77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
checkPointUuidMap = {
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"星流Star-3 Alpha文生图": "5d7e67009b344550bc1aa6ccbfa1d7f4",
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"星流Star-3 Alpha图生图": "07e00af4fc464c7ab55ff906f8acf1b7",
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"F.1文生图": "6f7c4652458d4802969f8d089cf5b91f",
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"F.1图生图": "63b72710c9574457ba303d9d9b8df8bd",
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}
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vad_map = {
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'Automatic': '',
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'1.5 - vae-ft-mse-840000-ema-pruned.safetensors': '2c1a337416e029dd65ab58784e8a4763',
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'1.5 - klF8Anime2VAE_klF8Anime2VAE.ckpt': 'd4a03b32d8d59552194a9453297180c1',
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'1.5 - color101VAE_v1.pt': 'd9be20ad5a7195ff0d97925e5afc7912',
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'1.5 - cute vae.safetensors': '88ae7501f5194e691a1dc32d6f7c6f1a',
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'1.5 - ClearVAE_V2.3.safetensors': '73f6e055eade7a85bda2856421d786fe',
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'1.5 - difconsistencyRAWVAE_v10.pt': '5e93d0d2a64143a9d28988e75f28cb29',
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'XL - sd_xl_vae_1.0': '3cefd3e4af2b8effb230b960da41a980',
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}
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lora_map = {
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"人像摄影 - 基础算法 F.1 - Filmfotos_日系胶片写真": "b59f7eb734864a74ba476af3aa28c2f3",
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"人像摄影 - 基础算法 F.1 - 极氪白白酱F.1-人像V6MAX": "169505112cee468b95d5e4a5db0e5669",
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"电商场景 - 基础算法 F.1 - 电商-F.1- | 运营启动页": "76af914cc3434937aa13aeb038aae838",
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"视觉海报 - 基础算法 F.1 - UNIT-F.1-MandelaEffect-LoRA": "50284151e507431facc2325cd62f73a3",
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"创意插画 - 基础算法 F.1 - 万物调节丨Flux 情绪插画": "be3909c5d7114d3b8717e966c884d3e1",
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"创意插画 - 基础算法 F.1 - 嘉嘉_国潮插画_F.1": "be3909c5d7114d3b8717e966c884d3e1",
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"创意插画 - 基础算法 F.1 - 风月无边illustrations": "be3909c5d7114d3b8717e966c884d3e1",
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"创意插画 - 基础算法 F.1 - 岩彩材质绘画": "be3909c5d7114d3b8717e966c884d3e1",
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}
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upscaler_map = {
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"Latent": 0,
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"Latent (antialiased)": 1,
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"Latent (bicubic)": 2,
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"Latent (bicubic antialiased)": 3,
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"Latent (nearest)": 4,
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"Latent (nearest-exact)": 5,
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"Lanczos": 6,
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"Nearest": 7,
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"ESRGAN_4x": 8,
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"LDSR": 9,
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"R-ESRGAN_4x+": 10,
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"R-ESRGAN_4x+ Anime6B": 11,
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"ScuNET GAN": 12,
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"ScuNET PSNR": 13,
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"SwinIR_4x": 14,
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"4x-UltraSharp": 15,
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"8x-NMKD-Superscale": 16,
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"4x_NMKD-Siax_200k": 17,
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"4x_NMKD-Superscale-SP_178000_G": 18,
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"4x-AnimeSharp": 19,
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"4x_foolhardy_Remacri": 20,
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"BSRGAN": 21,
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"DAT 2": 22,
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"DAT 3": 23,
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"DAT 4": 24,
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"4x-DeCompress": 25,
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"4x-DeCompress Strong": 26,
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}
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def get_vad_uuid_by_vad_name(vad_name):
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return vad_map[vad_name]
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def get_check_point(check_point_name):
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return checkPointUuidMap[check_point_name]
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def get_lora(lora_name):
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return lora_map[lora_name]
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def get_upscaler(upscaler_name):
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return upscaler_map[upscaler_name]
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def get_upscaler_keys():
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return upscaler_map.keys()
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