix_presets": (presets, ),
"file_format": (["png", "jpg", "webp", "tif"],),
},
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
"optional":
{"trigger": ("BOOLEAN", {"default": False},),
}
}
RETURN_TYPES = ("BOOLEAN", )
RETURN_NAMES = ("trigger", )
FUNCTION = "save_images"
OUTPUT_NODE = True
CATEGORY = icons.get("Comfyroll/Essential/Core")
def save_images(self, images, file_format, prefix_presets, filename_prefix="CR",
trigger=False, output_type="Preview", prompt=None, extra_pnginfo=None):
show_help = "https://github.com/Suzie1/ComfyUI_Comfyroll_CustomNodes/wiki/Core-Nodes#cr-image-output"
def map_filename(filename):
prefix_len = len(os.path.basename(filename_prefix))
prefix = filename[:prefix_len + 1]
try:
digits = int(filename[prefix_len + 1:].split('_')[0])
except:
digits = 0
return (digits, prefix)
if output_type == "Save":
self.output_dir = folder_paths.get_output_directory()
self.type = "output"
elif output_type == "Preview":
self.output_dir = folder_paths.get_temp_directory()
self.type = "temp"
date_formats = {
'yyyyMMdd': lambda d: '{}{:02d}{:02d}'.format(str(d.year), d.month, d.day),
}
current_datetime = datetime.datetime.now()
for format_key, format_lambda in date_formats.items():
preset_prefix = f"{format_lambda(current_datetime)}"
if prefix_presets != "None":
filename_prefix = filename_prefix + "_" + preset_prefix
if filename_prefix[0] == "_":
filename_prefix = filename_prefix[1:]
subfolder = os.path.dirname(os.path.normpath(filename_prefix))
filename = os.path.basename(os.path.normpath(filename_prefix))
full_output_folder = os.path.join(self.output_dir, subfolder)
if os.path.commonpath((self.output_dir, os.path.abspath(full_output_folder))) != self.output_dir:
return {}
try:
counter = max(filter(lambda a: a[1][:-1] == filename and a[1][-1] == "_", map(map_filename, os.listdir(full_output_folder))))[0] + 1
except ValueError:
counter = 1
except FileNotFoundError:
os.makedirs(full_output_folder, exist_ok=True)
counter = 1
if output_type == "UI (no batch)":
# based on ETN_SendImageWebSocket
results = []
for tensor in images:
array = 255.0 * tensor.cpu().numpy()
image = Image.fromarray(np.clip(array, 0, 255).astype(np.uint8))
server = PromptServer.instance
server.send_sync(
BinaryEventTypes.UNENCODED_PREVIEW_IMAGE,
["PNG", image, None],
server.client_id,
)
results.append(
{"source": "websocket", "content-type": "image/png", "type": "output"}
)
return {"ui": {"images": results}}
else:
results = list()
for image in images:
i = 255. * image.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
metadata = PngInfo()
if prompt is not None:
metadata.add_text("prompt", json.dumps(prompt))
if extra_pnginfo is not None:
for x in extra_pnginfo:
metadata.add_text(x, json.dumps(extra_pnginfo[x]))
file_name = f"{filename}_{counter:05}_.{file_format}"
img_params = {'png': {'compress_level': 4},
'webp': {'method': 6, 'lossless': False, 'quality': 80},
'jpg': {'format': 'JPEG'},
'tif': {'format': 'TIFF'}
}
resolved_image_path = os.path.join(full_output_folder, file_name)
img.save(resolved_image_path, **img_params[file_format], pnginfo=metadata)
results.append({
"filename": file_name,
"subfolder": subfolder,
"type": self.type
})
counter += 1
return { "ui": { "images": results }, "result": (trigger, show_help,) }