import os import json import copy import time import random import logging import numpy as np from typing import Any, Dict, List, Optional, Union from diffusers.utils import load_image import torch from PIL import Image import gradio as gr from diffusers import ( DiffusionPipeline, AutoencoderTiny, AutoencoderKL, AutoPipelineForImage2Image, FluxPipeline, FlowMatchEulerDiscreteScheduler) from huggingface_hub import ( hf_hub_download, HfFileSystem, ModelCard, snapshot_download) import torch from diffusers import FluxControlNetPipeline from diffusers import FluxControlNetModel import spaces #---if env = local or colab--- # Authenticate with Hugging Face # from huggingface_hub import login # Log in to Hugging Face using the provided token # hf_token = 'hf-token-authentication' # login(hf_token) def calculate_shift( image_seq_len, base_seq_len: int = 256, max_seq_len: int = 4096, base_shift: float = 0.5, max_shift: float = 1.16, ): m = (max_shift - base_shift) / (max_seq_len - base_seq_len) b = base_shift - m * base_seq_len mu = image_seq_len * m + b return mu def retrieve_timesteps( scheduler, num_inference_steps: Optional[int] = None, device: Optional[Union[str, torch.device]] = None, timesteps: Optional[List[int]] = None, sigmas: Optional[List[float]] = None, **kwargs, ): if timesteps is not None and sigmas is not None: raise ValueError("Only one of `timesteps` or `sigmas` can be passed. Please choose one to set custom values") if timesteps is not None: scheduler.set_timesteps(timesteps=timesteps, device=device, **kwargs) timesteps = scheduler.timesteps num_inference_steps = len(timesteps) elif sigmas is not None: scheduler.set_timesteps(sigmas=sigmas, device=device, **kwargs) timesteps = scheduler.timesteps num_inference_steps = len(timesteps) else: scheduler.set_timesteps(num_inference_steps, device=device, **kwargs) timesteps = scheduler.timesteps return timesteps, num_inference_steps # FLUX pipeline @torch.inference_mode() def flux_pipe_call_that_returns_an_iterable_of_images( self, prompt: Union[str, List[str]] = None, prompt_2: Optional[Union[str, List[str]]] = None, height: Optional[int] = None, width: Optional[int] = None, num_inference_steps: int = 28, timesteps: List[int] = None, guidance_scale: float = 3.5, num_images_per_prompt: Optional[int] = 1, generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, latents: Optional[torch.FloatTensor] = None, prompt_embeds: Optional[torch.FloatTensor] = None, pooled_prompt_embeds: Optional[torch.FloatTensor] = None, output_type: Optional[str] = "pil", return_dict: bool = True, joint_attention_kwargs: Optional[Dict[str, Any]] = None, max_sequence_length: int = 512, good_vae: Optional[Any] = None, ): height = height or self.default_sample_size * self.vae_scale_factor width = width or self.default_sample_size * self.vae_scale_factor self.check_inputs( prompt, prompt_2, height, width, prompt_embeds=prompt_embeds, pooled_prompt_embeds=pooled_prompt_embeds, max_sequence_length=max_sequence_length, ) self._guidance_scale = guidance_scale self._joint_attention_kwargs = joint_attention_kwargs self._interrupt = False batch_size = 1 if isinstance(prompt, str) else len(prompt) device = self._execution_device lora_scale = joint_attention_kwargs.get("scale", None) if joint_attention_kwargs is not None else None prompt_embeds, pooled_prompt_embeds, text_ids = self.encode_prompt( prompt=prompt, prompt_2=prompt_2, prompt_embeds=prompt_embeds, pooled_prompt_embeds=pooled_prompt_embeds, device=device, num_images_per_prompt=num_images_per_prompt, max_sequence_length=max_sequence_length, lora_scale=lora_scale, ) num_channels_latents = self.transformer.config.in_channels // 4 latents, latent_image_ids = self.prepare_latents( batch_size * num_images_per_prompt, num_channels_latents, height, width, prompt_embeds.dtype, device, generator, latents, ) sigmas = np.linspace(1.0, 1 / num_inference_steps, num_inference_steps) image_seq_len = latents.shape[1] mu = calculate_shift( image_seq_len, self.scheduler.config.base_image_seq_len, self.scheduler.config.max_image_seq_len, self.scheduler.config.base_shift, self.scheduler.config.max_shift, ) timesteps, num_inference_steps = retrieve_timesteps( self.scheduler, num_inference_steps, device, timesteps, sigmas, mu=mu, ) self._num_timesteps = len(timesteps) guidance = torch.full([1], guidance_scale, device=device, dtype=torch.float32).expand(latents.shape[0]) if self.transformer.config.guidance_embeds else None for i, t in enumerate(timesteps): if self.interrupt: continue timestep = t.expand(latents.shape[0]).to(latents.dtype) noise_pred = self.transformer( hidden_states=latents, timestep=timestep / 1000, guidance=guidance, pooled_projections=pooled_prompt_embeds, encoder_hidden_states=prompt_embeds, txt_ids=text_ids, img_ids=latent_image_ids, joint_attention_kwargs=self.joint_attention_kwargs, return_dict=False, )[0] latents_for_image = self._unpack_latents(latents, height, width, self.vae_scale_factor) latents_for_image = (latents_for_image / self.vae.config.scaling_factor) + self.vae.config.shift_factor image = self.vae.decode(latents_for_image, return_dict=False)[0] yield self.image_processor.postprocess(image, output_type=output_type)[0] latents = self.scheduler.step(noise_pred, t, latents, return_dict=False)[0] torch.cuda.empty_cache() latents = self._unpack_latents(latents, height, width, self.vae_scale_factor) latents = (latents / good_vae.config.scaling_factor) + good_vae.config.shift_factor image = good_vae.decode(latents, return_dict=False)[0] self.maybe_free_model_hooks() torch.cuda.empty_cache() yield self.image_processor.postprocess(image, output_type=output_type)[0] #-----------------------------------------------------------------------------------LoRA's--------------------------------------------------------------------------# loras = [ #0 { "image": "https://huggingface.co/prithivMLmods/Purple-Dreamy-Flux-LoRA/resolve/main/images/PD3.png", "title": "Purple Dream", "repo": "prithivMLmods/Purple-Dreamy-Flux-LoRA", "weights": "Purple-Dreamy.safetensors", "trigger_word": "Purple Dreamy" }, #1 { "image": "https://huggingface.co/prithivMLmods/Canopus-LoRA-Flux-FaceRealism/resolve/main/images/11.png", "title": "Flux Face Realism", "repo": "prithivMLmods/Canopus-LoRA-Flux-FaceRealism", "trigger_word": "Realism" }, #2 { "image": "https://huggingface.co/alvdansen/softserve_anime/resolve/main/images/ComfyUI_00134_.png", "title": "Softserve Anime", "repo": "alvdansen/softserve_anime", "trigger_word": "sftsrv style illustration" }, #3 { "image": "https://huggingface.co/prithivMLmods/Canopus-LoRA-Flux-Anime/resolve/main/assets/4.png", "title": "Flux Anime", "repo": "prithivMLmods/Canopus-LoRA-Flux-Anime", "trigger_word": "Anime" }, #4 { "image": "https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-One-Click-Creative-Template/resolve/main/images/f2cc649985648e57b9b9b14ca7a8744ac8e50d75b3a334ed4df0f368.jpg", "title": "Creative Template", "repo": "Shakker-Labs/FLUX.1-dev-LoRA-One-Click-Creative-Template", "trigger_word": "The background is 4 real photos, and in the middle is a cartoon picture summarizing the real photos." }, #5 { "image": "https://huggingface.co/prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0/resolve/main/images/3.png", "title": "Ultra Realism", "repo": "prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0", "trigger_word": "Ultra realistic" }, #6 { "image": "https://huggingface.co/gokaygokay/Flux-Game-Assets-LoRA-v2/resolve/main/images/example_y2bqpuphc.png", "title": "Game Assets", "repo": "gokaygokay/Flux-Game-Assets-LoRA-v2", "trigger_word": "wbgmsst, white background" }, #7 { "image": "https://huggingface.co/alvdansen/softpasty-flux-dev/resolve/main/images/ComfyUI_00814_%20(2).png", "title": "Softpasty", "repo": "alvdansen/softpasty-flux-dev", "trigger_word": "araminta_illus illustration style" }, #8 { "image": "https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-add-details/resolve/main/images/0.png", "title": "Details Add", "repo": "Shakker-Labs/FLUX.1-dev-LoRA-add-details", "trigger_word": "" }, #9 { "image": "https://huggingface.co/alvdansen/frosting_lane_flux/resolve/main/images/content%20-%202024-08-11T010011.238.jpeg", "title": "Frosting Lane", "repo": "alvdansen/frosting_lane_flux", "trigger_word": "frstingln illustration" }, #10 { "image": "https://huggingface.co/aleksa-codes/flux-ghibsky-illustration/resolve/main/images/example5.jpg", "title": "Ghibsky Illustration", "repo": "aleksa-codes/flux-ghibsky-illustration", "trigger_word": "GHIBSKY style painting" }, #11 { "image": "https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-Dark-Fantasy/resolve/main/images/c2215bd73da9f14fcd63cc93350e66e2901bdafa6fb8abaaa2c32a1b.jpg", "title": "Dark Fantasy", "repo": "Shakker-Labs/FLUX.1-dev-LoRA-Dark-Fantasy", "trigger_word": "" }, #12 { "image": "https://huggingface.co/Norod78/Flux_1_Dev_LoRA_Paper-Cutout-Style/resolve/main/d13591878d5043f3989dd6eb1c25b710_233c18effb4b491cb467ca31c97e90b5.png", "title": "Paper Cutout", "repo": "Norod78/Flux_1_Dev_LoRA_Paper-Cutout-Style", "trigger_word": "Paper Cutout Style" }, #13 { "image": "https://huggingface.co/alvdansen/mooniverse/resolve/main/images/out-0%20(17).webp", "title": "Mooniverse", "repo": "alvdansen/mooniverse", "trigger_word": "surreal style" }, #14 { "image": "https://huggingface.co/alvdansen/pola-photo-flux/resolve/main/images/out-0%20-%202024-09-22T130819.351.webp", "title": "Pola Photo", "repo": "alvdansen/pola-photo-flux", "trigger_word": "polaroid style" }, #15 { "image": "https://huggingface.co/multimodalart/flux-tarot-v1/resolve/main/images/7e180627edd846e899b6cd307339140d_5b2a09f0842c476b83b6bd2cb9143a52.png", "title": "Flux Tarot", "repo": "multimodalart/flux-tarot-v1", "trigger_word": "in the style of TOK a trtcrd tarot style" }, #16 { "image": "https://huggingface.co/prithivMLmods/Flux-Dev-Real-Anime-LoRA/resolve/main/images/111.png", "title": "Real Anime", "repo": "prithivMLmods/Flux-Dev-Real-Anime-LoRA", "trigger_word": "Real Anime" }, #17 { "image": "https://huggingface.co/diabolic6045/Flux_Sticker_Lora/resolve/main/images/example_s3pxsewcb.png", "title": "Stickers", "repo": "diabolic6045/Flux_Sticker_Lora", "trigger_word": "5t1cker 5ty1e" }, #18 { "image": "https://huggingface.co/VideoAditor/Flux-Lora-Realism/resolve/main/images/feel-the-difference-between-using-flux-with-lora-from-xlab-v0-j0ehybmvxehd1.png", "title": "Realism", "repo": "XLabs-AI/flux-RealismLora", "trigger_word": "" }, #19 { "image": "https://huggingface.co/alvdansen/flux-koda/resolve/main/images/ComfyUI_00583_%20(1).png", "title": "Koda", "repo": "alvdansen/flux-koda", "trigger_word": "flmft style" }, #20 { "image": "https://huggingface.co/mgwr/Cine-Aesthetic/resolve/main/images/00019-1333633802.png", "title": "Cine Aesthetic", "repo": "mgwr/Cine-Aesthetic", "trigger_word": "mgwr/cine" }, #21 { "image": "https://huggingface.co/SebastianBodza/flux_cute3D/resolve/main/images/astronaut.webp", "title": "Cute 3D", "repo": "SebastianBodza/flux_cute3D", "trigger_word": "NEOCUTE3D" }, #22 { "image": "https://huggingface.co/bingbangboom/flux_dreamscape/resolve/main/images/3.jpg", "title": "Dreamscape", "repo": "bingbangboom/flux_dreamscape", "trigger_word": "in the style of BSstyle004" }, #23 { "image": "https://huggingface.co/prithivMLmods/Canopus-LoRA-Flux-FaceRealism/resolve/main/images/xc.webp", "title": "Cute Kawaii", "repo": "prithivMLmods/Canopus-Cute-Kawaii-Flux-LoRA", "trigger_word": "cute-kawaii" }, #24 { "image": "https://cdn-uploads.huggingface.co/production/uploads/64b24543eec33e27dc9a6eca/_jyra-jKP_prXhzxYkg1O.png", "title": "Pastel Anime", "repo": "Raelina/Flux-Pastel-Anime", "trigger_word": "Anime" }, #25 { "image": "https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-Vector-Journey/resolve/main/images/f7a66b51c89896854f31bef743dc30f33c6ea3c0ed8f9ff04d24b702.jpg", "title": "Vector", "repo": "Shakker-Labs/FLUX.1-dev-LoRA-Vector-Journey", "trigger_word": "artistic style blends reality and illustration elements" }, #26 { "image": "https://huggingface.co/bingbangboom/flux-miniature-worlds/resolve/main/images/2.jpg", "title": "Miniature", "repo": "bingbangboom/flux-miniature-worlds", "weights": "flux_MNTRWRLDS.safetensors", "trigger_word": "Image in the style of MNTRWRLDS" }, #27 { "image": "https://huggingface.co/glif-loradex-trainer/bingbangboom_flux_surf/resolve/main/samples/1729012111574__000002000_0.jpg", "title": "Surf Bingbangboom", "repo": "glif-loradex-trainer/bingbangboom_flux_surf", "weights": "flux_surf.safetensors", "trigger_word": "SRFNGV01" }, #28 { "image": "https://huggingface.co/prithivMLmods/Canopus-Snoopy-Charlie-Brown-Flux-LoRA/resolve/main/000.png", "title": "Snoopy Charlie", "repo": "prithivMLmods/Canopus-Snoopy-Charlie-Brown-Flux-LoRA", "trigger_word": "Snoopy Charlie Brown" }, #29 { "image": "https://huggingface.co/alvdansen/sonny-anime-fixed/resolve/main/images/uqAuIMqA6Z7mvPkHg4qJE_f4c3cbe64e0349e7b946d02adeacdca3.png", "title": "Fixed Sonny", "repo": "alvdansen/sonny-anime-fixed", "trigger_word": "nm22 style" }, #30 { "image": "https://huggingface.co/davisbro/flux-multi-angle/resolve/main/multi-angle-examples/3.png", "title": "Multi Angle", "repo": "davisbro/flux-multi-angle", "trigger_word": "A TOK composite photo of a person posing at different angles" }, #31 { "image": "https://huggingface.co/glif/how2draw/resolve/main/images/glif-how2draw-araminta-k-vbnvy94npt8m338r2vm02m50.jpg", "title": "How2Draw", "repo": "glif/how2draw", "trigger_word": "How2Draw" }, #32 { "image": "https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-Text-Poster/resolve/main/images/6dd1a918d89991ad5e40513ab88e7d892077f89dac93edcf4b660dd2.jpg", "title": "Text Poster", "repo": "Shakker-Labs/FLUX.1-dev-LoRA-Text-Poster", "trigger_word": "text poster" }, #33 { "image": "https://huggingface.co/SebastianBodza/Flux_Aquarell_Watercolor_v2/resolve/main/images/coffee.webp", "title": "Aquarell Watercolor", "repo": "SebastianBodza/Flux_Aquarell_Watercolor_v2", "trigger_word": "AQUACOLTOK" }, #34 { "image": "https://huggingface.co/Purz/face-projection/resolve/main/34031797.jpeg", "title": "Face Projection ", "repo": "Purz/face-projection", "trigger_word": "f4c3_p40j3ct10n" }, #35 { "image": "https://huggingface.co/martintomov/ecom-flux-v2/resolve/main/images/example_z30slf97z.png", "title": "Ecom Design Art", "repo": "martintomov/ecom-flux-v2", "trigger_word": "" }, #36 { "image": "https://huggingface.co/TheAwakenOne/max-headroom/resolve/main/sample/max-headroom_000900_00_20241015234926.png", "title": "Max Head-Room", "repo": "TheAwakenOne/max-headroom", "weights": "max-headroom-v1.safetensors", "trigger_word": "M2X, Max-Headroom" }, #37 { "image": "https://huggingface.co/renderartist/toyboxflux/resolve/main/images/3D__00366_.png", "title": "Toy Box Flux", "repo": "renderartist/toyboxflux", "weights": "Toy_Box_Flux_v2_renderartist.safetensors", "trigger_word": "t0yb0x, simple toy design, detailed toy design, 3D render" }, #38 { "image": "https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-live-3D/resolve/main/images/51a716fb6fe9ba5d54c260b70e7ff661d38acedc7fb725552fa77bcf.jpg", "title": "Live 3D", "repo": "Shakker-Labs/FLUX.1-dev-LoRA-live-3D", "trigger_word": "" }, #39 { "image": "https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-Garbage-Bag-Art/resolve/main/images/42e944819b43869a03dc252d10409b5944a62494c7082816121016f9.jpg", "title": "Garbage Bag Art", "repo": "Shakker-Labs/FLUX.1-dev-LoRA-Garbage-Bag-Art", "trigger_word": "Inflatable plastic bag" }, #40 { "image": "https://huggingface.co/Shakker-Labs/FLUX.1-dev-LoRA-Logo-Design/resolve/main/images/73e7db6a33550d05836ce285549de60075d05373c7b0660d631dac33.jpg", "title": "Logo Design", "repo": "Shakker-Labs/FLUX.1-dev-LoRA-Logo-Design", "trigger_word": "wablogo, logo, Minimalist" }, #41 { "image": "https://huggingface.co/punzel/flux_sadie_sink/resolve/main/images/ComfyUI_Flux_Finetune_00069_.png", "title": "Sadie Sink", "repo": "punzel/flux_sadie_sink", "weights": "flux_sadie_sink.safetensors", "trigger_word": "Sadie Sink" }, #42 { "image": "https://huggingface.co/punzel/flux_jenna_ortega/resolve/main/images/ComfyUI_Flux_Finetune_00065_.png", "title": "Jenna ortega", "repo": "punzel/flux_jenna_ortega", "weights": "flux_jenna_ortega.safetensors", "trigger_word": "Jenna ortega" }, #43 { "image": "https://huggingface.co/Wakkamaruh/balatro-poker-cards/resolve/main/samples/01.png", "title": "Poker Cards", "repo": "Wakkamaruh/balatro-poker-cards", "weights": "balatro-poker-cards.safetensors", "trigger_word": "balatrocard" }, #44 { "image": "https://huggingface.co/lichorosario/flux-cubist-cartoon/resolve/main/samples/albert-einstein.png", "title": "Cubist Cartoon", "repo": "lichorosario/flux-cubist-cartoon", "weights": "lora.safetensors", "trigger_word": "CBSTCRTN" }, #45 { "image": "https://huggingface.co/iliketoasters/miniature-people/resolve/main/images/1757-over%20the%20shoulder%20shot%2C%20raw%20photo%2C%20a%20min-fluxcomfy-orgflux1-dev-fp8-128443497-converted.png", "title": "Miniature People", "repo": "iliketoasters/miniature-people", "trigger_word": "miniature people" }, #46 { "image": "https://huggingface.co/ampp/rough-kids-illustrations/resolve/main/samples/1725115106736__000001000_0.jpg", "title": "kids Illustrations", "repo": "ampp/rough-kids-illustrations", "weights": "rough-kids-illustrations.safetensors", "trigger_word": "r0ughkids4rt" }, #47 { "image": "https://huggingface.co/lichorosario/flux-lora-tstvctr/resolve/main/images/example_mo3jx93o6.png", "title": "TSTVCTR Cartoon", "repo": "lichorosario/flux-lora-tstvctr", "weights": "lora.safetensors", "trigger_word": "TSTVCTR cartoon illustration" }, #48 { "image": "https://huggingface.co/lichorosario/flux-lora-gliff-tosti-vector-no-captions-2500s/resolve/main/images/example_i6h6fi9sq.png", "title": "Tosti Vector", "repo": "lichorosario/flux-lora-gliff-tosti-vector-no-captions-2500s", "weights": "flux_dev_tosti_vector_without_captions_000002500.safetensors", "trigger_word": "" }, #49 { "image": "https://huggingface.co/AlekseyCalvin/Propaganda_Poster_Schnell_by_doctor_diffusion/resolve/main/Trashy.png", "title": "Propaganda Poster", "repo": "AlekseyCalvin/Propaganda_Poster_Schnell_by_doctor_diffusion", "weights": "propaganda_schnell_v1.safetensors", "trigger_word": "propaganda poster" }, #50 { "image": "https://huggingface.co/WizWhite/Wiz-PunchOut_Ringside_Portrait/resolve/main/images/punch0ut__ringside_pixel_portrait_depicting_chris_brown_wearing_a_veil__moonstone_gray_background_with_white_ropes___1923906484.png", "title": "Ringside Portrait", "repo": "WizWhite/Wiz-PunchOut_Ringside_Portrait", "trigger_word": "punch0ut, ringside pixel portrait depicting" }, #51 { "image": "https://huggingface.co/glif-loradex-trainer/kklors_flux_dev_long_exposure/resolve/main/samples/1729016926778__000003000_3.jpg", "title": "Long Exposure", "repo": "glif-loradex-trainer/kklors_flux_dev_long_exposure", "weights": "flux_dev_long_exposure.safetensors", "trigger_word": "LE" }, #52 { "image": "https://huggingface.co/DamarJati/streetwear-flux/resolve/main/img/79e891f9-ceb8-4f8a-a51d-bb432789d037.jpeg", "title": "Street Wear", "repo": "DamarJati/streetwear-flux", "weights": "Streetwear.safetensors", "trigger_word": "Handling Information Tshirt template" }, #53 { "image": "https://huggingface.co/multimodalart/vintage-ads-flux/resolve/main/samples/-FMpgla6rQ1hBwBpbr-Ao_da7b23c29de14a9cad94901879ae2e2b.png", "title": "Vintage Ads Flux", "repo": "multimodalart/vintage-ads-flux", "weights": "vintage-ads-flux-1350.safetensors", "trigger_word": "a vintage ad of" }, #54 { "image": "https://huggingface.co/multimodalart/product-design/resolve/main/images/example_vgv87rlfl.png", "title": "Product Design", "repo": "multimodalart/product-design", "weights": "product-design.safetensors", "trigger_word": "product designed by prdsgn" }, #55 { "image": "https://huggingface.co/prithivMLmods/Canopus-LoRA-Flux-Typography-ASCII/resolve/main/images/NNN.png", "title": "Typography", "repo": "prithivMLmods/Canopus-LoRA-Flux-Typography-ASCII", "weights": "Typography.safetensors", "trigger_word": "Typography, ASCII Art" }, #56 { "image": "https://huggingface.co/mateo-19182/mosoco/resolve/main/samples/1725714834007__000002000_0.jpg", "title": "Mosoco", "repo": "mateo-19182/mosoco", "weights": "mosoco.safetensors", "trigger_word": "moscos0" }, #57 { "image": "https://huggingface.co/jakedahn/flux-latentpop/resolve/main/images/2.webp", "title": "Latent Pop", "repo": "jakedahn/flux-latentpop", "weights": "lora.safetensors", "trigger_word": "latentpop" }, #58 { "image": "https://huggingface.co/glif-loradex-trainer/ddickinson_dstyl3xl/resolve/main/samples/1728556571974__000001500_2.jpg", "title": "Dstyl3xl", "repo": "glif-loradex-trainer/ddickinson_dstyl3xl", "weights": "dstyl3xl.safetensors", "trigger_word": "in the style of dstyl3xl" }, #59 { "image": "https://huggingface.co/TDN-M/RetouchFLux/resolve/main/images/496f0680-0158-4f37-805d-d227c1a08a7b.png", "title": "Retouch FLux", "repo": "TDN-M/RetouchFLux", "weights": "TDNM_Retouch.safetensors", "trigger_word": "luxury, enhance, hdr" }, #60 { "image": 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book flux", "repo": "renderartist/coloringbookflux", "weights": "c0l0ringb00k_Flux_v1_renderartist.safetensors", "trigger_word": "c0l0ringb00k, coloring book, coloring book page" }, #117 { "image": "https://huggingface.co/prithivMLmods/Uncoloured-Polygon-Flux-LoRA/resolve/main/images/1.webp", "title": "Uncoloured Polygon", "repo": "prithivMLmods/Uncoloured-Polygon-Flux-LoRA", "weights": "Uncoloured-3D-Polygon.safetensors", "trigger_word": "uncoloured polygon" }, #118 { "image": "https://huggingface.co/prithivMLmods/Past-Present-Deep-Mix-Flux-LoRA/resolve/main/images/PP3.webp", "title": "Past Present Mix", "repo": "prithivMLmods/Past-Present-Deep-Mix-Flux-LoRA", "weights": "Past-Present-Deep-Mix-Flux-LoRA.safetensors", "trigger_word": "Mixing Past and Present" }, #119 { "image": "https://huggingface.co/gokaygokay/Flux-Double-Exposure-LoRA/resolve/main/images/image3.jpg", "title": "Double Exposure", "repo": "gokaygokay/Flux-Double-Exposure-LoRA", "weights": "double_exposure.safetensors", "trigger_word": "dblxpsr" }, #120 { "image": "https://huggingface.co/gokaygokay/Flux-Seamless-Texture-LoRA/resolve/main/images/image3.jpg", "title": "Seamless Texture", "repo": "gokaygokay/Flux-Seamless-Texture-LoRA", "weights": "seamless_texture.safetensors", "trigger_word": "smlstxtr" }, #121 { "image": "https://huggingface.co/prithivMLmods/Mockup-Texture-Flux-LoRA/resolve/main/images/MU1.webp", "title": "Mockup Texture", "repo": "prithivMLmods/Mockup-Texture-Flux-LoRA", "weights": "Mockup-Texture.safetensors", "trigger_word": "Mockup" }, #122 { "image": "https://huggingface.co/prithivMLmods/Ton618-Tarot-Cards-Flux-LoRA/resolve/main/images/c2.webp", "title": "Tarot Cards", "repo": "prithivMLmods/Ton618-Tarot-Cards-Flux-LoRA", "weights": "Tarot-card.safetensors", "trigger_word": "Tarot card" }, #123 { "image": "https://huggingface.co/prithivMLmods/Ton618-Amxtoon-Flux-LoRA/resolve/main/images/am1.webp", "title": "Amxtoon", "repo": "prithivMLmods/Ton618-Amxtoon-Flux-LoRA", "weights": "Amxtoon.safetensors", "trigger_word": "Amxtoon" }, #124 { "image": "https://huggingface.co/prithivMLmods/Ton618-Epic-Realism-Flux-LoRA/resolve/main/images/ep3.png", "title": "Epic Realism", "repo": "prithivMLmods/Ton618-Epic-Realism-Flux-LoRA", "weights": "Epic-Realism-Unpruned.safetensors", "trigger_word": "Epic Realism" }, #125 { "image": "https://huggingface.co/bingbangboom/flux-mixReality/resolve/main/images/3.jpg", "title": "Mixed Reality", "repo": "bingbangboom/flux-mixReality", "weights": "HLFILSTHLFPHTO_000002500.safetensors", "trigger_word": "in the style of HLFILSTHLFPHTO" }, #126 { "image": "https://huggingface.co/sWizad/pokemon-trainer-sprites-pixelart-flux/resolve/main/26578919.jpeg", "title": "Pixelart", "repo": "sWizad/pokemon-trainer-sprites-pixelart-flux", "weights": "pktrainer_F1-v1-0.safetensors", "trigger_word": "pixel image of, pixel art" }, #127 { "image": "https://huggingface.co/bingbangboom/flux_colorscape/resolve/main/images/2.jpg", "title": "Colorscape", "repo": "bingbangboom/flux_colorscape", "weights": "flux_colorscape.safetensors", "trigger_word": "illustration in the style of ASstyle001" }, #128 { "image": "https://huggingface.co/UmeAiRT/FLUX.1-dev-LoRA-Modern_Pixel_art/resolve/main/images/c363192f-5fa0-4539-8295-b8d9e3e96747.jpeg", "title": "Modern Pixel art", "repo": "UmeAiRT/FLUX.1-dev-LoRA-Modern_Pixel_art", "weights": "ume_modern_pixelart.safetensors", "trigger_word": "umempart" }, #129 { "image": "https://huggingface.co/prithivMLmods/Ton618-Only-Stickers-Flux-LoRA/resolve/main/images/222.png", "title": "Sticker", "repo": "prithivMLmods/Ton618-Only-Stickers-Flux-LoRA", "weights": "only-stickers.safetensors", "trigger_word": "Only Sticker" }, #130 { "image": "https://huggingface.co/prithivMLmods/Ton618-Space-Wallpaper-LoRA/resolve/main/images/222.png", "title": "Space Wallpaper", "repo": "prithivMLmods/Ton618-Space-Wallpaper-LoRA", "weights": "space-wallpaper-xl.safetensor", "trigger_word": "Space Wallpaper" }, #131 { "image": "https://huggingface.co/prithivMLmods/Canopus-Pixar-3D-Flux-LoRA/resolve/main/images/11111.png", "title": "Pixar 3D", "repo": "prithivMLmods/Canopus-Pixar-3D-Flux-LoRA", "weights": "Canopus-Pixar-3D-FluxDev-LoRA.safetensors", "trigger_word": "Pixar 3D" }, #132 { "image": "https://huggingface.co/prithivMLmods/EBook-Creative-Cover-Flux-LoRA/resolve/main/images/E2.png", "title": "EBook Cover", "repo": "prithivMLmods/EBook-Creative-Cover-Flux-LoRA", "weights": "EBook-Cover.safetensors", "trigger_word": "EBook Cover" }, #133 { "image": "https://huggingface.co/prithivMLmods/Minimal-Futuristic-Flux-LoRA/resolve/main/images/MF3.png", "title": "Minimal Futuristic", "repo": "prithivMLmods/Minimal-Futuristic-Flux-LoRA", "weights": "Minimal-Futuristic.safetensors", "trigger_word": "Minimal Futuristic" }, #134 { "image": "https://huggingface.co/prithivMLmods/Seamless-Pattern-Design-Flux-LoRA/resolve/main/images/SP1.png", "title": "Seamless Pattern", "repo": "prithivMLmods/Seamless-Pattern-Design-Flux-LoRA", "weights": "Seamless-Pattern-Design.safetensors", "trigger_word": "Seamless Pattern Design" }, #135 { "image": "https://huggingface.co/prithivMLmods/Logo-Design-Flux-LoRA/resolve/main/images/LD1.png", "title": "Logo Design", "repo": "prithivMLmods/Logo-Design-Flux-LoRA", "weights": "Logo-design.safetensors", "trigger_word": "Logo Design" }, #136 { "image": "https://huggingface.co/prithivMLmods/Coloring-Book-Flux-LoRA/resolve/main/images/EB1.png", "title": "Coloring Book", "repo": "prithivMLmods/Coloring-Book-Flux-LoRA", "weights": "coloring-book.safetensors", "trigger_word": "Coloring Book" }, #137 { "image": "https://huggingface.co/prithivMLmods/Intense-Red-Flux-LoRA/resolve/main/images/IR1.png", "title": "Intense Red", "repo": "prithivMLmods/Intense-Red-Flux-LoRA", "weights": "Intense-Red.safetensors", "trigger_word": "Intense Red" }, #138 { "image": "https://huggingface.co/prithivMLmods/Glowing-Body-Flux-LoRA/resolve/main/images/GB3.png", "title": "Glowing Body Flux", "repo": "prithivMLmods/Glowing-Body-Flux-LoRA", "weights": "Glowing-Body.safetensors", "trigger_word": "Glowing Body" }, #139 { "image": "https://huggingface.co/prithivMLmods/Electric-Blue-Flux-LoRA/resolve/main/images/EB3.png", "title": "Electric Blue", "repo": "prithivMLmods/Electric-Blue-Flux-LoRA", "weights": "Electric-Blue.safetensors", "trigger_word": "Electric Blue" }, #140 { "image": "https://huggingface.co/prithivMLmods/Clouds-Illusion-Flux-LoRA/resolve/main/images/CI2.png", "title": "Clouds Illusion", "repo": "prithivMLmods/Clouds-Illusion-Flux-LoRA", "weights": "Clouds-Illusion.safetensors", "trigger_word": "Clouds Illusion" }, #141 { "image": "https://huggingface.co/prithivMLmods/Digital-Yellow-Flux-LoRA/resolve/main/images/DY3.png", "title": "Digital Yellow", "repo": "prithivMLmods/Digital-Yellow-Flux-LoRA", "weights": "Digital-Yellow.safetensors", "trigger_word": "Digital Yellow" }, #142 { "image": "https://huggingface.co/cfahlgren1/flux-qwen-capybara/resolve/main/images/example_72ao6twvk.png", "title": "Flux Qwen Capybara", "repo": "cfahlgren1/flux-qwen-capybara", "weights": "flux-qwen-capybara.safetensors", "trigger_word": "QWENCAPY" }, #143 { "image": "https://huggingface.co/dasdsff/PleinAirArt/resolve/main/images/e7499ccc-7504-4086-842f-275a5428ef0e.jpg", "title": "Plein Air Art ", "repo": "dasdsff/PleinAirArt", "weights": "PleinAir_000002500.safetensors", "trigger_word": "P1e!n" }, #144 { "image": "https://huggingface.co/prithivMLmods/Orange-Chroma-Flux-LoRA/resolve/main/images/OC1.png", "title": "Orange Chroma", "repo": "prithivMLmods/Orange-Chroma-Flux-LoRA", "weights": "Orange-Chroma.safetensors", "trigger_word": "Orange Chroma" }, #145 { "image": "https://huggingface.co/prithivMLmods/Lime-Green-Flux-LoRA/resolve/main/images/LM1.png", "title": "Lime Green", "repo": "prithivMLmods/Lime-Green-Flux-LoRA", "weights": "Lime-Green.safetensors", "trigger_word": "Lime Green" }, #146 { "image": "https://huggingface.co/prithivMLmods/Fractured-Line-Flare/resolve/main/images/FS1.png", "title": "Line Flare", "repo": "prithivMLmods/Fractured-Line-Flare", "weights": "Fractured-Line-Flare.safetensors", "trigger_word": "Fractured Line Flare" }, #147 { "image": "https://huggingface.co/prithivMLmods/Golden-Dust-Flux-LoRA/resolve/main/images/GD2.png", "title": "Golden Dust", "repo": "prithivMLmods/Golden-Dust-Flux-LoRA", "weights": "Golden-Dust.safetensors", "trigger_word": "Golden Dust" }, #148 { "image": "https://huggingface.co/prithivMLmods/Castor-Dramatic-Neon-Flux-LoRA/resolve/main/images/DN2.webp", "title": "Dramatic Neon", "repo": "prithivMLmods/Castor-Dramatic-Neon-Flux-LoRA", "weights": "Dramatic-Neon-Flux-LoRA.safetensors", "trigger_word": "Dramatic Neon" }, #149 { "image": "https://huggingface.co/tryonlabs/FLUX.1-dev-LoRA-Outfit-Generator/resolve/main/images/sample7.jpeg", "title": "Outfit Generator", "repo": "tryonlabs/FLUX.1-dev-LoRA-Outfit-Generator", "weights": "outfit-generator.safetensors", "trigger_word": "Outfit" }, #150 { "image": "https://huggingface.co/davisbro/half_illustration/resolve/main/images/example1.webp", "title": "Half Illustration", "repo": "davisbro/half_illustration", "weights": "flux_train_replicate.safetensors", "trigger_word": "in the style of TOK" }, #151 { "image": "https://huggingface.co/bingbangboom/flux_oilscape/resolve/main/extras/3.jpg", "title": "Oilscape", "repo": "bingbangboom/flux_oilscape", "weights": "flux_Oilstyle.safetensors", "trigger_word": "in the style of Oilstyle002" }, #152 { "image": "https://huggingface.co/prithivMLmods/Red-Undersea-Flux-LoRA/resolve/main/images/RU1.png", "title": "Red Undersea Flux", "repo": "prithivMLmods/Red-Undersea-Flux-LoRA", "weights": "Red-Undersea.safetensors", "trigger_word": "Red Undersea" }, #153 { "image": "https://huggingface.co/prithivMLmods/3D-Render-Flux-LoRA/resolve/main/images/3D2.png", "title": "3D Render Flux LoRA", "repo": "prithivMLmods/3D-Render-Flux-LoRA", "weights": "3D_Portrait.safetensors", "trigger_word": "3D Portrait, 3d render" }, #154 { "image": "https://huggingface.co/prithivMLmods/Yellow-Pop-Flux-Dev-LoRA/resolve/main/images/YP1.png", "title": "Yellow Pop Flux", "repo": "prithivMLmods/Yellow-Pop-Flux-Dev-LoRA", "weights": "Yellow_Pop.safetensors", "trigger_word": "Yellow Pop" }, #155 { "image": "https://huggingface.co/prithivMLmods/Purple-Grid-Flux-LoRA/resolve/main/images/PG2.png", "title": "Purple Grid Flux", "repo": "prithivMLmods/Purple-Grid-Flux-LoRA", "weights": "Purple_Grid.safetensors", "trigger_word": "Purple Grid" } #add new ] #--------------------------------------------------Model Initialization-----------------------------------------------------------------------------------------# dtype = torch.bfloat16 device = "cuda" if torch.cuda.is_available() else "cpu" base_model = "black-forest-labs/FLUX.1-dev" #TAEF1 is very tiny autoencoder which uses the same "latent API" as FLUX.1's VAE. FLUX.1 is useful for real-time previewing of the FLUX.1 generation process.# taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype).to(device) good_vae = AutoencoderKL.from_pretrained(base_model, subfolder="vae", torch_dtype=dtype).to(device) pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype, vae=taef1) pipe_i2i = AutoPipelineForImage2Image.from_pretrained(base_model, vae=good_vae, transformer=pipe.transformer, text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer, text_encoder_2=pipe.text_encoder_2, tokenizer_2=pipe.tokenizer_2, torch_dtype=dtype ) # CONTROLNET controlnet_model = "InstantX/FLUX.1-dev-controlnet-canny" controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=dtype) pipe_canny = FluxControlNetPipeline.from_pretrained( base_model, controlnet=controlnet, torch_dtype=dtype ) MAX_SEED = 2**32-1 pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe) class calculateDuration: def __init__(self, activity_name=""): self.activity_name = activity_name def __enter__(self): self.start_time = time.time() return self def __exit__(self, exc_type, exc_value, traceback): self.end_time = time.time() self.elapsed_time = self.end_time - self.start_time if self.activity_name: print(f"Elapsed time for {self.activity_name}: {self.elapsed_time:.6f} seconds") else: print(f"Elapsed time: {self.elapsed_time:.6f} seconds") def update_selection(evt: gr.SelectData, width, height): selected_lora = loras[evt.index] new_placeholder = f"Type a prompt for {selected_lora['title']}" lora_repo = selected_lora["repo"] updated_text = f"### Selected: [{lora_repo}](https://huggingface.co/{lora_repo}) ✅" if "aspect" in selected_lora: if selected_lora["aspect"] == "portrait": width = 768 height = 1024 elif selected_lora["aspect"] == "landscape": width = 1024 height = 768 else: width = 1024 height = 1024 return ( gr.update(placeholder=new_placeholder), updated_text, evt.index, width, height, ) import cv2 def generate_canny(image, type="canny"): img = cv2.imread(image) img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) img_blur = cv2.GaussianBlur(img_gray, (3,3), 0) if(type == "canny"): edges = cv2.Canny(image=img_blur, threshold1=100, threshold2=200) cv2.imwrite('output.jpg', edges) return 'output.jpg' if(type == "sobel"): sobelxy = cv2.Sobel(src=img_blur, ddepth=cv2.CV_64F, dx=1, dy=1, ksize=5) cv2.imwrite('output.jpg', sobelxy) return 'output.jpg' return image @spaces.GPU(duration=100) def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scale, progress): generator = torch.Generator(device="cuda").manual_seed(seed) pipe.to('cuda') with calculateDuration("Generating image"): # Generate image for img in pipe.flux_pipe_call_that_returns_an_iterable_of_images( prompt=prompt_mash, num_inference_steps=steps, guidance_scale=cfg_scale, width=width, height=height, generator=generator, joint_attention_kwargs={"scale": lora_scale}, output_type="pil", good_vae=good_vae, ): yield img def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps, cfg_scale, width, height, lora_scale, seed): generator = torch.Generator(device="cuda").manual_seed(seed) pipe_i2i.to('cuda') image_input = load_image(image_input_path) final_image = pipe_i2i( prompt=prompt_mash, image=image_input, strength=image_strength, num_inference_steps=steps, guidance_scale=cfg_scale, width=width, height=height, generator=generator, joint_attention_kwargs={"scale": lora_scale}, output_type="pil", ).images[0] return final_image def generate_image_canny(prompt_mash, canny, image_strength, steps, cfg_scale, width, height, lora_scale, seed): control_image = load_image(canny) generator = torch.Generator(device="cuda").manual_seed(seed) pipe_canny.to('cuda') image = pipe_canny( prompt=prompt_mash, control_image=control_image, controlnet_conditioning_scale=0.6, num_inference_steps=steps, guidance_scale=cfg_scale, width=width, height=height, generator=generator, joint_attention_kwargs={"scale": lora_scale}, output_type="pil", ).images[0] return image @spaces.GPU(duration=100) def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale, useCanny, useSobel, progress=gr.Progress(track_tqdm=True)): if selected_index is None: raise gr.Error("You must select a LoRA before proceeding.🧨") selected_lora = loras[selected_index] lora_path = selected_lora["repo"] trigger_word = selected_lora["trigger_word"] if(trigger_word): if "trigger_position" in selected_lora: if selected_lora["trigger_position"] == "prepend": prompt_mash = f"{trigger_word} {prompt}" else: prompt_mash = f"{prompt} {trigger_word}" else: prompt_mash = f"{trigger_word} {prompt}" else: prompt_mash = prompt with calculateDuration("Unloading LoRA"): pipe.unload_lora_weights() pipe_i2i.unload_lora_weights() #LoRA weights flow with calculateDuration(f"Loading LoRA weights for {selected_lora['title']}"): pipe_to_use = pipe_i2i if image_input is not None else pipe weight_name = selected_lora.get("weights", None) pipe_to_use.load_lora_weights( lora_path, weight_name=weight_name, low_cpu_mem_usage=True ) with calculateDuration("Randomizing seed"): if randomize_seed: seed = random.randint(0, MAX_SEED) if(image_input is not None): if(useCanny): final_image = generate_canny(image_input, "canny") img = generate_image_canny(prompt_mash, final_image, image_strength, steps, cfg_scale, width, height, lora_scale, seed) yield img, final_image, seed, gr.update(visible=False) elif(useSobel): final_image = generate_canny(image_input, "sobel") img = generate_image_canny(prompt_mash, final_image, image_strength, steps, cfg_scale, width, height, lora_scale, seed) yield img, final_image, seed, gr.update(visible=False) else: final_image = generate_image_to_image(prompt_mash, image_input, image_strength, steps, cfg_scale, width, height, lora_scale, seed) yield final_image, final_image, seed, gr.update(visible=False) else: image_generator = generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scale, progress) final_image = None step_counter = 0 for image in image_generator: step_counter+=1 final_image = image progress_bar = f'
' yield image, image, seed, gr.update(value=progress_bar, visible=True) yield final_image,final_image, seed, gr.update(value=progress_bar, visible=False) def get_huggingface_safetensors(link): split_link = link.split("/") if(len(split_link) == 2): model_card = ModelCard.load(link) base_model = model_card.data.get("base_model") print(base_model) #Allows Both if((base_model != "black-forest-labs/FLUX.1-dev") and (base_model != "black-forest-labs/FLUX.1-schnell")): raise Exception("Flux LoRA Not Found!") # Only allow "black-forest-labs/FLUX.1-dev" #if base_model != "black-forest-labs/FLUX.1-dev": #raise Exception("Only FLUX.1-dev is supported, other LoRA models are not allowed!") image_path = model_card.data.get("widget", [{}])[0].get("output", {}).get("url", None) trigger_word = model_card.data.get("instance_prompt", "") image_url = f"https://huggingface.co/{link}/resolve/main/{image_path}" if image_path else None fs = HfFileSystem() try: list_of_files = fs.ls(link, detail=False) for file in list_of_files: if(file.endswith(".safetensors")): safetensors_name = file.split("/")[-1] if (not image_url and file.lower().endswith((".jpg", ".jpeg", ".png", ".webp"))): image_elements = file.split("/") image_url = f"https://huggingface.co/{link}/resolve/main/{image_elements[-1]}" except Exception as e: print(e) gr.Warning(f"You didn't include a link neither a valid Hugging Face repository with a *.safetensors LoRA") raise Exception(f"You didn't include a link neither a valid Hugging Face repository with a *.safetensors LoRA") return split_link[1], link, safetensors_name, trigger_word, image_url def check_custom_model(link): if(link.startswith("https://")): if(link.startswith("https://huggingface.co") or link.startswith("https://www.huggingface.co")): link_split = link.split("huggingface.co/") return get_huggingface_safetensors(link_split[1]) else: return get_huggingface_safetensors(link) def add_custom_lora(custom_lora): global loras if(custom_lora): try: title, repo, path, trigger_word, image = check_custom_model(custom_lora) print(f"Loaded custom LoRA: {repo}") card = f'''
Loaded custom LoRA:

{title}

{"Using: "+trigger_word+" as the trigger word" if trigger_word else "No trigger word found. If there's a trigger word, include it in your prompt"}
''' existing_item_index = next((index for (index, item) in enumerate(loras) if item['repo'] == repo), None) if(not existing_item_index): new_item = { "image": image, "title": title, "repo": repo, "weights": path, "trigger_word": trigger_word } print(new_item) existing_item_index = len(loras) loras.append(new_item) return gr.update(visible=True, value=card), gr.update(visible=True), gr.Gallery(selected_index=None), f"Custom: {path}", existing_item_index, trigger_word except Exception as e: gr.Warning(f"Invalid LoRA: either you entered an invalid link, or a non-FLUX LoRA") return gr.update(visible=True, value=f"Invalid LoRA: either you entered an invalid link, a non-FLUX LoRA"), gr.update(visible=False), gr.update(), "", None, "" else: return gr.update(visible=False), gr.update(visible=False), gr.update(), "", None, "" def remove_custom_lora(): return gr.update(visible=False), gr.update(visible=False), gr.update(), "", None, "" run_lora.zerogpu = True css = ''' #gen_btn{height: 100%} #gen_column{align-self: stretch} #title{text-align: center} #title h1{font-size: 3em; display:inline-flex; align-items:center} #title img{width: 100px; margin-right: 0.5em} #gallery .grid-wrap{height: 10vh} #lora_list{background: var(--block-background-fill);padding: 0 1em .3em; font-size: 90%} .card_internal{display: flex;height: 100px;margin-top: .5em} .card_internal img{margin-right: 1em} .styler{--form-gap-width: 0px !important} #progress{height:30px} #progress .generating{display:none} .progress-container {width: 100%;height: 30px;background-color: #f0f0f0;border-radius: 15px;overflow: hidden;margin-bottom: 20px} .progress-bar {height: 100%;background-color: #4f46e5;width: calc(var(--current) / var(--total) * 100%);transition: width 0.5s ease-in-out} ''' with gr.Blocks(theme="prithivMLmods/Minecraft-Theme", css=css, delete_cache=(60, 60)) as app: title = gr.HTML( """

FLUX LoRA DLC🥳

""", elem_id="title", ) selected_index = gr.State(None) with gr.Row(): with gr.Column(scale=3): prompt = gr.Textbox(label="Prompt", lines=1, placeholder=":/ choose the LoRA and type the prompt ") with gr.Column(scale=1, elem_id="gen_column"): generate_button = gr.Button("Generate", variant="primary", elem_id="gen_btn") with gr.Row(): with gr.Column(): selected_info = gr.Markdown("") gallery = gr.Gallery( [(item["image"], item["title"]) for item in loras], label="LoRA DLC's", allow_preview=False, columns=3, elem_id="gallery", show_share_button=False ) with gr.Group(): custom_lora = gr.Textbox(label="Enter Custom LoRA", placeholder="prithivMLmods/Canopus-LoRA-Flux-Anime") gr.Markdown("[Check the list of FLUX LoRA's](https://huggingface.co/models?other=base_model:adapter:black-forest-labs/FLUX.1-dev)", elem_id="lora_list") custom_lora_info = gr.HTML(visible=False) custom_lora_button = gr.Button("Remove custom LoRA", visible=False) with gr.Column(): progress_bar = gr.Markdown(elem_id="progress",visible=False) result = gr.Image(label="Generated Image") canny = gr.Image(label="Generated Canny") with gr.Row(): with gr.Accordion("Advanced Settings", open=False): with gr.Row(): input_image = gr.Image(label="Input image", type="filepath") image_strength = gr.Slider(label="Denoise Strength", info="Lower means more image influence", minimum=0.1, maximum=1.0, step=0.01, value=0.75) with gr.Column(): with gr.Row(): cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=3.5) steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=28) useCanny = gr.Checkbox(label="use canny") useSobel = gr.Checkbox(label="use Sobel") with gr.Row(): width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024) height = gr.Slider(label="Height", minimum=256, maximum=1536, step=64, value=1024) with gr.Row(): randomize_seed = gr.Checkbox(True, label="Randomize seed") seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True) lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=3, step=0.01, value=0.95) gallery.select( update_selection, inputs=[width, height], outputs=[prompt, selected_info, selected_index, width, height] ) custom_lora.input( add_custom_lora, inputs=[custom_lora], outputs=[custom_lora_info, custom_lora_button, gallery, selected_info, selected_index, prompt] ) custom_lora_button.click( remove_custom_lora, outputs=[custom_lora_info, custom_lora_button, gallery, selected_info, selected_index, custom_lora] ) gr.on( triggers=[generate_button.click, prompt.submit], fn=run_lora, inputs=[prompt, input_image, image_strength, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale, useCanny, useSobel], outputs=[result, canny, seed, progress_bar] ) app.queue() app.launch(share=True)