56 lines
1.6 KiB
Markdown
56 lines
1.6 KiB
Markdown
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# Documentation
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- Class name: SAMEmbeddingToImage
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- Category: Art Venture/Segmentation
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- Output node: False
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SAMEmbeddingToImage节点用于将SAM嵌入转换为可视化表示，从而实现对嵌入数据的直观解释和操作。它将嵌入中包含的复杂信息抽象为更易于理解的图像格式。
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# Input types
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## Required
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- embedding
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- embedding参数代表需要转换为图像的SAM嵌入。这个嵌入至关重要，因为它包含了将被可视化为图像的编码信息。
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- Comfy dtype: SAM_EMBEDDING
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- Python dtype: np.ndarray
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# Output types
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- image
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- 输出是从SAM嵌入生成的图像，允许对编码信息进行可视化和进一步处理。
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- Comfy dtype: IMAGE
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- Python dtype: Tuple[torch.Tensor]
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class SAMEmbeddingToImage:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"embedding": ("SAM_EMBEDDING",),
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},
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}
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RETURN_TYPES = ("IMAGE",)
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CATEGORY = "Art Venture/Segmentation"
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FUNCTION = "sam_embedding_to_noise_image"
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def sam_embedding_to_noise_image(self, embedding: np.ndarray):
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# Flatten the array to a 1D array
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flat_arr = embedding.flatten()
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# Convert the 1D array to bytes
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bytes_arr = flat_arr.astype(np.float32).tobytes()
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# Convert bytes to RGBA PIL Image
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size = (embedding.shape[1] * 4, int(embedding.shape[2] * embedding.shape[3] / 4))
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img = Image.frombytes("RGBA", size, bytes_arr)
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return (pil2tensor(img),)
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```
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