From 2f60b4aa0f42107be52d6f2280deba71877fed0c Mon Sep 17 00:00:00 2001 From: engineer6980 Date: Sat, 31 Jan 2026 21:38:37 +0800 Subject: [PATCH] =?UTF-8?q?=E5=A2=9E=E5=8A=A0=E8=A7=A3=E7=A0=81=E8=8A=82?= =?UTF-8?q?=E7=82=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- __init__.py | 8 ++----- cipher_nodes.py | 63 ++++++++++++++++++++----------------------------- readme.md | 2 +- 3 files changed, 29 insertions(+), 44 deletions(-) diff --git a/__init__.py b/__init__.py index 3d41e76..128e1e5 100644 --- a/__init__.py +++ b/__init__.py @@ -1,17 +1,13 @@ -# 导入你写的节点类 from .cipher_nodes import ImageCipherEncode, ImageCipherDecode -# 建立 ComfyUI 内部识别名与 Python 类的映射 NODE_CLASS_MAPPINGS = { "ImageCipherEncode": ImageCipherEncode, "ImageCipherDecode": ImageCipherDecode } -# 建立节点在 UI 界面显示的中文/英文名称 NODE_DISPLAY_NAME_MAPPINGS = { - "ImageCipherEncode": "🔒 RGB 行交织加密", - "ImageCipherDecode": "🔓 RGB 行交织解密" + "ImageCipherEncode": "🔒 Cipher Encode (Color Noise)", + "ImageCipherDecode": "🔓 Cipher Decode (Preview)" } -# 必须导出这两个变量 __all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS'] \ No newline at end of file diff --git a/cipher_nodes.py b/cipher_nodes.py index 12aaa3b..1e8f4e4 100644 --- a/cipher_nodes.py +++ b/cipher_nodes.py @@ -1,7 +1,7 @@ import torch # ========================================== -# 🔑 固定密钥：前端和PyCharm必须使用同一个数字 +# 🔑 全局密钥：必须保持一致 # ========================================== SECRET_KEY = 999 @@ -14,68 +14,59 @@ class ImageCipherEncode: def INPUT_TYPES(s): return { "required": { - # 输入标准 VAE 解码后的图像 "images": ("IMAGE",), } } RETURN_TYPES = ("IMAGE",) - RETURN_NAMES = ("cipher_color_noise",) + RETURN_NAMES = ("cipher_image",) FUNCTION = "encode" CATEGORY = "CipherTools" def encode(self, images): - # images shape: [Batch, Height, Width, Channel=3] batch, h, w, c = images.shape out_list = [] - - # 使用固定密钥作为基础偏移量 base_shift = SECRET_KEY for i in range(batch): - img = images[i] # [H, W, 3] + img = images[i] - # 1. 拆分三个通道，它们现在的形状都是 [H, W] - r_plane = img[:, :, 0] - g_plane = img[:, :, 1] - b_plane = img[:, :, 2] + # 分离通道 + r = img[:, :, 0] + g = img[:, :, 1] + b = img[:, :, 2] - # 准备加密容器 - r_encrypted = torch.zeros_like(r_plane) - g_encrypted = torch.zeros_like(g_plane) - b_encrypted = torch.zeros_like(b_plane) + # 准备容器 + r_enc = torch.zeros_like(r) + g_enc = torch.zeros_like(g) + b_enc = torch.zeros_like(b) - # 2. 核心加密循环：对每一行进行不同程度的位移 + # 加密循环：正向位移 (shifts=正数) for y in range(h): - # 关键点：R, G, B 使用不同的倍率 (1, 2, 3)，确保它们错开 - # 计算 R 通道当前行的位移量 shift_r = (y * base_shift * 1) % w - r_encrypted[y, :] = torch.roll(r_plane[y, :], shifts=shift_r, dims=0) - - # 计算 G 通道当前行的位移量 (倍率不同) shift_g = (y * base_shift * 2) % w - g_encrypted[y, :] = torch.roll(g_plane[y, :], shifts=shift_g, dims=0) - - # 计算 B 通道当前行的位移量 (倍率不同) shift_b = (y * base_shift * 3) % w - b_encrypted[y, :] = torch.roll(b_plane[y, :], shifts=shift_b, dims=0) - # 3. 重新组合成彩色图像 [H, W, 3] - # 此时 R,G,B 已经完全错位，图像看起来是彩色噪点 - encrypted_img = torch.stack((r_encrypted, g_encrypted, b_encrypted), dim=-1) - out_list.append(encrypted_img) + r_enc[y, :] = torch.roll(r[y, :], shifts=shift_r, dims=0) + g_enc[y, :] = torch.roll(g[y, :], shifts=shift_g, dims=0) + b_enc[y, :] = torch.roll(b[y, :], shifts=shift_b, dims=0) + + out_list.append(torch.stack((r_enc, g_enc, b_enc), dim=-1)) return (torch.stack(out_list, dim=0),) -# 解密节点（仅供 ComfyUI 内部测试用，实际业务在前端完成） class ImageCipherDecode: def __init__(self): pass @classmethod def INPUT_TYPES(s): - return {"required": {"images": ("IMAGE",), }} + return { + "required": { + "images": ("IMAGE",), + } + } RETURN_TYPES = ("IMAGE",) RETURN_NAMES = ("restored_image",) @@ -89,7 +80,7 @@ class ImageCipherDecode: for i in range(batch): img = images[i] - # 1. 拆分加密后的通道 + r_enc = img[:, :, 0] g_enc = img[:, :, 1] b_enc = img[:, :, 2] @@ -98,19 +89,17 @@ class ImageCipherDecode: g_dec = torch.zeros_like(g_enc) b_dec = torch.zeros_like(b_enc) - # 2. 反向操作：向相反方向回滚 + # 解密循环：反向位移 (shifts=负数) for y in range(h): - # 计算加密时用的位移量 shift_r = (y * base_shift * 1) % w shift_g = (y * base_shift * 2) % w shift_b = (y * base_shift * 3) % w - # 使用负数 shifts 进行反向滚动 + # 注意这里的负号 -shift r_dec[y, :] = torch.roll(r_enc[y, :], shifts=-shift_r, dims=0) g_dec[y, :] = torch.roll(g_enc[y, :], shifts=-shift_g, dims=0) b_dec[y, :] = torch.roll(b_enc[y, :], shifts=-shift_b, dims=0) - restored_img = torch.stack((r_dec, g_dec, b_dec), dim=-1) - out_list.append(restored_img) + out_list.append(torch.stack((r_dec, g_dec, b_dec), dim=-1)) return (torch.stack(out_list, dim=0),) \ No newline at end of file diff --git a/readme.md b/readme.md index 3372f03..212ede7 100644 --- a/readme.md +++ b/readme.md @@ -26,4 +26,4 @@ - **G 通道位移量**: `(y * KEY * 2) % width` - **B 通道位移量**: `(y * KEY * 3) % width` -*详细的前端 JS 代码示例请参考仓库内的说明或联系作者。* \ No newline at end of file +*可通过本地使用ComfyUI_RH_APICall节点调用RH上的工作流，最终在本地完成图片输出* \ No newline at end of file