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import nodes | |
import folder_paths | |
from comfy.cli_args import args | |
from PIL import Image | |
from PIL.PngImagePlugin import PngInfo | |
import numpy as np | |
import json | |
import os | |
MAX_RESOLUTION = nodes.MAX_RESOLUTION | |
class ImageCrop: | |
def INPUT_TYPES(s): | |
return {"required": { "image": ("IMAGE",), | |
"width": ("INT", {"default": 512, "min": 1, "max": MAX_RESOLUTION, "step": 1}), | |
"height": ("INT", {"default": 512, "min": 1, "max": MAX_RESOLUTION, "step": 1}), | |
"x": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}), | |
"y": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}), | |
}} | |
RETURN_TYPES = ("IMAGE",) | |
FUNCTION = "crop" | |
CATEGORY = "image/transform" | |
def crop(self, image, width, height, x, y): | |
x = min(x, image.shape[2] - 1) | |
y = min(y, image.shape[1] - 1) | |
to_x = width + x | |
to_y = height + y | |
img = image[:,y:to_y, x:to_x, :] | |
return (img,) | |
class RepeatImageBatch: | |
def INPUT_TYPES(s): | |
return {"required": { "image": ("IMAGE",), | |
"amount": ("INT", {"default": 1, "min": 1, "max": 4096}), | |
}} | |
RETURN_TYPES = ("IMAGE",) | |
FUNCTION = "repeat" | |
CATEGORY = "image/batch" | |
def repeat(self, image, amount): | |
s = image.repeat((amount, 1,1,1)) | |
return (s,) | |
class ImageFromBatch: | |
def INPUT_TYPES(s): | |
return {"required": { "image": ("IMAGE",), | |
"batch_index": ("INT", {"default": 0, "min": 0, "max": 4095}), | |
"length": ("INT", {"default": 1, "min": 1, "max": 4096}), | |
}} | |
RETURN_TYPES = ("IMAGE",) | |
FUNCTION = "frombatch" | |
CATEGORY = "image/batch" | |
def frombatch(self, image, batch_index, length): | |
s_in = image | |
batch_index = min(s_in.shape[0] - 1, batch_index) | |
length = min(s_in.shape[0] - batch_index, length) | |
s = s_in[batch_index:batch_index + length].clone() | |
return (s,) | |
class SaveAnimatedWEBP: | |
def __init__(self): | |
self.output_dir = folder_paths.get_output_directory() | |
self.type = "output" | |
self.prefix_append = "" | |
methods = {"default": 4, "fastest": 0, "slowest": 6} | |
def INPUT_TYPES(s): | |
return {"required": | |
{"images": ("IMAGE", ), | |
"filename_prefix": ("STRING", {"default": "ComfyUI"}), | |
"fps": ("FLOAT", {"default": 6.0, "min": 0.01, "max": 1000.0, "step": 0.01}), | |
"lossless": ("BOOLEAN", {"default": True}), | |
"quality": ("INT", {"default": 80, "min": 0, "max": 100}), | |
"method": (list(s.methods.keys()),), | |
# "num_frames": ("INT", {"default": 0, "min": 0, "max": 8192}), | |
}, | |
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}, | |
} | |
RETURN_TYPES = () | |
FUNCTION = "save_images" | |
OUTPUT_NODE = True | |
CATEGORY = "image/animation" | |
def save_images(self, images, fps, filename_prefix, lossless, quality, method, num_frames=0, prompt=None, extra_pnginfo=None): | |
method = self.methods.get(method) | |
filename_prefix += self.prefix_append | |
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0]) | |
results = list() | |
pil_images = [] | |
for image in images: | |
i = 255. * image.cpu().numpy() | |
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8)) | |
pil_images.append(img) | |
metadata = pil_images[0].getexif() | |
if not args.disable_metadata: | |
if prompt is not None: | |
metadata[0x0110] = "prompt:{}".format(json.dumps(prompt)) | |
if extra_pnginfo is not None: | |
inital_exif = 0x010f | |
for x in extra_pnginfo: | |
metadata[inital_exif] = "{}:{}".format(x, json.dumps(extra_pnginfo[x])) | |
inital_exif -= 1 | |
if num_frames == 0: | |
num_frames = len(pil_images) | |
c = len(pil_images) | |
for i in range(0, c, num_frames): | |
file = f"{filename}_{counter:05}_.webp" | |
pil_images[i].save(os.path.join(full_output_folder, file), save_all=True, duration=int(1000.0/fps), append_images=pil_images[i + 1:i + num_frames], exif=metadata, lossless=lossless, quality=quality, method=method) | |
results.append({ | |
"filename": file, | |
"subfolder": subfolder, | |
"type": self.type | |
}) | |
counter += 1 | |
animated = num_frames != 1 | |
return { "ui": { "images": results, "animated": (animated,) } } | |
class SaveAnimatedPNG: | |
def __init__(self): | |
self.output_dir = folder_paths.get_output_directory() | |
self.type = "output" | |
self.prefix_append = "" | |
def INPUT_TYPES(s): | |
return {"required": | |
{"images": ("IMAGE", ), | |
"filename_prefix": ("STRING", {"default": "ComfyUI"}), | |
"fps": ("FLOAT", {"default": 6.0, "min": 0.01, "max": 1000.0, "step": 0.01}), | |
"compress_level": ("INT", {"default": 4, "min": 0, "max": 9}) | |
}, | |
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}, | |
} | |
RETURN_TYPES = () | |
FUNCTION = "save_images" | |
OUTPUT_NODE = True | |
CATEGORY = "image/animation" | |
def save_images(self, images, fps, compress_level, filename_prefix="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, images[0].shape[1], images[0].shape[0]) | |
results = list() | |
pil_images = [] | |
for image in images: | |
i = 255. * image.cpu().numpy() | |
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8)) | |
pil_images.append(img) | |
metadata = None | |
if not args.disable_metadata: | |
metadata = PngInfo() | |
if prompt is not None: | |
metadata.add(b"comf", "prompt".encode("latin-1", "strict") + b"\0" + json.dumps(prompt).encode("latin-1", "strict"), after_idat=True) | |
if extra_pnginfo is not None: | |
for x in extra_pnginfo: | |
metadata.add(b"comf", x.encode("latin-1", "strict") + b"\0" + json.dumps(extra_pnginfo[x]).encode("latin-1", "strict"), after_idat=True) | |
file = f"{filename}_{counter:05}_.png" | |
pil_images[0].save(os.path.join(full_output_folder, file), pnginfo=metadata, compress_level=compress_level, save_all=True, duration=int(1000.0/fps), append_images=pil_images[1:]) | |
results.append({ | |
"filename": file, | |
"subfolder": subfolder, | |
"type": self.type | |
}) | |
return { "ui": { "images": results, "animated": (True,)} } | |
NODE_CLASS_MAPPINGS = { | |
"ImageCrop": ImageCrop, | |
"RepeatImageBatch": RepeatImageBatch, | |
"ImageFromBatch": ImageFromBatch, | |
"SaveAnimatedWEBP": SaveAnimatedWEBP, | |
"SaveAnimatedPNG": SaveAnimatedPNG, | |
} | |