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import nodes |
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import folder_paths |
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from fcbh.cli_args import args |
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from PIL import Image |
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import numpy as np |
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import json |
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import os |
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MAX_RESOLUTION = nodes.MAX_RESOLUTION |
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class ImageCrop: |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": { "image": ("IMAGE",), |
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"width": ("INT", {"default": 512, "min": 1, "max": MAX_RESOLUTION, "step": 1}), |
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"height": ("INT", {"default": 512, "min": 1, "max": MAX_RESOLUTION, "step": 1}), |
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"x": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}), |
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"y": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}), |
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}} |
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RETURN_TYPES = ("IMAGE",) |
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FUNCTION = "crop" |
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CATEGORY = "image/transform" |
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def crop(self, image, width, height, x, y): |
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x = min(x, image.shape[2] - 1) |
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y = min(y, image.shape[1] - 1) |
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to_x = width + x |
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to_y = height + y |
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img = image[:,y:to_y, x:to_x, :] |
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return (img,) |
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class RepeatImageBatch: |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": { "image": ("IMAGE",), |
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"amount": ("INT", {"default": 1, "min": 1, "max": 64}), |
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}} |
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RETURN_TYPES = ("IMAGE",) |
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FUNCTION = "repeat" |
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CATEGORY = "image/batch" |
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def repeat(self, image, amount): |
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s = image.repeat((amount, 1,1,1)) |
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return (s,) |
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class SaveAnimatedWEBP: |
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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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methods = {"default": 4, "fastest": 0, "slowest": 6} |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": |
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{"images": ("IMAGE", ), |
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"filename_prefix": ("STRING", {"default": "fcbh_backend"}), |
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"fps": ("FLOAT", {"default": 6.0, "min": 0.01, "max": 1000.0, "step": 0.01}), |
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"lossless": ("BOOLEAN", {"default": True}), |
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"quality": ("INT", {"default": 80, "min": 0, "max": 100}), |
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"method": (list(s.methods.keys()),), |
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}, |
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"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}, |
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} |
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RETURN_TYPES = () |
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FUNCTION = "save_images" |
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OUTPUT_NODE = True |
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CATEGORY = "_for_testing" |
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def save_images(self, images, fps, filename_prefix, lossless, quality, method, num_frames=0, prompt=None, extra_pnginfo=None): |
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method = self.methods.get(method, "aoeu") |
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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, images[0].shape[1], images[0].shape[0]) |
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results = list() |
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pil_images = [] |
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for image in images: |
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i = 255. * image.cpu().numpy() |
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img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8)) |
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pil_images.append(img) |
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metadata = None |
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if not args.disable_metadata: |
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metadata = pil_images[0].getexif() |
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if prompt is not None: |
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metadata[0x0110] = "prompt:{}".format(json.dumps(prompt)) |
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if extra_pnginfo is not None: |
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inital_exif = 0x010f |
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for x in extra_pnginfo: |
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metadata[inital_exif] = "{}:{}".format(x, json.dumps(extra_pnginfo[x])) |
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inital_exif -= 1 |
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if num_frames == 0: |
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num_frames = len(pil_images) |
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c = len(pil_images) |
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for i in range(0, c, num_frames): |
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file = f"{filename}_{counter:05}_.webp" |
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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) |
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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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animated = num_frames != 1 |
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return { "ui": { "images": results, "animated": (animated,) } } |
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NODE_CLASS_MAPPINGS = { |
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"ImageCrop": ImageCrop, |
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"RepeatImageBatch": RepeatImageBatch, |
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"SaveAnimatedWEBP": SaveAnimatedWEBP, |
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} |
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