Fix incorrect sampler name in output

import json

import math

import os

    return image

def get_correct_sampler(p):

    if isinstance(p, modules.processing.StableDiffusionProcessingTxt2Img):

        return sd_samplers.samplers

    elif isinstance(p, modules.processing.StableDiffusionProcessingImg2Img):

        return sd_samplers.samplers_for_img2img

class StableDiffusionProcessing:

    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt="", styles=None, seed=-1, subseed=-1, subseed_strength=0, seed_resize_from_h=-1, seed_resize_from_w=-1, seed_enable_extras=True, sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, restore_faces=False, tiling=False, do_not_save_samples=False, do_not_save_grid=False, extra_generation_params=None, overlay_images=None, negative_prompt=None, eta=None):

        self.sd_model = sd_model

    generation_params = {

        "Steps": p.steps,

        "Sampler": sd_samplers.samplers[p.sampler_index].name,

        "Sampler": get_correct_sampler(p)[p.sampler_index].name,

        "CFG scale": p.cfg_scale,

        "Seed": all_seeds[index],

        "Face restoration": (opts.face_restoration_model if p.restore_faces else None),

import gradio as gr

from modules import images

from modules.processing import process_images, Processed

from modules.processing import process_images, Processed, get_correct_sampler

from modules.shared import opts, cmd_opts, state

import modules.shared as shared

import modules.sd_samplers

    p.prompt = prompt_tmp + p.prompt

def build_samplers_dict(p):

    samplers_dict = {}

for i, sampler in enumerate(modules.sd_samplers.samplers):

    for i, sampler in enumerate(get_correct_sampler(p)):

        samplers_dict[sampler.name.lower()] = i

        for alias in sampler.aliases:

            samplers_dict[alias.lower()] = i

    return samplers_dict

def apply_sampler(p, x, xs):

    sampler_index = samplers_dict.get(x.lower(), None)

    sampler_index = build_samplers_dict(p).get(x.lower(), None)

    if sampler_index is None:

        raise RuntimeError(f"Unknown sampler: {x}")