# Documentation - Class name: WAS_Image_Bloom_Filter - Category: WAS Suite/Image/Filter - Output node: False - Repo Ref: https://github.com/WASasquatch/was-node-suite-comfyui WAS_Image_Bloom_Filter节点对图像应用了一种bloom效果,通过模拟光线的散射来增强其视觉吸引力。它调整图像的亮度以创建发光效果,这对于各种图像处理任务非常有用。 # Input types ## Required - image - 将应用bloom滤镜的输入图像。它是节点处理的主要对象,直接影响最终输出。 - Comfy dtype: IMAGE - Python dtype: PIL.Image.Image ## Optional - radius - 半径参数控制用于创建bloom效果的高斯模糊的范围。它是确定bloom柔和度的重要因素。 - Comfy dtype: FLOAT - Python dtype: float - intensity - 强度参数调整bloom效果的亮度。较高的值会导致更明显的bloom,而较低的值则产生更微妙的效果。 - Comfy dtype: FLOAT - Python dtype: float # Output types - output_image - output_image是应用了bloom滤镜的处理后的图像。它代表了节点操作的最终视觉结果。 - Comfy dtype: IMAGE - Python dtype: torch.Tensor # Usage tips - Infra type: CPU # Source code ``` class WAS_Image_Bloom_Filter: def __init__(self): pass @classmethod def INPUT_TYPES(cls): return {'required': {'image': ('IMAGE',), 'radius': ('FLOAT', {'default': 10, 'min': 0.0, 'max': 1024, 'step': 0.1}), 'intensity': ('FLOAT', {'default': 1, 'min': 0.0, 'max': 1.0, 'step': 0.1})}} RETURN_TYPES = ('IMAGE',) FUNCTION = 'image_bloom' CATEGORY = 'WAS Suite/Image/Filter' def image_bloom(self, image, radius=0.5, intensity=1.0): return (pil2tensor(self.apply_bloom_filter(tensor2pil(image), radius, intensity)),) def apply_bloom_filter(self, input_image, radius, bloom_factor): blurred_image = input_image.filter(ImageFilter.GaussianBlur(radius=radius)) high_pass_filter = ImageChops.subtract(input_image, blurred_image) bloom_filter = high_pass_filter.filter(ImageFilter.GaussianBlur(radius=radius * 2)) bloom_filter = ImageEnhance.Brightness(bloom_filter).enhance(2.0) bloom_filter = ImageChops.multiply(bloom_filter, Image.new('RGB', input_image.size, (int(255 * bloom_factor), int(255 * bloom_factor), int(255 * bloom_factor)))) blended_image = ImageChops.screen(input_image, bloom_filter) return blended_image ```