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import os |
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import random |
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import numpy as np |
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import gradio as gr |
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import base64 |
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from io import BytesIO |
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import PIL.Image |
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from typing import Tuple |
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from novita_client import NovitaClient, InstantIDControlnetUnit, InstantIDLora |
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from time import time |
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import datetime |
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from style_template import styles |
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MAX_SEED = np.iinfo(np.int32).max |
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STYLE_NAMES = list(styles.keys()) |
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DEFAULT_STYLE_NAME = '(No style)' |
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DEFAULT_MODEL_NAME = 'sdxlUnstableDiffusers_v8HEAVENSWRATH_133813' |
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enable_lcm_arg = False |
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face_adapter = f'./checkpoints/ip-adapter.bin' |
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controlnet_path = f'./checkpoints/ControlNetModel' |
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controlnet_pose_model = 'thibaud/controlnet-openpose-sdxl-1.0' |
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controlnet_canny_model = 'diffusers/controlnet-canny-sdxl-1.0' |
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controlnet_depth_model = 'diffusers/controlnet-depth-sdxl-1.0-small' |
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SDXL_MODELS = [ |
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"albedobaseXL_v04_130099", |
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"altxl_v60_146691", |
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"animagineXLV3_v30_231047", |
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"animeArtDiffusionXL_alpha2_91872", |
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"animeArtDiffusionXL_alpha3_93120", |
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"animeIllustDiffusion_v04_117809", |
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"breakdomainxl_V05g_124265", |
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"brixlAMustInYour_v40Dagobah_145992", |
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"cinemaxAlphaSDXLCinema_alpha1_107473", |
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"cineroXLPhotomatic_v12aPHENO_137703", |
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"clearhungAnimeXL_v10_117716", |
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"copaxTimelessxlSDXL1_colorfulV2_100729", |
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"counterfeitxl_v10_108721", |
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"counterfeitxl__98184", |
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"crystalClearXL_ccxl_97637", |
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"dreamshaperXL09Alpha_alpha2Xl10_91562", |
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"dynavisionXLAllInOneStylized_alpha036FP16Bakedvae_99980", |
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"dynavisionXLAllInOneStylized_beta0411Bakedvae_109970", |
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"dynavisionXLAllInOneStylized_release0534bakedvae_129001", |
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"fenrisxl_145_134980", |
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"foddaxlPhotorealism_v45_122788", |
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"formulaxl_v10_104889", |
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"juggernautXL_v8Rundiffusion_227002", |
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"juggernautXL_version2_113240", |
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"juggernautXL_version5_126522", |
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"kohakuXL_alpha7_111843", |
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"LahMysteriousSDXL_v40_122478", |
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"leosamsHelloworldSDXLModel_helloworldSDXL10_112178", |
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"leosamsHelloworldSDXL_helloworldSDXL50_268813", |
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"mbbxlUltimate_v10RC_94686", |
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"moefusionSDXL_v10_114018", |
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"nightvisionXLPhotorealisticPortrait_beta0681Bakedvae_108833", |
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"nightvisionXLPhotorealisticPortrait_beta0702Bakedvae_113098", |
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"nightvisionXLPhotorealisticPortrait_release0770Bakedvae_154525", |
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"novaPrimeXL_v10_107899", |
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"pixelwave_v10_117722", |
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"protovisionXLHighFidelity3D_beta0520Bakedvae_106612", |
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"protovisionXLHighFidelity3D_release0620Bakedvae_131308", |
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"protovisionXLHighFidelity3D_release0630Bakedvae_154359", |
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"protovisionXLHighFidelity3D_releaseV660Bakedvae_207131", |
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"realismEngineSDXL_v05b_131513", |
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"realismEngineSDXL_v10_136287", |
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"realisticStockPhoto_v10_115618", |
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"RealitiesEdgeXL_4_122673", |
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"realvisxlV20_v20Bakedvae_129156", |
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"riotDiffusionXL_v20_139293", |
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"roxl_v10_109354", |
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"sdxlNijiSpecial_sdxlNijiSE_115638", |
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"sdxlNijiV3_sdxlNijiV3_104571", |
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"sdxlNijiV51_sdxlNijiV51_112807", |
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"sdxlUnstableDiffusers_v8HEAVENSWRATH_133813", |
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"sdxlYamersAnimeUltra_yamersAnimeV3_121537", |
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"sd_xl_base_0.9", |
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"sd_xl_base_1.0", |
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"shikianimexl_v10_93788", |
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"theTalosProject_v10_117893", |
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"thinkdiffusionxl_v10_145931", |
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"voidnoisecorexl_r1486_150780", |
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"wlopArienwlopstylexl_v10_101973", |
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"wlopSTYLEXL_v2_126171", |
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"xl13AsmodeusSFWNSFW_v22BakedVAE_111954", |
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"xxmix9realisticsdxl_v10_123235", |
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"zavychromaxl_b2_103298", |
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"toonSphere3D_v10_252626", |
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"pixelArtDiffusionXL_spriteShaper_291175", |
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"SDXLPixelArtBase_v10_246513", |
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"animeRealisticXL_animeXLReal_211225", |
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"animeChangefulXL_v10ReleasedCandidate_96351", |
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"realisticMixXL_v10_288901", |
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] |
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LORA_MODELS = [ |
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"DI_belle_delphine_sdxl_v1_93586", |
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"NsfwPovAllInOneLoraSdxl-000009_120561", |
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"acidzlime-sdxl_154149", |
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"add-detail-xl_99264", |
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"bwporcelaincd_xl-000007_124344", |
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"concept_pov_dt_xl2-000020_119643", |
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"epoxy_skull-sdxl_153213", |
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"landscape-painting-sdxl_v2_111037", |
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"polyhedron_all_sdxl-000004_110557", |
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"ral-beer-sdxl_235173", |
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"ral-wtchz-sdxl_233487", |
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"sdxl_cute_social_comic-000002_107980", |
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"sdxl_glass_136034", |
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"sdxl_lightning_2step_lora", |
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"sdxl_lightning_4step_lora", |
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"sdxl_lightning_8step_lora", |
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"sdxl_offset_example_v10_113006", |
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"sdxl_wrong_lora", |
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"xl_more_art-full_v1_113467", |
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"xl_yoshiaki_kawajiri_v1r64_126468", |
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"AmiguramiRedmond-Crochet-Amigurumi_312819", |
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"zwuul-sdxl_162249", |
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"羊毛毡_119309", |
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"Clay Animation_114757", |
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"CLAYMATE_V2.03__182497", |
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"ClayAnimationRedm_119998", |
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"mosaic_110562", |
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"hjsocrealmosaic_v10xl_158107", |
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"jadecarvingcd_xl-000007_185347", |
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"jade_125785", |
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"SDXL1.0_Essenz-series-by-AI_Characters_Style_YourNameWeatheringWithYouSuzumeMakotoShinkai-v1.4-'Skynet'_195187", |
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"pixel-art-xl-v1.1_99321", |
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"OWStyleYeiyeiArt-8_210248", |
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"yen_w3_sdxl_3000_95299", |
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"EnvyEleganceXL01_170674", |
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"Van_gogh_by_DevDope-000014_272552", |
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"vincent_van_gogh_xl_98658", |
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"tbh123-sdxl_422666", |
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"AutumnStyleXL_152042", |
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"shadows_281564", |
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"cybepunk_261064", |
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"Neon_Cyberpunk_SDXL_Dwarves_248422", |
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"Neon_Cyberpunk_Headoverlay_SDXL_435708", |
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"cyberpunk_xl-000004_410262", |
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"Halcyon Cyberpunk Style_357239", |
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"HLMCoreyAnimagine_242097", |
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"GTA_VI_Style_203190", |
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"oil-painting-style_A3.1_XL-9_418884", |
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"oil painting_92815", |
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"youhua_97640", |
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"Realistic_Insta_InfluencerV1.0_340126", |
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"Origami_World-000005_129203", |
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"ORIGAMI_115169", |
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"ral-orgmi-sdxl_179458", |
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"MJMangaSDXL_280228", |
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"Original video animation style_365023", |
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"Nier_Automata_2B_White_Wedding_Dress_Bride_Cosplay_Realistic_LoRA_349884", |
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"sl_sila_94476", |
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"Ariel_the_Mermaid_XL_157225", |
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"mermaidXL_143722", |
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"EnvyFairyQueenXL01_114606", |
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"童话绘本-Arien奇幻风格_v1.0_134091", |
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"high_elf_archer_v0.0.1_102856", |
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"DreamARTSDXL_100272", |
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"harry_potter_v1_269226", |
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"arwen_prodigy_sdxl_3300_235876", |
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"2ellie-000003_184345", |
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"bella_ramsey_sdxl_190746", |
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"sketch_for_art_examination_166045", |
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"traditional_watercolor_painting_137593", |
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"watercolor_204560", |
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"EnvyAnimeWatercolorXL01_199536", |
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"vampire teeth v3_255457", |
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"SDXL_Superhero_287891", |
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"CyborgsXL_227686", |
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"Astro_Life_132655", |
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"ral-czmcrnbw-sdxl_252438", |
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"EnvyScifiStreamlineXL01_204968", |
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"PixarXL_162719", |
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"chibistylexl-v1-2_99955", |
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"gldnglry_203448", |
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"NeonifyV2-4Extreme_99051", |
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"fflix-npt_294031", |
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"Dhevv-FantasyEgyptClothesXL_397565", |
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"xl0918ice-water_124998", |
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] |
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CONTROLNET_DICT = dict( |
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pose=InstantIDControlnetUnit( |
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model_name='controlnet-openpose-sdxl-1.0', |
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strength=1, |
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preprocessor='openpose', |
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), |
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canny=InstantIDControlnetUnit( |
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model_name='controlnet-canny-sdxl-1.0', |
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strength=1, |
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preprocessor='canny', |
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), |
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depth=InstantIDControlnetUnit( |
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model_name='controlnet-depth-sdxl-1.0', |
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strength=1, |
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preprocessor='depth', |
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), |
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lineart=InstantIDControlnetUnit( |
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model_name='controlnet-softedge-sdxl-1.0', |
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strength=1, |
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preprocessor='lineart', |
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), |
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) |
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last_check = 0 |
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def get_novita_client (novita_key): |
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client = NovitaClient(novita_key, os.getenv('NOVITA_API_URI', None)) |
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return client |
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get_local_storage = ''' |
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function () { |
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globalThis.setStorage = (key, value)=>{ |
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localStorage.setItem(key, JSON.stringify(value)) |
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} |
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globalThis.getStorage = (key, value)=>{ |
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return JSON.parse(localStorage.getItem(key)) |
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} |
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const novita_key = getStorage("novita_key") |
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return [novita_key]; |
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} |
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''' |
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def toggle_lcm_ui (value): |
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if value: |
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return ( |
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gr.update(minimum=0, maximum=100, step=1, value=5), |
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gr.update(minimum=0.1, maximum=20.0, step=0.1, value=1.5), |
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) |
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else: |
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return ( |
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gr.update(minimum=5, maximum=100, step=1, value=30), |
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gr.update(minimum=0.1, maximum=20.0, step=0.1, value=5), |
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) |
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def randomize_seed_fn (seed: int, randomize_seed: bool) -> int: |
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if randomize_seed: |
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seed = random.randint(0, MAX_SEED) |
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return seed |
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def remove_tips (): |
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return gr.update(visible=False) |
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def apply_style (style_name: str, positive: str, negative: str = "") -> Tuple[str, str]: |
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p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME]) |
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return p.replace("{prompt}", positive), n + " " + negative |
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def get_example (): |
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case = [ |
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[ |
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'./examples/yann-lecun_resize.jpg', |
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None, |
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'a man', |
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'Spring Festival', |
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'(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green', |
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], |
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[ |
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'./examples/musk_resize.jpeg', |
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'./examples/poses/pose2.jpg', |
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'a man flying in the sky in Mars', |
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'Mars', |
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'(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green', |
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], |
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[ |
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'./examples/sam_resize.png', |
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'./examples/poses/pose4.jpg', |
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'a man doing a silly pose wearing a suite', |
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'Jungle', |
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'(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, gree', |
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], |
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[ |
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'./examples/schmidhuber_resize.png', |
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'./examples/poses/pose3.jpg', |
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'a man sit on a chair', |
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'Neon', |
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'(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green', |
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], |
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[ |
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'./examples/kaifu_resize.png', |
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'./examples/poses/pose.jpg', |
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'a man', |
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'Vibrant Color', |
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'(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green', |
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], |
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] |
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return case |
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def load_example (face_file, pose_file, prompt, style, negative_prompt): |
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name = os.path.basename(face_file).split('_')[0] |
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image = PIL.Image.open(open(f'./examples/generated/{name}.jpg', 'rb')) |
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return image, gr.update(visible=True) |
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upload_depot = {} |
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def upload_assets_with_cache (client, paths): |
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global upload_depot |
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pending_paths = [path for path in paths if not path in upload_depot] |
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if pending_paths: |
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print('uploading images:', pending_paths) |
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for key, value in zip(pending_paths, client.upload_assets(pending_paths)): |
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upload_depot[key] = value |
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return [upload_depot[path] for path in paths] |
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def generate_image ( |
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novita_key1, |
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model_name, |
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lora_selection, |
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face_image_path, |
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pose_image_path, |
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prompt, |
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negative_prompt, |
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style_name, |
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num_steps, |
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identitynet_strength_ratio, |
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adapter_strength_ratio, |
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controlnet_strength_1, controlnet_strength_2, controlnet_strength_3, controlnet_strength_4, |
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controlnet_selection, |
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guidance_scale, |
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seed, |
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scheduler, |
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progress=gr.Progress(track_tqdm=True), |
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): |
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if face_image_path is None: |
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raise gr.Error(f'Cannot find any input face image! Please refer to step 1️⃣') |
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if not novita_key1: |
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raise gr.Error(f'Please input your Novita Key!') |
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try: |
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client = get_novita_client(novita_key1) |
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prompt, negative_prompt = apply_style(style_name, prompt, negative_prompt) |
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prompt = prompt[:1024] or ' ' |
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ref_image_path = pose_image_path if pose_image_path else face_image_path |
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ref_image = PIL.Image.open(ref_image_path) |
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width, height = ref_image.size |
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large_edge = max(width, height) |
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if large_edge < 1024: |
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scaling = 1024 / large_edge |
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width = int(width * scaling) |
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height = int(height * scaling) |
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|
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( |
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CONTROLNET_DICT['pose'].strength, |
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CONTROLNET_DICT['canny'].strength, |
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CONTROLNET_DICT['depth'].strength, |
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CONTROLNET_DICT['lineart'].strength, |
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) = [controlnet_strength_1, controlnet_strength_2, controlnet_strength_3, controlnet_strength_4] |
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|
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def progress_ (x): |
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global last_check |
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t = time() |
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if t > last_check + 5: |
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last_check = t |
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print('progress:', t, x.task.status) |
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|
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res = client.instant_id( |
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model_name=f'{model_name}.safetensors', |
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face_images=[face_image_path], |
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ref_images=[ref_image_path], |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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controlnets=[CONTROLNET_DICT[name] for name in controlnet_selection if name in CONTROLNET_DICT], |
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loras=[InstantIDLora( |
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model_name=f'{name}.safetensors', |
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strength=1, |
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) for name in lora_selection], |
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steps=num_steps, |
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seed=seed, |
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guidance_scale=guidance_scale, |
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sampler_name=scheduler, |
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id_strength=identitynet_strength_ratio, |
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adapter_strength=adapter_strength_ratio, |
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width=width, |
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height=height, |
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response_image_type='jpeg', |
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callback=progress_, |
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) |
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|
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print('task_id:', datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), res.task.task_id) |
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|
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if not hasattr(res, 'images_encoded'): |
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raise gr.Error(f'Error: {res.task}') |
|
except Exception as e: |
|
raise gr.Error(f'Error: {e}') |
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|
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image = PIL.Image.open(BytesIO(base64.b64decode(res.images_encoded[0]))) |
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|
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return image, gr.update(visible=True) |
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|
|
|
|
def get_payload ( |
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model_name, |
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lora_selection, |
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face_image_path, |
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pose_image_path, |
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prompt, |
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negative_prompt, |
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style_name, |
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num_steps, |
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identitynet_strength_ratio, |
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adapter_strength_ratio, |
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controlnet_strength_1, controlnet_strength_2, controlnet_strength_3, controlnet_strength_4, |
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controlnet_selection, |
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guidance_scale, |
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seed, |
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scheduler, |
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): |
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prompt, negative_prompt = apply_style(style_name, prompt, negative_prompt) |
|
|
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ref_image_path = pose_image_path if pose_image_path else face_image_path |
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ref_image = PIL.Image.open(ref_image_path) |
|
|
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width, height = ref_image.size |
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large_edge = max(width, height) |
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if large_edge < 1024: |
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scaling = 1024 / large_edge |
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width = int(width * scaling) |
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height = int(height * scaling) |
|
|
|
( |
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CONTROLNET_DICT['pose'].strength, |
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CONTROLNET_DICT['canny'].strength, |
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CONTROLNET_DICT['depth'].strength, |
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CONTROLNET_DICT['lineart'].strength, |
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) = [controlnet_strength_1, controlnet_strength_2, controlnet_strength_3, controlnet_strength_4] |
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|
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return { |
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'extra': { |
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'response_image_type': 'jpeg', |
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}, |
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'model_name': f'{model_name}.safetensors', |
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'face_image_assets_ids': "[assets_ids of id image, please manually upload to novita.ai]", |
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'ref_image_assets_ids': "[assets_ids of reference image, please manually upload to novita.ai]", |
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'prompt': prompt, |
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'negative_prompt': negative_prompt, |
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'controlnet': { |
|
'units': [CONTROLNET_DICT[name] for name in controlnet_selection if name in CONTROLNET_DICT], |
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}, |
|
'loras': [dict( |
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model_name=f'{name}.safetensors', |
|
strength=1, |
|
) for name in lora_selection], |
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'image_num': 1, |
|
'steps': num_steps, |
|
'seed': seed, |
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'guidance_scale': guidance_scale, |
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'sampler_name': scheduler, |
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'id_strength': identitynet_strength_ratio, |
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'adapter_strength': adapter_strength_ratio, |
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'width': width, |
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'height': height, |
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} |
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|
|
|
|
|
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title = r''' |
|
<h1 align="center">InstantID: Zero-shot Identity-Preserving Generation in Seconds (via Novita)</h1> |
|
''' |
|
|
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description = r''' |
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<a href='https://github.com/InstantID/InstantID' target="_blank"><b>InstantID</b></a> demo via <a href="https://novita.ai/" target="_blank"><b>Novita API</b></a>.<br> |
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How to use:<br> |
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0. Input your <a href="https://novita.ai/dashboard/key" target="_blank"><b>Novita API Key</b></a>. |
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1. Upload an image with a face. For images with multiple faces, we will only detect the largest face. Ensure the face is not too small and is clearly visible without significant obstructions or blurring. |
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2. (Optional) You can upload another image as a reference for the face pose. If you don't, we will use the first detected face image to extract facial landmarks. If you use a cropped face at step 1, it is recommended to upload it to define a new face pose. |
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3. (Optional) You can select multiple ControlNet models to control the generation process. The default is to use the IdentityNet only. The ControlNet models include pose skeleton, canny, and depth. You can adjust the strength of each ControlNet model to control the generation process. |
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4. Enter a text prompt, as done in normal text-to-image models. |
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5. Click the <b>Submit</b> button to begin customization. |
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6. Share your customized photo with your friends and enjoy! 😊''' |
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article = r''' |
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--- |
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''' |
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tips = r''' |
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### Usage tips of InstantID |
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1. If you're not satisfied with the similarity, try increasing the weight of "IdentityNet Strength" and "Adapter Strength." |
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2. If you feel that the saturation is too high, first decrease the Adapter strength. If it remains too high, then decrease the IdentityNet strength. |
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3. If you find that text control is not as expected, decrease Adapter strength. |
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4. If you find that realistic style is not good enough, go for our Github repo and use a more realistic base model. |
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''' |
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css = ''' |
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.gradio-container {width: 85% !important} |
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''' |
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with gr.Blocks(css=css) as demo: |
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gr.Markdown(title) |
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gr.Markdown(description) |
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with gr.Row(): |
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with gr.Column(scale=1): |
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novita_key = gr.Textbox(value='', label='Novita.AI API KEY', placeholder='novita.ai api key', type='password') |
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with gr.Column(scale=1): |
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user_balance = gr.Textbox(label='User Balance', value='0.0') |
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with gr.Row(): |
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with gr.Column(): |
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with gr.Row(equal_height=True): |
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face_file = gr.Image( |
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label='Upload a photo of your face', type='filepath' |
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) |
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pose_file = gr.Image( |
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label='Upload a reference pose image (Optional)', |
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type='filepath', |
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) |
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prompt = gr.Textbox( |
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label='Prompt', |
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info='Give simple prompt is enough to achieve good face fidelity', |
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placeholder='A photo of a person', |
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value='', |
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) |
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submit = gr.Button('Submit', variant='primary') |
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model_name = gr.Dropdown( |
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label='Base model', |
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choices=SDXL_MODELS, |
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value=DEFAULT_MODEL_NAME, |
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) |
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with gr.Accordion('Lora', open=False): |
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lora_selection = gr.CheckboxGroup( |
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LORA_MODELS, value=[], |
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info='Try lora models mix in generation' |
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) |
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style = gr.Dropdown( |
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label='Style template', |
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choices=STYLE_NAMES, |
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value=DEFAULT_STYLE_NAME, |
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) |
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identitynet_strength_ratio = gr.Slider( |
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label='IdentityNet strength (for fidelity)', |
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minimum=0, |
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maximum=1.5, |
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step=0.05, |
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value=0.80, |
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) |
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adapter_strength_ratio = gr.Slider( |
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label='Image adapter strength (for detail)', |
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minimum=0, |
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maximum=1.5, |
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step=0.05, |
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value=0.80, |
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) |
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with gr.Accordion('Controlnet'): |
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controlnet_selection = gr.CheckboxGroup( |
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CONTROLNET_DICT.keys(), label='Controlnet', value=['pose'], |
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info='Use pose for skeleton inference, canny for edge detection, and depth for depth map estimation. You can try all three to control the generation process' |
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) |
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pose_strength = gr.Slider( |
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label='Pose strength', |
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minimum=0, |
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maximum=1.5, |
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step=0.05, |
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value=0.40, |
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) |
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canny_strength = gr.Slider( |
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label='Canny strength', |
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minimum=0, |
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maximum=1.5, |
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step=0.05, |
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value=0.40, |
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) |
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depth_strength = gr.Slider( |
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label='Depth strength', |
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minimum=0, |
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maximum=1.5, |
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step=0.05, |
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value=0.40, |
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) |
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lineart_strength = gr.Slider( |
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label='Lineart strength', |
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minimum=0, |
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maximum=1.5, |
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step=0.05, |
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value=0.40, |
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) |
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with gr.Accordion(open=False, label='Advanced Options'): |
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negative_prompt = gr.Textbox( |
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label='Negative Prompt', |
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placeholder='low quality', |
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value='(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green', |
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) |
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num_steps = gr.Slider( |
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label='Number of sample steps', |
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minimum=1, |
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maximum=100, |
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step=1, |
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value=5 if enable_lcm_arg else 30, |
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) |
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guidance_scale = gr.Slider( |
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label='Guidance scale', |
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minimum=1., |
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maximum=30.0, |
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step=0.1, |
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value=0.0 if enable_lcm_arg else 5.0, |
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) |
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seed = gr.Slider( |
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label='Seed', |
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minimum=0, |
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maximum=MAX_SEED, |
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step=1, |
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value=42, |
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) |
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schedulers = [ |
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'Euler', |
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'Euler a', |
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'Heun', |
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'DPM++ SDE', |
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'DPM++ SDE Karras', |
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'DPM2', |
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'DPM2 Karras', |
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'DPM2 a', |
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'DPM2 a Karras', |
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] |
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scheduler = gr.Dropdown( |
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label='Schedulers', |
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choices=schedulers, |
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value='Euler', |
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) |
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randomize_seed = gr.Checkbox(label='Randomize seed', value=True) |
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with gr.Column(scale=1): |
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gallery = gr.Image(label='Generated Images') |
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usage_tips = gr.Markdown( |
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label='InstantID Usage Tips', value=tips, visible=False |
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) |
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api_payload = gr.JSON(label="Novita API Payload, POST /v3/async/instant-id") |
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submit.click( |
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fn=remove_tips, |
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outputs=usage_tips, |
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).then( |
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fn=randomize_seed_fn, |
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inputs=[seed, randomize_seed], |
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outputs=seed, |
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queue=False, |
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api_name=False, |
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).then( |
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fn=get_payload, |
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inputs=[ |
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model_name, |
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lora_selection, |
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face_file, |
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pose_file, |
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prompt, |
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negative_prompt, |
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style, |
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num_steps, |
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identitynet_strength_ratio, |
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adapter_strength_ratio, |
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pose_strength, |
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canny_strength, |
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depth_strength, |
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lineart_strength, |
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controlnet_selection, |
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guidance_scale, |
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seed, |
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scheduler, |
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], |
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outputs=api_payload, |
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).then( |
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fn=generate_image, |
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inputs=[ |
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novita_key, |
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model_name, |
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lora_selection, |
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face_file, |
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pose_file, |
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prompt, |
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negative_prompt, |
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style, |
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num_steps, |
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identitynet_strength_ratio, |
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adapter_strength_ratio, |
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pose_strength, |
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canny_strength, |
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depth_strength, |
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lineart_strength, |
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controlnet_selection, |
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guidance_scale, |
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seed, |
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scheduler, |
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], |
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outputs=[gallery, usage_tips], |
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) |
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gr.Examples( |
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examples=get_example(), |
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inputs=[face_file, pose_file, prompt, style, negative_prompt], |
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fn=load_example, |
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outputs=[gallery, usage_tips], |
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cache_examples=True, |
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) |
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gr.Markdown(article) |
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def onload(novita_key): |
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if novita_key is None or novita_key == '': |
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return novita_key, f'$ UNKNOWN', gr.update(visible=False) |
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try: |
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user_info_json = get_novita_client(novita_key).user_info() |
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except Exception as e: |
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return novita_key, f'$ UNKNOWN' |
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return novita_key, f'$ {user_info_json.credit_balance / 100 / 100:.2f}' |
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novita_key.change(onload, inputs=novita_key, outputs=[novita_key, user_balance], js='v=>{ setStorage("novita_key", v); return [v]; }') |
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demo.load( |
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inputs=[novita_key], |
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outputs=[novita_key, user_balance], |
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fn=onload, |
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js=get_local_storage, |
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) |
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demo.queue(api_open=False) |
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demo.launch() |
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