68 lines
2.2 KiB
Markdown
68 lines
2.2 KiB
Markdown
|
|
# Documentation
|
|
- Class name: SampleColorHSV
|
|
- Category: Bmad/CV/Color A.
|
|
- Output node: False
|
|
|
|
SampleColorHSV节点旨在从RGB图像中抽样像素并将这些样本转换为HSV颜色空间。它通过提供HSV格式的图像颜色分布代表性子集，来促进图像内色彩信息的分析和操作。
|
|
|
|
# Input types
|
|
## Required
|
|
- rgb_image
|
|
- 将被抽样的RGB图像。这是生成HSV格式的颜色信息子集的主要输入。
|
|
- Comfy dtype: IMAGE
|
|
- Python dtype: torch.Tensor
|
|
- sample_size
|
|
- 决定从RGB图像中抽样的像素数量。更大的样本量能提供更具代表性的图像颜色分布子集。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
- sampling_seed
|
|
- 用于抽样像素的随机数生成器的种子值。这确保了在不同运行中抽样子集的可重复性。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
|
|
# Output types
|
|
- hsv_samples
|
|
- 输出是一组从RGB转换为HSV颜色空间的抽样像素，为进一步的颜色分析或操作提供基础。
|
|
- Comfy dtype: HSV_SAMPLES
|
|
- Python dtype: tuple
|
|
|
|
|
|
## Usage tips
|
|
- Infra type: `GPU`
|
|
- Common nodes: unknown
|
|
|
|
|
|
## Source code
|
|
```python
|
|
class SampleColorHSV:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
import sys
|
|
return {"required": {
|
|
"rgb_image": ("IMAGE",),
|
|
"sample_size": ("INT", {"default": 1000, "min": 1, "max": 256 * 256, }),
|
|
"sampling_seed": ("INT", {"default": 0, "min": 0, "max": sys.maxsize, "step": 1})
|
|
}}
|
|
|
|
RETURN_TYPES = ("HSV_SAMPLES",)
|
|
FUNCTION = "sample"
|
|
CATEGORY = "Bmad/CV/Color A."
|
|
|
|
def sample(self, rgb_image, sample_size, sampling_seed):
|
|
image = tensor2opencv(rgb_image, 3)
|
|
image_width = image.shape[1]
|
|
|
|
# sample pixels
|
|
np.random.seed(sampling_seed)
|
|
random_indices = np.random.choice(image.shape[0] * image_width, sample_size, replace=False)
|
|
sample_pixels = np.array([image[i // image_width, i % image_width] for i in random_indices])
|
|
sample_pixels = sample_pixels.reshape((1, -1, 3))
|
|
|
|
# only convert samples to HSV
|
|
sample_pixels_hsv = cv.cvtColor(sample_pixels, cv.COLOR_RGB2HSV)
|
|
samples_object = HSV_Samples(sample_pixels_hsv[0, :, :])
|
|
return (samples_object,)
|
|
|
|
```
|