私的AI研究会 > AI_Program9
これまで検証してきた結果をもとに、Python で生成 AI プログラムを書く
| 画像生成のプログラムを書く |
(base) PS > conda activate sd_test (sd_test) PS > cd workspace_3/sd_test
| Step | プログラム名 | 機能 |
| 81 | sd_081 | 「テキストから画像生成（txt2img）」 |
| 91 | sd_091 | 「画像から画像生成（img2img）」 |
| 40 | sd_040 | 「instruct-pix2pix」で画像を変換する |
| 42 | sd_042 | 「controlnet instruct-pix2pix」で画像を変換する |
| 44 | sd_044 | 「controlnet inpaint」で画像の一部を変換する |
| 46 | sd_046 | 「outpaint」画像の外側を書き加える |
| 47 | sd_047 | 「controlnet scribble」手描きの線画から画像を生成 |
| 48 | sd_048 | 「controlnet openpose」画像から同じ姿勢の画像を生成 |
| 50 | sd_050 | 「顔の崩れを修正する１」 |
| 51 | sd_051 | 「顔の崩れを修正する２「ADetailer」」 |
python sd_100 --pros_sel [081 / 091 / 040 / 042 / 044 / 046 / 047 / 048 / 050 / 051]・将来的にはプログラム内でダイナミックに変更できるようにする
| pros_sel | sd_81 | sd_091 | sd_040 | sd_042 |
| 機能 | テキストから画像生成 | 画像をテキストで変更 | 画像から画像を変換生成 | 画像から画像を変換生成 |
| text2image | image2image | instruct-pix2pix | controlnet instruct-pix2pix | |
| advanced 画面 |  |  |  |  |
| normal 画面 |  |  |  |  |
| pros_sel | sd_044 | sd_046 | sd_047 | sd_048 |
| 機能 | 画像の一部を変更 | 画像の外側を書き加える | 手描きの線画から画像を生成 | 画像から同じ姿勢の画像を生成 |
| controlnet inpaint | outpaint | controlnet scribble | controlnet openpose | |
| advanced 画面 |  |  |  |  |
| normal 画面 |  |  |  |  |
| pros_sel | sd_050 | sd_051 | ||
| 機能 | 顔の崩れを修正する１ | 顔の崩れを修正する２ | ||
| face_recognition inpaint | ADetailer | |||
| advanced 画面 |  |  | ||
| normal 画面 |  |  |
| コマンドオプション | 引数 | 初期値（--pros_sel sd_044 の例） | 意味 | GUI |
| --pros_sel | str | 処理するプログラム名（必須指定） | ||
| --result_image | str | './sd_results3/sd.png' | 保存するファイルパスとヘッダ名の指定 | 〇 |
| --cpu | bool | False | cpu mode. | |
| --log | int | 3 | Log level(-1/0/1/2/3/4/5) | |
| --model_dir | str | '/StabilityMatrix/Data/Models/StableDiffusion' | モデルフォルダのパス | |
| --model_path | str | 'SD1.5/beautifulRealistic_brav5.safetensors' | モデルファイル | 〇 |
| --ctrl_model_dir | str | '/StabilityMatrix/Data/Models/ControlNet' | コントロールネット・モデルフォルダのパス | |
| --ctrl_model_path | str | 'control_v11p_sd15_inpaint_fp16.safetensors' | コントロールネット・モデルファイル | 〇 |
| --image_path | str | 'images/sd_038_test.png' | 入力画像のファイル・パス名 | 〇 |
| --ctrl_image_path | str | 'images/sd_038_test_mask.png' | コントロールネット・入力画像のファイル・パス名 | 〇 |
| --max_size | int | 0 | 入力画像リサイズの最大値（0=入力画像サイズ） | 〇 |
| --prompt | str | '微笑んでいる女性' | 画像生成のためのプロンプト（日本語/英語） | 〇 |
| --seed | int | 12345678 | シード値（-1の時はランダムに生成） | 〇 |
| --width | int | 512 | 生成画像サイズの幅 | 〇 |
| --height | int | 512 | 生成画像サイズの高さ | 〇 |
| --step | int | 20 | 生成ステップ数 | 〇 |
| --scale | float | 7.0 | ガイダンススケール値 | 〇 |
| --image_scale | float | 1.5 | イメージ・ガイダンススケール値 | |
| --cc_scale | float | 1.0 | controlnet conditioning scale | |
| --strength | float | 0.6 | 変化の強さを表すパラメータ | 〇 |
| --neg_prompt | str | '最悪の品質、おかしい人体構造' | 画像生成のためのネガティブ・プロンプト（日本語/英語） | 〇 |
| --ip_image_path | str | '' | IP-Adapter 入力画像（'' の時は IP-Adapter を使用しない） | |
| --ip_scale | float | 0.5 | ip_adapter_scale パラメータ | |
| --mode | bool | True | パラメータ設定モード（advanced/norma） | |
| --ext | str | '' | 拡張機能（Extentions）※ |
python sd_100 --pros_sel [081 / 091 / 040 / 042 / 044 / 046 / 047 / 048 / 050 / 051]
(sd_test) PS python sd_100.py --pros_sel sd_048 Stable Diffusion with diffusers(100) Ver 0.05 <sd_048>: Starting application... --pros_sel : sd_048 --result_image : ./sd_results3/sd.png --cpu : False --log : 3 --model_dir : /StabilityMatrix/Data/Models/StableDiffusion --model_path : SD1.5/beautifulRealistic_brav5.safetensors --ctrl_model_dir : /StabilityMatrix/Data/Models/ControlNet --ctrl_model_path : control_v11p_sd15_openpose_fp16.safetensors --image_path : images/sd_048_test1.png --max_size : 0 --prompt : ダンスを踊る女性 --seed : -1 --step : 20 --neg_prompt : 最悪の品質、おかしい人体構造 --mode : True ** Start 1 ** prompt: Dancing Woman neg_prompt: Worst quality, funny body structure seed: 2292601352 Fetching 11 files: 100%|███████████████████████████████| 11/11 [00:00<?, ?it/s] Loading pipeline components...: 100%|████████████| 6/6 [00:00<00:00, 32.07it/s] 100%|██████████████████████████████████████████| 20/20 [00:02<00:00, 6.93it/s] result_file: ./sd_results3/sd_00012_2292601352.png ** Complete ** 00:00:08 ** Start 1 ** prompt: Dancing Woman neg_prompt: Worst quality, funny body structure seed: 1070611060 Fetching 11 files: 100%|███████████████████████████████| 11/11 [00:00<?, ?it/s] Loading pipeline components...: 100%|████████████| 6/6 [00:00<00:00, 31.88it/s] 100%|██████████████████████████████████████████| 20/20 [00:02<00:00, 7.23it/s] result_file: ./sd_results3/sd_00013_1070611060.png ** Complete ** 00:00:05 Finished.
python sd_100.py --pros_sel sd_081 --prompt '高精細、コーヒーショップで窓際に座っている女性' --ip_image_path 'images/sd_080_test.png' --seed 12345678
python sd_100.py --pros_sel sd_091 --ip_image_path 'images/sd_080_test.png'
python sd_100.py --pros_sel sd_040 --prompt '春の場面にする' --ip_image_path 'images/flower.jpg' --ip_scale 0.2
python sd_100.py --pros_sel sd_042 --ip_image_path 'images/beach.jpg'
python sd_100.py --pros_sel sd_044 --ip_image_path 'images/sd_046_test.png'
python sd_100.py --pros_sel sd_046 --ip_image_path 'images/sd_040_test.png'
python sd_100.py --pros_sel sd_047 --prompt 'ビーチに置かれたオレンジ色のコーヒーカップ' --ip_image_path 'images/beach.jpg'
python sd_100.py --pros_sel sd_048 --seed 4260871861 --step 50 --ip_image_path 'images/fashion.jpg'
# -*- coding: utf-8 -*-
##--------------------------------------------------
## Stable Diffusion with diffusers(100) Ver 0.08
## img2img GUI interface
## 2025.08.02 Masahiro Izutsu
##--------------------------------------------------
## sd_100.py
## Ver 0.00 2025.07.17 Trial version
## Ver 0.05 2025.07.20 sd_100.py 統合版対応
## Ver 0.06 2025.07.27 sd_081 IP-Adapter 対応
## Ver 0.07 2025.08.01 sd_050 対応
## Ver 0.08 2025.08.02 sd_051 ADetailer 対応
# タイトル
title = 'Stable Diffusion with diffusers(100) Ver 0.08'
import warnings
warnings.simplefilter('ignore')
# インポート＆初期設定
import os
import numpy as np
import time
import csv
import cv2
import PySimpleGUI as sg
import my_logging
import my_thumbnail
import my_dialog
import my_imagetool
import sd_tools as sdt
import sd_results as sdr
# 定数定義
DEF_THEME = 'BlueMono'
CANVAS_SIZE = 512
DEF_SEED_VAL = '12345678'
CSV_LOG_FILE = 'result_100.csv'
KEY_CANCEL = '-Cancel-'
KEY_IMAGE = '-Image-'
KEY_INPUT_IMAGE = '-Input_Image-'
KEY_IMAGE_SEL = '-Image_sel-'
KEY_CTRL_IMAGE_SEL = '-Ctrl_Image_sel-'
KEY_MODELSEL = '-Model_sel-'
KEY_CTRL_MODELSEL = '-Ctrl_Model_sel-'
KEY_SEED_INPUT = '-Seed_input-'
KEY_ADVANCED = '-Advanced-'
KEY_EXIT = '-Exit-'
KEY_GENERATE = '-Generate-'
KEY_INPUT_TXT = '-Input_text-'
KEY_CTRL_MODEL_TXT ='-ctrl_model_text-'
KEY_CTRL_IMGPATH_TXT = '--ctrl_image_path_text--'
KEY_MAXSIZE_TXT = '-MaxSize_text-'
KEY_WIDTH_TXT = '--Image_width_text--'
KEY_HEIGHT_TXT = '--Image_height_text--'
KEY_STEP_TXT = '-Step_text-'
KEY_SCALE_TXT = '-Scale_text-'
KEY_STRENGTH_TXT = '-strength_text-'
KEY_SEED_CLR = '--seed_clear--'
KEY_SEED_SET = '--seed_set--'
SKEY_RESULT_PATH = '-result_path-'
SKEY_RESULT_FILE = '-result_file-'
SKEY_DEF_OUTPATH = '-default_image-'
# csv save
KEY_PROS_SEL = '--Proscess--'
KEY_OUTPATH = '-Output-'
KEY_SEED = '-Seed-'
KEY_PROMPT_JP = '-PromptJP-'
KEY_PROMPT = '-Prompt-'
KEY_INPUTPATH = '-Input-'
KEY_MAXSIZE = '-MaxSize-'
KEY_STEP = '-Step-'
KEY_SCALE = '-Scale-'
KEY_STRENGTH = '-strength-'
KEY_MODEL_DIR = '-model_dir-'
KEY_MODEL = '-Model-'
KEY_CTRL_IMGPATH = '--ctrl_image_path--'
KEY_CTRL_DIR = '-ctrl_model_dir-'
KEY_CTRL_MODEL = '-ctrl_model-'
KEY_WIDTH = '--Image_width--'
KEY_HEIGHT = '--Image_height--'
KEY_IMG_SCALE = '--Image_scale--'
KEY_CC_SCALE = '--Control_scale--'
KEY_DEVICE = '-Device-'
KEY_TIME = '-Time-'
KEY_LOOP = '-Loop-'
KEY_NEG_PROMPT_JP = '-Negative_PromptJP-'
KEY_NEG_PROMPT = '-Negative_Prompt-'
KEY_IP_IMGPATH = '-Ip_image_path-'
KEY_IP_SCALE = '-Ip_scale-'
KEY_EXTENTION = '-Extention-'
# ----------
# コマンドライン定義
def_result_image = './sd_results3/sd.png'
def_cpu = 'store_true'
def_log = '3'
def_model_dir = ''
def_model_path = ''
def_ctrl_model_dir = ''
def_ctrl_model_path = ''
def_image_path = ''
def_control_image_path = ''
def_max_size = ''
def_prompt = ''
def_seed = ''
def_width = ''
def_height = ''
def_step = ''
def_scale = ''
def_image_scale = ''
def_cc_scale = ''
def_strength = ''
def_neg_prompt = ''
def_ip_image_path = ''
def_ip_scale = ''
def_mode = 'store_false'
def_ext = ''
opt_list = [
['pros_sel','','sd_100'], # 0
['result_image', def_result_image, 'path to output image file'], # 1
['cpu', def_cpu, 'cpu mode'], # 2
['log', def_log, 'Log level(-1/0/1/2/3/4/5) Default value is \'3\''], # 3
['model_dir', def_model_dir, 'Model directory'], # 4
['model_path', def_model_path, 'Model Path'], # 5
['ctrl_model_dir', def_ctrl_model_dir, 'ControlNet Model directory'], # 6
['ctrl_model_path', def_ctrl_model_path, 'ControlNet Model Path'], # 7
['image_path', def_image_path, 'Sourcs image file path'], # 8
['ctrl_image_path', '', 'Control image file path'], # 9
['max_size', def_max_size, 'image max size (0=source)'], # 10
['prompt', def_prompt, 'Prompt text'], # 11
['seed', def_seed, 'Seed parameter (-1 = rundom)'], # 12
['width', def_width, 'image size width'], # 13
['height', def_height, 'image size height'], # 14
['step', def_step, 'infer step'], # 15
['scale', def_scale, 'gaidanse scale'], # 16
['image_scale', def_image_scale, 'image gaidanse scale'], # 17
['cc_scale', def_cc_scale, 'controlnet conditioning scale'], # 18
['strength', def_strength, 'strength value'], # 19
['neg_prompt', def_neg_prompt, 'Negative Prompt text'], # 20
['ip_image_path', def_ip_image_path, 'IP-Adapter image filr path'], # 21
['ip_scale', def_ip_scale, 'IP-Adapter scale'], # 22
['mode', def_mode, 'aplication mode'],
['ext', def_ext, 'Extensions \'\' or \'girl\' or \'boy\''],
]
# コマンドオプションを設定する
def set_option(opt, sdt_list):
for n in range(len(opt_list)):
if opt_list[n][1] == '':
for n0 in range(len(sd_list)):
if opt_list[n][0] == sd_list[n0][0]: opt_list[n][1] = sd_list[n0][1]
opt_list[0][2] = sd_list[0][2]
if opt.result_image == '': opt.result_image = opt_list[1][1]
if opt.log == '': opt.log = opt_list[3][1]
if opt.model_dir == '': opt.model_dir = opt_list[4][1]
if opt.model_path == '': opt.model_path = opt_list[5][1]
if opt.ctrl_model_dir == '': opt.ctrl_model_dir = opt_list[6][1]
if opt.ctrl_model_path == '': opt.ctrl_model_path = opt_list[7][1]
if opt.image_path == '': opt.image_path = opt_list[8][1]
if opt.ctrl_image_path == '': opt.ctrl_image_path = opt_list[9][1]
if opt.max_size == '': opt.max_size = opt_list[10][1]
if opt.prompt == '': opt.prompt = opt_list[11][1]
if opt.seed == '': opt.seed = opt_list[12][1]
if opt.width == '': opt.width = opt_list[13][1]
if opt.height == '': opt.height = opt_list[14][1]
if opt.step == '': opt.step = opt_list[15][1]
if opt.scale == '': opt.scale = opt_list[16][1]
if opt.image_scale == '': opt.image_scale = opt_list[17][1]
if opt.cc_scale == '': opt.cc_scale = opt_list[18][1]
if opt.strength == '': opt.strength = opt_list[19][1]
if opt.neg_prompt == '': opt.neg_prompt = opt_list[20][1]
def set_pros_hedder(pros):
opt_list[0][2] = pros
sdt.opt_list[0][2] = pros
sdr.opt_list[0][2] = pros
# ウィジェットのデータの取得（1回目）
def get_paramlist(window, values, param):
param[KEY_MODEL] = window[KEY_MODEL].DisplayText
param[KEY_MAXSIZE] = int(values[KEY_MAXSIZE])
param[KEY_SEED] = sdt.get_random_seed_value(values[KEY_SEED_INPUT])
param[KEY_WIDTH] = int(values[KEY_WIDTH])
param[KEY_HEIGHT] = int(values[KEY_HEIGHT])
param[KEY_STEP] = int(values[KEY_STEP])
param[KEY_SCALE] = float(values[KEY_SCALE])
param[KEY_STRENGTH] = float(values[KEY_STRENGTH])
param[KEY_PROMPT_JP] = values[KEY_PROMPT_JP]
param[KEY_PROMPT] = sdt.trans_jp2en(param[KEY_PROMPT_JP])
param[KEY_NEG_PROMPT_JP] = values[KEY_NEG_PROMPT_JP]
param[KEY_NEG_PROMPT] = sdt.trans_jp2en(param[KEY_NEG_PROMPT_JP])
param[KEY_CTRL_MODEL] = window[KEY_CTRL_MODEL].DisplayText
param[KEY_LOOP] = int(values[KEY_LOOP])
if param[KEY_LOOP] < 1:
param[KEY_LOOP] = 1
if param[KEY_LOOP] > 50:
param[KEY_LOOP] = 50
# ウィジェットのデータの取得（2回目以降）
def get_paramlist2(window, values, param):
if int(values[KEY_SEED_INPUT]) > 0:
param[KEY_SEED] = param[KEY_SEED] + 1
else:
param[KEY_SEED] = sdt.get_random_seed_value(values[KEY_SEED_INPUT])
# マスク画像ファイル名を得る（sd_044）
def get_mask_file(imgfile):
s = os.path.splitext(imgfile)
if len(s[0]) > 5 and s[0][-5:] == '_mask': return ''
m_path = s[0] + '_mask' + s[1]
mskfile = m_path if os.path.isfile(m_path) else ''
logger.debug(f'mask file: {mskfile｝')
return mskfile
# 画像生成
def generate_image(param, logger = None):
pros_sel = sdt._get_process_name(opt_list) # pros_sel 処理方法
image_path_save = param[KEY_INPUTPATH] # image_path push
# 前処理
if pros_sel == 'sd_048':
image_path = param[KEY_INPUTPATH]
if not sdt.is_pose(image_path):
pose_path = sd.pre_generation(image_path, logger)
param[KEY_INPUTPATH] = pose_path
param[KEY_CTRL_IMGPATH] = pose_path # ポーズ画像
if pros_sel == 'sd_047':
image_path = param[KEY_INPUTPATH]
if sdt.get_image_channel(image_path) == 3:
img = cv2.imread(image_path)
msk = sdt.line_drawing_image(img)
src_path, mask_path = sdt.get_source_mask_path(image_path, logger)
sdt.image_save(msk, mask_path, dispname = mask_path, wait_s = 1) # 1秒 wait
param[KEY_CTRL_IMGPATH] = mask_path # 生成マスク画像
if pros_sel == 'sd_046':
image_path = param[KEY_INPUTPATH]
src_path, mask_path = sd.pre_generation(image_path, logger)
param[KEY_INPUTPATH] = src_path
param[KEY_CTRL_IMGPATH] = mask_path
if pros_sel == 'sd_044':
image_path = param[KEY_INPUTPATH]
mask_path = get_mask_file(image_path)
param[KEY_CTRL_IMGPATH] = mask_path
if pros_sel == 'sd_081':
if param[KEY_IP_IMGPATH] == '':
image_path = param[KEY_INPUTPATH]
param[KEY_IP_IMGPATH] = image_path # 入力画像を IP-Adapter
param[KEY_INPUTPATH] = ''
model = param[KEY_MODEL] if param[KEY_MODEL_DIR] == '' else param[KEY_MODEL_DIR] + '/' + param[KEY_MODEL]
image_path = param[KEY_INPUTPATH]
prompt = param[KEY_PROMPT]
max_size = param[KEY_MAXSIZE]
seed = param[KEY_SEED]
num_inference_steps = param[KEY_STEP]
guidance_scale = param[KEY_SCALE]
strength = param[KEY_STRENGTH]
device = param[KEY_DEVICE]
out_path = param[SKEY_RESULT_PATH] + '/' + sdt.make_filename_by_seq(param[SKEY_RESULT_PATH], param[SKEY_RESULT_FILE], seq_digit = 5, ex = seed)
param[KEY_OUTPATH] = out_path
ctrl_model_dir = param[KEY_CTRL_DIR]
ctrl_model_path = param[KEY_CTRL_MODEL] if param[KEY_CTRL_DIR] == '' else param[KEY_CTRL_DIR] + '/' + param[KEY_CTRL_MODEL]
width = param[KEY_WIDTH]
height = param[KEY_HEIGHT]
cc_scale = param[KEY_CC_SCALE]
img_scale = param[KEY_IMG_SCALE]
neg_prompt = param[KEY_NEG_PROMPT]
ip_image_path = param[KEY_IP_IMGPATH]
ip_scale = param[KEY_IP_SCALE]
if ip_scale == '': ip_scale = 0.5
extention = param[KEY_EXTENTION]
logger.debug(f'** pros_sel: {pros_sel｝')
logger.debug(f'model: {model｝')
logger.info(f'prompt: {prompt｝')
logger.info(f'neg_prompt: {neg_prompt｝')
logger.info(f'image_path: {image_path｝')
logger.debug(f'max_size: {max_size｝')
logger.info(f'seed: {seed｝')
logger.debug(f'num_inference_steps: {num_inference_steps｝')
logger.debug(f'guidance_scale: {guidance_scale｝')
logger.debug(f'strength: {strength｝')
logger.debug(f'device: {device｝')
logger.debug(f'loop: {param[KEY_LOOP]｝')
logger.debug(f'out_path: {out_path｝')
logger.debug(f'ctrl_model_path: {ctrl_model_path｝')
if ip_image_path == '':
logger.debug(f'IP-Adapter image: {ip_image_path｝')
else:
logger.info(f'IP-Adapter image: {ip_image_path｝')
logger.info(f'IP-Adapter scale: {ip_scale｝')
src_image = None # 元画像
ip_image = None # IP 画像
if image_path != '': src_image = sdt._get_resize_image(image_path, max_size, logger)
if ip_image_path != '': ip_image = sdt._get_resize_image(ip_image_path, max_size, logger)
if pros_sel == 'sd_040':
image = sd.image_generation(model, src_image, prompt, seed, num_inference_steps, width, height, guidance_scale, img_scale, neg_prompt, ip_image, ip_scale, device)
elif pros_sel == 'sd_042':
image = sd.image_generation(model, ctrl_model_path, src_image, prompt, seed, num_inference_steps, width, height, guidance_scale, cc_scale, neg_prompt, ip_image, ip_scale, device)
elif pros_sel == 'sd_044' or pros_sel == 'sd_046':
ctrl_image_path = param[KEY_CTRL_IMGPATH]
sdt.image_disp(ctrl_image_path, ctrl_image_path, wait_s = 1) # マスク表示
msk_image = sdt._get_resize_image(ctrl_image_path, max_size, logger)
img_ctrl = sdt.make_inpaint_condition(src_image, msk_image) # コントロール画像
image = sd.image_generation(model, ctrl_model_path, src_image, msk_image, img_ctrl, prompt, seed, num_inference_steps, width, height, guidance_scale, cc_scale, strength, neg_prompt, ip_image, ip_scale, device)
elif pros_sel == 'sd_047':
image = sd.image_generation(model, ctrl_model_path, src_image, prompt, seed, num_inference_steps, neg_prompt, ip_image, ip_scale, device)
elif pros_sel == 'sd_048':
if extention =="":
image = sd.image_generation(model, ctrl_model_path, src_image, prompt, seed, num_inference_steps, neg_prompt, ip_image, ip_scale, device)
else:
image = sd.image_generation_ad(extention, model, ctrl_model_path, src_image, prompt, seed, num_inference_steps, neg_prompt, ip_image, ip_scale, device)
elif pros_sel == 'sd_050':
image = sd.image_generation(model, image_path_save, prompt, seed, num_inference_steps, width, height, guidance_scale, strength, neg_prompt = neg_prompt, device = device)
elif pros_sel == 'sd_051':
image = sd.image_generation_ex(extention, src_image, device, prompt, model, seed, num_inference_steps)
elif pros_sel == 'sd_091':
image = sd.image_generation(model, prompt, src_image, seed, num_inference_steps, guidance_scale, strength, neg_prompt, ip_image, ip_scale, device)
elif pros_sel == 'sd_081':
image = sd.image_generation(model, prompt, seed, num_inference_steps, guidance_scale, width, height, neg_prompt, ip_image, ip_scale, device)
if image is None:
logger.info(f'{sdt.RED｝Unable to generate image !!{sdt.NOCOLOR｝')
else:
image.save(out_path)
logger.info(f'result_file: {out_path｝')
param[KEY_INPUTPATH] = image_path_save # image_path pop
sdt.device_empty_cache(device) # メモリー開放
# ** main関数 **
def main(opt, logger = None):
# ------------------------------------------
# キャンバスをクリア
def clear_canvas(key, msg, color):
frame = np.zeros((CANVAS_SIZE, CANVAS_SIZE, 3), np.uint8)
frame[:,:,] = 0xf0
return msg_out_canvas(key, frame, msg, color)
def msg_out_canvas(key, frame, msg, color):
x0,y0,x1,y1 = cv2_putText(img=frame, text=msg, org=(CANVAS_SIZE//2, CANVAS_SIZE//2), fontFace=font_face, fontScale=16, color=color, mode=2,areaf=True)
cv2.rectangle(frame,(x0-8, y0), (x1+8, y1), (0xf0,0xf0,0xf0), -1)
img = cv2_putText(img=frame, text=msg, org=(CANVAS_SIZE//2, CANVAS_SIZE//2), fontFace=font_face, fontScale=16, color=color, mode=2)
img = cv2.imencode('.png', frame)[1].tobytes()
window[key].update(img)
return frame
# キャンバスへ画像の表示
def update_canvas(key, imgfile):
if os.path.isfile(imgfile):
frame = cv2.imread(imgfile)
frame = my_imagetool.frame_square(frame, (240, 240, 240))
frame = cv2.resize(frame, dsize = (CANVAS_SIZE, CANVAS_SIZE))
img = cv2.imencode('.png', frame)[1].tobytes()
window[key].update(img)
else:
msg = 'Input Image' if key == KEY_INPUT_IMAGE else 'Generate Image'
frame = clear_canvas(key, msg, (0,0,0))
return frame
# ウイジェットの更新
def update_widget():
frame = update_canvas(KEY_IMAGE, param[KEY_OUTPATH])
frame_input = update_canvas(KEY_INPUT_IMAGE, param[KEY_INPUTPATH])
window[KEY_OUTPATH].update(param[KEY_OUTPATH])
window[KEY_SEED].update(param[KEY_SEED_INPUT]) # シード値の表示
window[KEY_PROMPT_JP].update(param[KEY_PROMPT_JP])
window[KEY_PROMPT].update(param[KEY_PROMPT])
window[KEY_INPUTPATH].update(param[KEY_INPUTPATH])
window[KEY_MODEL].update(param[KEY_MODEL])
window[KEY_MAXSIZE].update(param[KEY_MAXSIZE])
window[KEY_STEP].update(param[KEY_STEP])
window[KEY_SCALE].update(param[KEY_SCALE])
window[KEY_STRENGTH].update(param[KEY_STRENGTH])
window[KEY_NEG_PROMPT_JP].update(param[KEY_NEG_PROMPT_JP])
window[KEY_NEG_PROMPT].update(param[KEY_NEG_PROMPT])
window[KEY_WIDTH].update(param[KEY_WIDTH])
window[KEY_HEIGHT].update(param[KEY_HEIGHT])
window[KEY_CTRL_MODEL].update(param[KEY_CTRL_MODEL])
window[KEY_CTRL_IMGPATH].update(param[KEY_CTRL_IMGPATH])
return frame
# ウイジェットの禁止・許可
def set_enb_dis(disabled):
window[KEY_IMAGE_SEL].update(disabled = disabled)
window[KEY_MODELSEL].update(disabled = disabled)
window[KEY_GENERATE].update(disabled = disabled)
window[KEY_LOOP].update(disabled = disabled)
window[KEY_EXIT].update(disabled = disabled)
# モード変更
def change_mode(advanced):
pros_sel = sdt._get_process_name(opt_list) # pros_sel 処理方法
enb = pros_sel != 'sd_081'
window[KEY_CTRL_MODEL_TXT].update(visible = advanced and enb)
window[KEY_CTRL_MODEL].update(visible = advanced and enb)
window[KEY_CTRL_MODELSEL].update(visible = advanced and enb)
window[KEY_MAXSIZE_TXT].update(visible = advanced)
window[KEY_MAXSIZE].update(visible = advanced)
window[KEY_STEP_TXT].update(visible = advanced)
window[KEY_STEP].update(visible = advanced)
window[KEY_SCALE_TXT].update(visible = advanced)
window[KEY_SCALE].update(visible = advanced)
enb = pros_sel != 'sd_040' and pros_sel != 'sd_081'
window[KEY_STRENGTH_TXT].update(visible = advanced and enb)
window[KEY_STRENGTH].update(visible = advanced and enb)
enb = pros_sel == 'sd_044' or pros_sel == 'sd_046' or pros_sel == 'sd_047' or pros_sel == 'sd_048'
window[KEY_CTRL_IMGPATH_TXT].update(visible = advanced and enb)
window[KEY_CTRL_IMGPATH].update(visible = advanced and enb)
window[KEY_CTRL_IMAGE_SEL].update(visible = advanced and enb)
# ------------------------------------------
# パラメータ設定
pros_sel = sdt._get_process_name(opt_list) # pros_sel 処理方法
advanced = opt.mode
device = sdt._get_device(opt, logger)
result_path = sdt._get_result_path(opt, logger)
result_file = sdt._get_result_file(opt, logger)
image_path = sdt._get_source_image_path(opt, logger)
prompt = sdt._get_prompt(opt, logger)
model_path = sdt._get_model_path(opt, logger)
max_size = sdt._get_max_size(opt, logger)
height, width = sdt._get_image_size(opt, logger)
seed = DEF_SEED_VAL
num_inference_steps = sdt._get_inference_steps(opt, logger)
guidance_scale = sdt._get_guidance_scale(opt, logger)
strength = sdt._get_strength(opt, logger)
neg_prompt = sdt._get_negative_prompt(opt, logger)
ip_image_path = sdt._get_ip_image_path(opt, logger)
ip_scale = sdt._get_ip_scale(opt, logger)
param = sdr.param
param[KEY_PROS_SEL] = pros_sel
param[KEY_OUTPATH] = ''
param[KEY_PROMPT_JP] = opt.prompt
param[KEY_PROMPT] = prompt
param[KEY_INPUTPATH] = image_path
param[KEY_MODEL] = opt.model_path
param[KEY_MAXSIZE] = max_size
param[KEY_SEED_INPUT] = opt.seed
param[KEY_SEED] = seed
param[KEY_STEP] = num_inference_steps
param[KEY_SCALE] = guidance_scale
param[KEY_STRENGTH] = strength
param[KEY_DEVICE] = device
param[KEY_LOOP] = 1
param[KEY_TIME] = sdt.elapsed_time_str(0)
param[SKEY_RESULT_PATH] = result_path
param[SKEY_RESULT_FILE] = result_file
param[KEY_MODEL_DIR] = opt.model_dir
param[KEY_CTRL_IMGPATH] = sdt._get_control_image_path(opt, logger)
param[KEY_CTRL_DIR] = sdt._get_controlnet_model_dir(opt, logger)
param[KEY_CTRL_MODEL] = opt.ctrl_model_path
param[KEY_WIDTH] = width
param[KEY_HEIGHT] = height
param[KEY_IMG_SCALE] = sdt._get_image_guidance_scale(opt, logger)
param[KEY_CC_SCALE] = sdt._get_controlnet_conditioning_scale(opt, logger)
param[KEY_NEG_PROMPT_JP] = opt.neg_prompt
param[KEY_NEG_PROMPT] = neg_prompt
param[KEY_IP_IMGPATH] = ip_image_path
param[KEY_IP_SCALE] = ip_scale
param[KEY_EXTENTION] = opt.ext
sdr.logout_data(param, logger)
csvfile = param[SKEY_RESULT_PATH]+ '/' + CSV_LOG_FILE # 出力画像ログファイル名
# 出力フォルダ
os.makedirs(result_path, exist_ok = True)
# フォント取得
from my_puttext import get_font, cv2_putText
font_face = get_font()
# ウィンドウのテーマ
sg.theme(DEF_THEME)
canvas_input_img = sg.Image(size = (CANVAS_SIZE, CANVAS_SIZE), key=KEY_INPUT_IMAGE)
canvas_img = sg.Image(size = (CANVAS_SIZE, CANVAS_SIZE), key=KEY_IMAGE)
# モードボタン初期設定
if advanced:
b0 = 'Advance'
b1 = 'LightCyan'
b2 = 'cornflower blue'
else:
b0 = 'Normal'
b1 = 'cornflower blue'
b2 = 'LightCyan'
col_left = [
[canvas_input_img],
[sg.Text("Input File", size=(14, 1), key=KEY_INPUT_TXT), sg.Text(param[KEY_INPUTPATH], size=(39,1), text_color='#008800', background_color='LightSteelBlue1', key=KEY_INPUTPATH), sg.Button('Image', size=(6, 1), key=KEY_IMAGE_SEL)],
[sg.Text("Model", size=(14, 1)), sg.Text(param[KEY_MODEL], size=(39,1), text_color='#008800', background_color='LightSteelBlue1', key=KEY_MODEL), sg.Button('Model', size=(6, 1), key=KEY_MODELSEL)],
[sg.Text("Prompt input", size=(14, 1)), sg.Multiline(param[KEY_PROMPT_JP], size=(52,2), key=KEY_PROMPT_JP)],
[sg.Text("Prompt", size=(14, 1)), sg.Multiline(param[KEY_PROMPT], size=(52,2), text_color='#008800', background_color='LightSteelBlue1', key=KEY_PROMPT)],
[sg.Text("Negative Prompt in", size=(14, 1)), sg.Multiline(param[KEY_NEG_PROMPT_JP], size=(52,2), key=KEY_NEG_PROMPT_JP)],
[sg.Text("Negative Prompt", size=(14, 1)), sg.Multiline(param[KEY_NEG_PROMPT], size=(52,2), text_color='#008800', background_color='LightSteelBlue1', key=KEY_NEG_PROMPT)],
[sg.Text("ControlNet File", size=(14, 1), key=KEY_CTRL_IMGPATH_TXT), sg.Text(param[KEY_CTRL_IMGPATH], size=(39,1), text_color='#008800', background_color='LightSteelBlue1', key=KEY_CTRL_IMGPATH), sg.Button('C Image', size=(6, 1), key=KEY_CTRL_IMAGE_SEL)],
]
col_right = [
[canvas_img],
[sg.Text("Output File", size=(14, 1)), sg.Text(param[KEY_OUTPATH], size=(39,1), key=KEY_OUTPATH), sg.Button(b0, button_color=(b1, b2), size=(6, 1), key=KEY_ADVANCED)],
[sg.Text("ControlNet Model", size=(14, 1), key=KEY_CTRL_MODEL_TXT), sg.Text(param[KEY_CTRL_MODEL], size=(39,1), text_color='#008800', background_color='LightSteelBlue1', key=KEY_CTRL_MODEL), sg.Button('C Model', size=(6, 1), key=KEY_CTRL_MODELSEL)],
[sg.Text("Gen Image Width", size=(14, 1), key=KEY_WIDTH_TXT), sg.Input(param[KEY_WIDTH], size=(10,1), key=KEY_WIDTH), sg.Text("Height", size=(5, 1), key=KEY_HEIGHT_TXT), sg.Input(param[KEY_HEIGHT], size=(10,1), key=KEY_HEIGHT), sg.Text(" Max size", size=(8, 1), key=KEY_MAXSIZE_TXT), sg.Input(param[KEY_MAXSIZE], size=(10,1), key=KEY_MAXSIZE)],
[sg.Text("Seed (-1=Random)", size=(14, 1)), sg.Input(param[KEY_SEED_INPUT], size=(18,1), key=KEY_SEED_INPUT), sg.Button('←', size=(4, 1), key=KEY_SEED_SET), sg.Text(param[KEY_SEED], size=(14,1), text_color='#008800', background_color='LightSteelBlue1', key=KEY_SEED), sg.Button('-1', size=(5, 1), key=KEY_SEED_CLR)],
[sg.Text("Detail (Steps)", size=(14, 1), key=KEY_STEP_TXT), sg.Slider((10, 150), float(param[KEY_STEP]), 1, orientation='h', size=(42, 5), key=KEY_STEP)],
[sg.Text("Guidance Scale", size=(14, 1), key=KEY_SCALE_TXT), sg.Slider((1, 50), float(param[KEY_SCALE]), 0.1, orientation='h', size=(42, 5), key=KEY_SCALE)],
[sg.Text("Strength", size=(14, 1), key=KEY_STRENGTH_TXT), sg.Slider((0, 1), float(param[KEY_STRENGTH]), 0.1, orientation='h', size=(42, 5), key=KEY_STRENGTH)],
[sg.Text("", size=(14, 1))],
[sg.Text("Loop count (1-50)", size=(14, 1)), sg.Input(param[KEY_LOOP], size=(2,1), justification='right', key=KEY_LOOP), sg.Text("", size=(2, 1)), sg.Button('Generate', size=(10, 1), key=KEY_GENERATE), sg.Text("", size=(8, 1)), sg.Button('Exit', size=(10, 1), key=KEY_EXIT)]
]
# ウィンドウのレイアウト
layout = [[sg.Column(col_left, vertical_alignment='top'), sg.Column(col_right, vertical_alignment='top')]]
# ウィンドウオブジェクトの作成
window = sg.Window(title, layout, finalize=True, return_keyboard_events=True, disable_close=True) #「X」無効
# ユーザーイベントの定義
canvas_img.bind('<ButtonPress>', '_click_on')
canvas_input_img.bind('<ButtonPress>', '_click_on')
# キャンバス初期化
pros_sel = sdt._get_process_name(opt_list) # pros_sel 処理方法
ss = param[KEY_SEED_INPUT] # 最初のシード入力値
if pros_sel == 'sd_081' and param[KEY_IP_IMGPATH] != '':
param[KEY_INPUTPATH] = param[KEY_IP_IMGPATH] # IP-Adapter を 入力画像
bf = False # 常に初期化する 2025/07/28
# bf = sdr.read_result_csv(csvfile, param, logger, '1')
if bf:
frame = update_widget()
param[KEY_SEED] = param[KEY_SEED_INPUT]
param[KEY_SEED_INPUT] = ss
window[KEY_SEED].update(param[KEY_SEED])
window[KEY_SEED_INPUT].update(param[KEY_SEED_INPUT] )
else:
frame = update_canvas(KEY_IMAGE, param[KEY_OUTPATH])
frame_input = update_canvas(KEY_INPUT_IMAGE, param[KEY_INPUTPATH])
param[SKEY_DEF_OUTPATH] = param[KEY_OUTPATH] # 現在の画像パス
new_make_f = False
window[KEY_PROMPT].update(disabled = True)
change_mode(advanced)
# イベントのループ
while True:
event, values = window.read(timeout = 30)
# 画像生成
if new_make_f:
# 処理プロセス
logger.info(f'{sdt.CYAN｝** Start {param[KEY_LOOP]｝ **{sdt.NOCOLOR｝')
input_img_path = param[KEY_INPUTPATH]
start_time = time.time()
generate_image(param, logger)
param[KEY_TIME] = sdt.elapsed_time_str(time.time() - start_time)
sdr.result_csv(csvfile, param, logger)
frame = update_canvas(KEY_IMAGE, param[KEY_OUTPATH])
param[SKEY_DEF_OUTPATH] = param[KEY_OUTPATH] # 現在の画像パス
window[KEY_OUTPATH].update(param[KEY_OUTPATH])
param[KEY_LOOP] = param[KEY_LOOP] - 1
window[KEY_LOOP].update(param[KEY_LOOP])
if input_img_path != param[KEY_INPUTPATH]:
frame_input = update_canvas(KEY_INPUT_IMAGE, param[KEY_INPUTPATH])
window[KEY_INPUTPATH].update(param[KEY_INPUTPATH] )
if param[KEY_LOOP] < 1:
param[KEY_LOOP] = 1
window[KEY_LOOP].update(param[KEY_LOOP])
set_enb_dis(False)
new_make_f = False
else:
get_paramlist2(window, values, param)
window[KEY_SEED].update(param[KEY_SEED])
logger.info(f'{sdt.CYAN｝** Complete **{sdt.NOCOLOR｝ {param[KEY_TIME]｝')
# 終了
if event == KEY_EXIT or event == sg.WIN_CLOSED:
break
# KEY_IMAGE
if event == KEY_IMAGE + '_click_on':
logger.debug(f'{event｝')
set_enb_dis(True)
def_file = param[SKEY_DEF_OUTPATH]
if os.path.isfile(def_file):
imgfile = sdr.image_dialog(param, csvfile, def_file, title='Result Image file select', xn=10, yn=3, thumb_size=128, gap=4, logger=logger)
if os.path.isfile(imgfile):
logger.debug(f'Output select: {imgfile｝')
bf = sdr.read_result_csv(csvfile, param, logger, imgfile)
if bf:
frame = update_widget()
param[SKEY_DEF_OUTPATH] = param[KEY_OUTPATH]
else:
sdr.read_result_csv(csvfile, param, logger, def_file)
frame = update_widget()
param[SKEY_DEF_OUTPATH] = param[KEY_OUTPATH]
set_enb_dis(False)
# KEY_INPUT_IMAGE
if event == KEY_INPUT_IMAGE + '_click_on':
logger.debug(f'{event｝')
set_enb_dis(True)
def_file = param[KEY_INPUTPATH]
if os.path.isfile(def_file):
imgfile = my_thumbnail.image_dialog(def_file, 'Image file select', my_thumbnail.DEF_THEME, 10, 4, ret = '', logger = logger)
bf = True
if pros_sel == 'sd_044':
mskfile = get_mask_file(imgfile)
if mskfile != '':
param[KEY_CTRL_IMGPATH] = mskfile
else:
bf = False
if bf and os.path.isfile(imgfile):
logger.debug(f'Input select: {imgfile｝')
param[KEY_INPUTPATH] = imgfile
update_widget()
set_enb_dis(False)
# モード・チェンジ
if event == KEY_ADVANCED:
logger.debug(f'{event｝ {not advanced｝')
if advanced:
window[KEY_ADVANCED].update('Normal', button_color=('cornflower blue', 'LightCyan'))
advanced = False
else:
window[KEY_ADVANCED].update('Advance', button_color=('LightCyan', 'cornflower blue'))
advanced = True
change_mode(advanced)
# シード値セット・ボタン
if event == KEY_SEED_SET:
logger.debug(f'{event｝')
window[KEY_SEED_INPUT].update(param[KEY_SEED])
# シード値クリア・ボタン
if event == KEY_SEED_CLR:
logger.debug(f'{event｝')
window[KEY_SEED_INPUT].update('-1')
# 画像選択ボタン
if event == KEY_IMAGE_SEL:
logger.debug(f'{event｝')
set_enb_dis(True)
imgfile = my_dialog.select_image_file(initdir=os.path.dirname(param[KEY_INPUTPATH]))
bf = True
if pros_sel == 'sd_044':
mskfile = get_mask_file(imgfile)
if mskfile != '':
param[KEY_CTRL_IMGPATH] = mskfile
else:
bf = False
if bf and len(imgfile) > 0:
logger.debug(f'Input select: {imgfile｝')
param[KEY_INPUTPATH] = imgfile
frame_input = update_canvas(KEY_INPUT_IMAGE, param[KEY_INPUTPATH])
window[KEY_INPUTPATH].update(param[KEY_INPUTPATH])
set_enb_dis(False)
# Model ボタン
if event == KEY_MODELSEL:
logger.debug(f'{event｝')
set_enb_dis(True)
s0 = param[KEY_MODEL]
id = s0.find('/')
s1 = '/' + s0[:id] if id > 0 else ''
s2 = param[KEY_MODEL_DIR] + s1
ttl = 'モデルファイルを選択'
types = [("Model file", ".safetensors .pt"), ("model", ".safetensors"), ("pt file", ".pt") ]
filename = my_dialog.file_dialog(ttl, types, s2)
if len(filename) > 0:
s3 = os.path.basename(filename) # ファイル名
s4 = os.path.dirname(filename) # ディレクトリ名
id = s4.find('SD1.5')
if id >= 0 and id == len(s4) - 5: # SD1.5
s5 = s4[:id - 1]
s3 = 'SD1.5/' + s3
else: # SDXL
s5 = s4
param[KEY_MODEL] = s3
s6 = os.path.abspath(param[KEY_MODEL_DIR])
s7 = s6.replace('\\', '/')
if s7 == s5: # モデルディレクトリは変更不可
window[KEY_MODEL].update(param[KEY_MODEL])
logger.debug(f'{param[KEY_MODEL_DIR]｝/{param[KEY_MODEL]｝')
else:
my_dialog.warning_dialog(ttl, 'モデルディレクトリは変更できません')
set_enb_dis(False)
# Genarate ボタン
if event == KEY_GENERATE:
logger.debug(f'{event｝')
set_enb_dis(True)
get_paramlist(window, values, param)
frame = msg_out_canvas(KEY_IMAGE, frame, 'Generating ...', (240,0,0))
window[KEY_OUTPATH].update('')
window[KEY_PROMPT].update(param[KEY_PROMPT])
window[KEY_SEED].update(param[KEY_SEED])
window[KEY_NEG_PROMPT].update(param[KEY_NEG_PROMPT])
new_make_f = True
# ウィンドウ終了処理
window.close()
# main関数エントリーポイント(実行開始)
if __name__ == "__main__":
# コマンドライン入力設定
parser = sdt.parse_args(None, opt_list)
opt = parser.parse_args()
if opt.pros_sel == 'sd_040': import sd_040 as sd
elif opt.pros_sel == 'sd_042': import sd_042 as sd
elif opt.pros_sel == 'sd_044': import sd_044 as sd
elif opt.pros_sel == 'sd_046': import sd_046 as sd
elif opt.pros_sel == 'sd_047': import sd_047 as sd
elif opt.pros_sel == 'sd_048': import sd_048 as sd
elif opt.pros_sel == 'sd_050': import sd_050 as sd
elif opt.pros_sel == 'sd_051': import sd_051 as sd
elif opt.pros_sel == 'sd_091': import sd_091 as sd
elif opt.pros_sel == 'sd_081': import sd_081 as sd
else: exit(0)
# オプションリスト変更
sd_list = sd.opt_list
set_option(opt, sd_list)
title = title + ' <' + opt.pros_sel + '>'
set_pros_hedder(opt.pros_sel)
# アプリケーション・ログ設定
module = os.path.basename(__file__)
module_name = os.path.splitext(module)[0]
logger = my_logging.get_module_logger_sel(module_name, int(opt.log))
sdt._get_device(opt)
sdt.display_info(opt, title)
main(opt, logger)
logger.info('\nFinished.\n')
※ 上記ソースコードは表示の都合上、半角コード '}' が 全角 '｝'になっていることに注意
python sd_mask.py
(sd_test) python sd_mask.py Stable Diffusion with diffusers (sd_mask) Ver 0.01: Starting application... --image_path : images/heron.jpg --log : 3 result_file: D:/anaconda_win/workspace_3/sd_test/images_work/dog_mask.png Finished.
| 機能 | 戻り値 | 関数 |
| マスク作成 | - | mask_paint(image_path, work_path, chenge = True, logger = None) |
| 機能 | 戻り値 | 関数 |
| 結果を CSV ファイルに残す | - | result_csv(csvfile, param, logger) |
| 結果ログからパラメータを取得 | bool | read_result_csv(csvfile, param, logger, imgfile = '0', pros_f = False) |
| 動的パラメータの出力 | - | logout_data(param, logger) |
| 生成画選択ダイアログ | image_file | image_dialog(param, csvfile, file_path, title='', theme=DEF_THEME, xn=10, yn=3, thumb_size=128, gap=4, file_ext=my_thumbnail.IMAGE_EXT, logger=None) |
# -*- coding: utf-8 -*-
##--------------------------------------------------
## sd_test basic tools for results Ver 0.07
##
## 2025.08.02 Masahiro Izutsu
##--------------------------------------------------
## sd_results.py
## Ver 0.00 2025.07.17 Trial version
## Ver 0.05 2025.07.21 sd_100.py 統合版対応
## Ver 0.06 2025.07.27 sd_081 IP-Adapter 対応
## Ver 0.07 2025.08.02 sd_051 ADetailer 対応
import warnings
warnings.simplefilter('ignore')
# タイトル
title = 'sd_test basic tools Ver 0.07'
# インポート＆初期設定
import os
import cv2
import csv
import PySimpleGUI as sg
import tkinter as tk
from PIL import Image, ImageTk
import my_logging
import my_csv
import my_thumbnail
import sd_tools as sdt
# 定数定義
DEF_THEME = 'GrayGrayGray'
KEY_SEED_INPUT = '-Seed_input-'
SKEY_RESULT_PATH = '-result_path-'
SKEY_RESULT_FILE = '-result_file-'
SKEY_DEF_OUTPATH = '-default_image-'
# csv save
KEY_PROS_SEL = '--Proscess--'
KEY_OUTPATH = '-Output-'
KEY_SEED = '-Seed-'
KEY_PROMPT_JP = '-PromptJP-'
KEY_PROMPT = '-Prompt-'
KEY_INPUTPATH = '-Input-'
KEY_MAXSIZE = '-MaxSize-'
KEY_STEP = '-Step-'
KEY_SCALE = '-Scale-'
KEY_STRENGTH = '-strength-'
KEY_MODEL_DIR = '-model_dir-'
KEY_MODEL = '-Model-'
KEY_CTRL_IMGPATH = '--ctrl_image_path--'
KEY_CTRL_DIR = '-ctrl_model_dir-'
KEY_CTRL_MODEL = '-ctrl_model-'
KEY_WIDTH = '--Image_width--'
KEY_HEIGHT = '--Image_height--'
KEY_IMG_SCALE = '--Image_scale--'
KEY_CC_SCALE = '--Control_scale--'
KEY_DEVICE = '-Device-'
KEY_TIME = '-Time-'
KEY_LOOP = '-Loop-'
KEY_NEG_PROMPT_JP = '-Negative_PromptJP-'
KEY_NEG_PROMPT = '-Negative_Prompt-'
KEY_IP_IMGPATH = '-Ip_image_path-'
KEY_IP_SCALE = '-Ip_scale-'
KEY_EXTENTION = '-Extention-'
# 共通データ
param = {｝
param[KEY_PROS_SEL] = 'sd_resilts'
param[KEY_OUTPATH] = './sd_results3/sd_00000_0.png'
param[KEY_PROMPT_JP] = '雪の中の場面にする'
param[KEY_PROMPT] = 'Make it a scene in the snow'
param[KEY_INPUTPATH] = 'images/sd_040_test.png'
param[KEY_MODEL_DIR] = ''
param[KEY_MODEL] = 'timbrooks/instruct-pix2pix'
param[KEY_MAXSIZE] = 0
param[KEY_SEED] = 0
param[KEY_SEED_INPUT] = 0
param[KEY_STEP] = 20
param[KEY_SCALE] = 7.0
param[KEY_STRENGTH] = 0.5
param[KEY_DEVICE] = 'cuda'
param[KEY_LOOP] = 1
param[KEY_TIME] = '00:00:09'
param[KEY_CTRL_IMGPATH] = ''
param[KEY_CTRL_DIR] = ''
param[KEY_CTRL_MODEL] = ''
param[KEY_WIDTH] = 512
param[KEY_HEIGHT] = 512
param[KEY_IMG_SCALE] = 1.5
param[KEY_CC_SCALE] = 1.0
param[KEY_NEG_PROMPT_JP] = '最悪の品質、おかしい人体構造'
param[KEY_NEG_PROMPT] = 'Worst quality, funny body structure'
param[SKEY_RESULT_PATH] = ''
param[SKEY_RESULT_FILE] = ''
param[SKEY_DEF_OUTPATH] = ''
param[KEY_IP_IMGPATH] = ''
param[KEY_IP_SCALE] = 0.5
param[KEY_EXTENTION] = ''
opt_list = [
['pros_sel','','sd_resilts'], # 0
]
# 結果を CSV ファイルに残す
def result_csv(csvfile, param, logger):
my_csv_treatment = my_csv.CSVtreatment(csvfile, 'utf_8_sig')
s = my_csv_treatment.read_csv()
if len(s) ==0:
data = []
data.append(KEY_PROS_SEL)
data.append(KEY_OUTPATH)
data.append(KEY_SEED)
data.append(KEY_PROMPT_JP)
data.append(KEY_PROMPT)
data.append(KEY_INPUTPATH)
data.append(KEY_MAXSIZE)
data.append(KEY_STEP)
data.append(KEY_SCALE)
data.append(KEY_STRENGTH)
data.append(KEY_MODEL_DIR)
data.append(KEY_MODEL)
data.append(KEY_CTRL_IMGPATH)
data.append(KEY_CTRL_DIR)
data.append(KEY_CTRL_MODEL)
data.append(KEY_WIDTH)
data.append(KEY_HEIGHT)
data.append(KEY_IMG_SCALE)
data.append(KEY_CC_SCALE)
data.append(KEY_DEVICE)
data.append(KEY_TIME)
data.append(KEY_LOOP)
data.append(KEY_NEG_PROMPT_JP)
data.append(KEY_NEG_PROMPT)
data.append(KEY_IP_IMGPATH)
data.append(KEY_IP_SCALE)
data.append(KEY_EXTENTION)
my_csv_treatment.write_csv(data)
logger.debug(data)
data = []
data.append(param[KEY_PROS_SEL])
data.append(param[KEY_OUTPATH])
data.append(str(param[KEY_SEED]))
data.append(param[KEY_PROMPT_JP])
data.append(param[KEY_PROMPT])
data.append(param[KEY_INPUTPATH])
data.append(str(param[KEY_MAXSIZE]))
data.append(str(param[KEY_STEP]))
data.append(str(param[KEY_SCALE]))
data.append(str(param[KEY_STRENGTH]))
data.append(param[KEY_MODEL_DIR])
data.append(param[KEY_MODEL])
data.append(param[KEY_CTRL_IMGPATH])
data.append(param[KEY_CTRL_DIR])
data.append(param[KEY_CTRL_MODEL])
data.append(param[KEY_WIDTH])
data.append(param[KEY_HEIGHT])
data.append(param[KEY_IMG_SCALE])
data.append(param[KEY_CC_SCALE])
data.append(param[KEY_DEVICE])
data.append(param[KEY_TIME])
data.append(param[KEY_LOOP])
data.append(param[KEY_NEG_PROMPT_JP])
data.append(param[KEY_NEG_PROMPT])
data.append(param[KEY_IP_IMGPATH])
data.append(param[KEY_IP_SCALE])
data.append(param[KEY_EXTENTION])
my_csv_treatment.append_csv(data)
logger.debug(data)
# 結果ログからパラメータを取得
def read_result_csv(csvfile, param, logger, imgfile = '0', pros_f = False):
def _get_val(dd, key):
return dd.get(key, '')
def _get_val_int(dd, key):
val = dd.get(key, '')
if val != '':
val = int(val)
return val
def _get_val_float(dd, key):
val = dd.get(key, '')
if val != '':
val = float(val)
return val
param[KEY_PROS_SEL] = sdt._get_process_name(opt_list)
bf = False
dds = {｝
dd = {｝
try:
with open(csvfile, 'r', encoding = 'utf_8_sig') as f:
reader = csv.DictReader(f)
if imgfile == '0': # 最初の行
for dd in reader:
bf = True
break
elif imgfile == '1': # 同じ処理の最後の行
for dd in reader:
if param[KEY_PROS_SEL] == dd.get(KEY_PROS_SEL, 'not found'):
dds = dd.copy()
bf = True
continue
if dds == {｝:
bf = False
else:
dd = dds.copy()
else: # 出力ファイルの行
img_path = os.path.basename(imgfile)
for dd in reader:
out_path = os.path.basename(dd[KEY_OUTPATH])
if out_path == img_path and (pros_f or param[KEY_PROS_SEL] == dd.get(KEY_PROS_SEL, 'not found')):
bf = True
break
except FileNotFoundError as e:
pass
except csv.Error as e:
logger.debug(e)
if bf:
param[KEY_PROS_SEL] = _get_val(dd, KEY_PROS_SEL)
param[KEY_OUTPATH] = _get_val(dd, KEY_OUTPATH)
param[KEY_SEED_INPUT] = _get_val_int(dd, KEY_SEED)
param[KEY_PROMPT_JP] = _get_val(dd, KEY_PROMPT_JP)
param[KEY_PROMPT] = _get_val(dd, KEY_PROMPT)
param[KEY_INPUTPATH] = _get_val(dd, KEY_INPUTPATH)
param[KEY_MAXSIZE] = _get_val_int(dd, KEY_MAXSIZE)
param[KEY_STEP] = _get_val_int(dd, KEY_STEP)
param[KEY_SCALE] = _get_val_float(dd, KEY_SCALE)
param[KEY_STRENGTH] = _get_val_float(dd, KEY_STRENGTH)
param[KEY_MODEL_DIR] = _get_val(dd, KEY_MODEL_DIR)
param[KEY_MODEL] = _get_val(dd, KEY_MODEL)
param[KEY_CTRL_IMGPATH] = _get_val(dd, KEY_CTRL_IMGPATH)
param[KEY_CTRL_DIR] = _get_val(dd, KEY_CTRL_DIR)
param[KEY_CTRL_MODEL] = _get_val(dd, KEY_CTRL_MODEL)
param[KEY_WIDTH] = _get_val_int(dd, KEY_WIDTH)
param[KEY_HEIGHT] = _get_val_int(dd, KEY_HEIGHT)
param[KEY_IMG_SCALE] = _get_val_float(dd, KEY_IMG_SCALE)
param[KEY_CC_SCALE] = _get_val_float(dd, KEY_CC_SCALE)
param[KEY_NEG_PROMPT_JP] = _get_val(dd, KEY_NEG_PROMPT_JP)
param[KEY_NEG_PROMPT] = _get_val(dd, KEY_NEG_PROMPT)
param[KEY_IP_IMGPATH] = _get_val(dd, KEY_IP_IMGPATH)
param[KEY_IP_SCALE] = _get_val_float(dd, KEY_IP_SCALE)
param[KEY_EXTENTION] = _get_val(dd, KEY_EXTENTION)
logout_data(param, logger)
elif os.path.isfile(imgfile):
param[KEY_OUTPATH] = imgfile
param[KEY_SEED_INPUT] = sdt.path2seed(imgfile) # ファイル名に含まれるシード値
logout_data(param, logger)
elif bf and dd.get(KEY_PROS_SEL, '') == '': # csvファイルのバージョンチェック
os.remove(csvfile)
return bf
# 動的パラメータの出力
def logout_data(param, logger):
logger.debug('---------------------------------------------')
logger.debug(param[KEY_OUTPATH])
logger.debug(param[KEY_SEED])
logger.debug(param[KEY_PROMPT_JP])
logger.debug(param[KEY_PROMPT])
logger.debug(param[KEY_INPUTPATH])
logger.debug(param[KEY_MAXSIZE])
logger.debug(param[KEY_STEP])
logger.debug(param[KEY_SCALE])
logger.debug(param[KEY_STRENGTH])
logger.debug(param[KEY_MODEL_DIR])
logger.debug(param[KEY_MODEL])
logger.debug(param[KEY_CTRL_IMGPATH])
logger.debug(param[KEY_CTRL_DIR])
logger.debug(param[KEY_CTRL_MODEL])
logger.debug(param[KEY_WIDTH])
logger.debug(param[KEY_HEIGHT])
logger.debug(param[KEY_IMG_SCALE])
logger.debug(param[KEY_CC_SCALE])
logger.debug(param[KEY_DEVICE])
logger.debug(param[KEY_NEG_PROMPT_JP])
logger.debug(param[KEY_NEG_PROMPT])
logger.debug(param[KEY_IP_IMGPATH])
logger.debug(param[KEY_IP_SCALE])
logger.debug(param[KEY_EXTENTION])
logger.debug('---------------------------------------------')
# 生成画選択ダイアログ
def image_dialog(param, csvfile, file_path, title='', theme=DEF_THEME, xn=10, yn=3, thumb_size=128, gap=4, file_ext=my_thumbnail.IMAGE_EXT, logger=None):
pros_sel = sdt._get_process_name(sdt.opt_list) # pros_sel 処理方法
image_file = ''
br = read_result_csv(csvfile, param, logger, file_path, True)
if not br:
print(sdt.RED + '生成画像がありません！' + sdt.NOCOLOR)
return image_file
KEY_IMG_SEL = '-ImgSel-'
KEY_TXTIMG = '-TextImg-'
KEY_OK = '-Ok-'
KEY_CANCEL = '-Cancel-'
KEY_PAGE = '-Page-'
KEY_PAGEUP = '-PageUp-'
KEY_PAGEDOWN = '-PageDown-'
def update_param(file_path, bok):
br = read_result_csv(csvfile, param, logger, file_path, True)
if br:
cc = cf if pros_sel == param[KEY_PROS_SEL] else '#880000'
window[KEY_PROS_SEL].update(param[KEY_PROS_SEL], text_color=cc)
window[KEY_PROMPT_JP].update(param[KEY_PROMPT_JP])
window[KEY_PROMPT].update(param[KEY_PROMPT])
window[KEY_INPUTPATH].update(param[KEY_INPUTPATH])
window[KEY_MODEL_DIR].update(param[KEY_MODEL_DIR])
window[KEY_MODEL].update(param[KEY_MODEL])
window[KEY_MAXSIZE].update(param[KEY_MAXSIZE])
window[KEY_SEED].update(param[KEY_SEED_INPUT]) # シード値
window[KEY_STEP].update(param[KEY_STEP])
window[KEY_SCALE].update(param[KEY_SCALE])
window[KEY_STRENGTH].update(param[KEY_STRENGTH])
window[KEY_DEVICE].update(param[KEY_DEVICE])
window[KEY_TIME].update(param[KEY_TIME])
window[KEY_CTRL_IMGPATH].update(param[KEY_CTRL_IMGPATH])
window[KEY_CTRL_DIR].update(param[KEY_CTRL_DIR])
window[KEY_CTRL_MODEL].update(param[KEY_CTRL_MODEL])
window[KEY_WIDTH].update(param[KEY_WIDTH])
window[KEY_HEIGHT].update(param[KEY_HEIGHT])
window[KEY_IMG_SCALE].update(param[KEY_IMG_SCALE])
window[KEY_CC_SCALE].update(param[KEY_CC_SCALE])
window[KEY_NEG_PROMPT_JP].update(param[KEY_NEG_PROMPT_JP])
window[KEY_NEG_PROMPT].update(param[KEY_NEG_PROMPT])
window[KEY_IP_IMGPATH].update(param[KEY_IP_IMGPATH])
window[KEY_IP_SCALE].update(param[KEY_IP_SCALE])
window[KEY_EXTENTION].update(param[KEY_EXTENTION])
if bok:
window[KEY_OK].update(disabled = pros_sel != param[KEY_PROS_SEL])
# Thumbnail オブジェクト作成
Thumb = my_thumbnail.Thumbnail(xn, yn, thumb_size, gap, file_ext)
image_file = file_path
frame = Thumb.initialize(image_file, False)
image_file = Thumb.get_sel_filepath()
# ウィンドウのテーマ
sg.theme(theme)
cf = '#008800' # テキストの色
cb = 'LightSteelBlue1' # 背景の色
canvas = sg.Image(size = Thumb.get_canvas_size(), key='CANVAS')
# ウィンドウのレイアウト
col_top = [
[sg.Text(image_file, background_color='White', size=(32, 1), key = KEY_IMG_SEL), sg.Text('', size=(32, 1), key = KEY_TXTIMG)],
[canvas],
]
col_btn = [
[
sg.Text("Page: 1/1", size=(12, 1), key=KEY_PAGE),
sg.Button('▼', size=(2, 1), key=KEY_PAGEUP),
sg.Button('▲', size=(2, 1), key=KEY_PAGEDOWN),
sg.Text("", size=(4, 1)),
sg.Button('Ok', size=(8, 1), key=KEY_OK, focus=True),
sg.Button('Cancel', size=(8, 1), key=KEY_CANCEL),
sg.Text("", size=(1, 1))
]
]
col_left = [
[sg.Text("Process", size=(14, 1)), sg.Text(param[KEY_PROS_SEL], size=(47,1), text_color=cf, background_color=cb, key=KEY_PROS_SEL)],
[sg.Text("Prompt jp", size=(14, 1)), sg.Multiline(param[KEY_PROMPT_JP], size=(52,3), text_color=cf, background_color=cb, disabled=True, key=KEY_PROMPT_JP)],
[sg.Text("Prompt", size=(14, 1)), sg.Multiline(param[KEY_PROMPT], size=(52,2), text_color=cf, background_color=cb, disabled=True, key=KEY_PROMPT)],
[sg.Text("Negative Prompt jp", size=(14, 1)), sg.Multiline(param[KEY_NEG_PROMPT_JP], size=(52,3), text_color=cf, background_color=cb, disabled=True, key=KEY_NEG_PROMPT_JP)],
[sg.Text("Negative Prompt", size=(14, 1)), sg.Multiline(param[KEY_NEG_PROMPT], size=(52,2), text_color=cf, background_color=cb, disabled=True, key=KEY_NEG_PROMPT)],
]
col_center = [
[sg.Text("Model Directory", size=(14, 1)), sg.Text(param[KEY_MODEL_DIR], size=(48,1), text_color=cf, background_color=cb, key=KEY_MODEL_DIR)],
[sg.Text("Model", size=(14, 1)), sg.Text(param[KEY_MODEL], size=(48,1), text_color=cf, background_color=cb, key=KEY_MODEL)],
[sg.Text("Input Image", size=(14, 1)), sg.Text(param[KEY_INPUTPATH], size=(48,1), text_color=cf, background_color=cb, key=KEY_INPUTPATH)],
[sg.Text("Control Image", size=(14, 1)), sg.Text(param[KEY_CTRL_IMGPATH], size=(48,1), text_color=cf, background_color=cb, key=KEY_CTRL_IMGPATH)],
[sg.Text("Control Model Dir", size=(14, 1)), sg.Text(param[KEY_CTRL_DIR], size=(48,1), text_color=cf, background_color=cb, key=KEY_CTRL_DIR)],
[sg.Text("Control Model", size=(14, 1)), sg.Text(param[KEY_CTRL_MODEL], size=(48,1), text_color=cf, background_color=cb, key=KEY_CTRL_MODEL)],
[sg.Text("Device", size=(14, 1)), sg.Text(param[KEY_DEVICE], size=(48,1), text_color=cf, background_color=cb, key=KEY_DEVICE)],
[sg.Text("Max size", size=(14, 1)), sg.Text(param[KEY_MAXSIZE], size=(48,1), text_color=cf, background_color=cb, key=KEY_MAXSIZE)],
[sg.Text("ip-adapter image", size=(14, 1)), sg.Text(param[KEY_IP_IMGPATH], size=(48,1), text_color=cf, background_color=cb, key=KEY_IP_IMGPATH)],
[sg.Text("Time", size=(14, 1)), sg.Text(param[KEY_TIME], size=(48,1), text_color=cf, background_color=cb, key=KEY_TIME)],
]
col_right = [
[sg.Text("Seed Value", size=(14, 1)), sg.Text(param[KEY_SEED_INPUT], size=(11,1), text_color=cf, background_color=cb, key=KEY_SEED)],
[sg.Text("Steps", size=(14, 1)), sg.Text(param[KEY_STEP], size=(11,1), text_color=cf, background_color=cb, key=KEY_STEP)],
[sg.Text("Guidance Scale", size=(14, 1)), sg.Text(param[KEY_SCALE], size=(11,1), text_color=cf, background_color=cb, key=KEY_SCALE)],
[sg.Text("Strength", size=(14, 1)), sg.Text(param[KEY_STRENGTH], size=(11,1), text_color=cf, background_color=cb, key=KEY_STRENGTH)],
[sg.Text("Image Width", size=(14, 1)), sg.Text(param[KEY_WIDTH], size=(11,1), text_color=cf, background_color=cb, key=KEY_WIDTH)],
[sg.Text("Image Height", size=(14, 1)), sg.Text(param[KEY_HEIGHT], size=(11,1), text_color=cf, background_color=cb, key=KEY_HEIGHT)],
[sg.Text("Image Scale", size=(14, 1)), sg.Text(param[KEY_IMG_SCALE], size=(11,1), text_color=cf, background_color=cb, key=KEY_IMG_SCALE)],
[sg.Text("Control Scale", size=(14, 1)), sg.Text(param[KEY_CC_SCALE], size=(11,1), text_color=cf, background_color=cb, key=KEY_CC_SCALE)],
[sg.Text("ip-adapter Scale", size=(14, 1)), sg.Text(param[KEY_IP_SCALE], size=(11,1), text_color=cf, background_color=cb, key=KEY_IP_SCALE)],
[sg.Text("Extentions", size=(14, 1)), sg.Text(param[KEY_EXTENTION], size=(11,1), text_color=cf, background_color=cb, key=KEY_EXTENTION)],
]
layout = [
[sg.Column(col_top, vertical_alignment='top')],
[sg.Column(col_left, vertical_alignment='top'), sg.Column(col_center, vertical_alignment='top'), sg.Column(col_right, vertical_alignment='top')],
[sg.Column(col_btn, justification='r') ],
]
# ウィンドウオブジェクトの作成
window = sg.Window(title, layout, finalize=True, return_keyboard_events=True, use_default_focus=False)
img = cv2.imencode('.png', frame)[1].tobytes()
window['CANVAS'].update(img)
# ユーザーイベントの定義
canvas.bind('<Motion>', '_motion')
canvas.bind('<ButtonPress>', '_click_on')
canvas.bind('<ButtonRelease>', '_click_off')
canvas.bind('<Double-Button>', '_double_click')
page_offset, page_max = Thumb.get_page_max()
window[KEY_PAGE].update(f'Page: {page_offset + 1｝/{page_max｝')
window[KEY_PAGEUP].update(disabled = not Thumb.check_page_up())
window[KEY_PAGEDOWN].update(disabled = not Thumb.check_page_down())
param_save = param.copy() # パラメータ push
new_make_f = False
# イベントのループ
while True:
event, values = window.read()
if new_make_f:
new_make_f = False
if event == KEY_CANCEL or event == sg.WIN_CLOSED:
param = param_save.copy() # パラメータ pop
image_file = ''
break
if event == KEY_OK:
logger.debug(f'{event｝ {image_file｝')
break
if event == KEY_PAGEUP:
logger.debug(f'{event｝')
frame = Thumb.page_up()
if frame is not None:
window[KEY_TXTIMG].update('')
img = cv2.imencode('.png', frame)[1].tobytes()
window['CANVAS'].update(img)
page_offset, page_max = Thumb.get_page_max()
window[KEY_PAGE].update(f'Page: {page_offset + 1｝/{page_max｝')
window[KEY_PAGEUP].update(disabled = not Thumb.check_page_up())
window[KEY_PAGEDOWN].update(disabled = not Thumb.check_page_down())
if event == KEY_PAGEDOWN:
logger.debug(f'{event｝')
frame = Thumb.page_down()
if frame is not None:
window[KEY_TXTIMG].update('')
img = cv2.imencode('.png', frame)[1].tobytes()
window['CANVAS'].update(img)
page_offset, page_max = Thumb.get_page_max()
window[KEY_PAGE].update(f'Page: {page_offset + 1｝/{page_max｝')
window[KEY_PAGEUP].update(disabled = not Thumb.check_page_up())
window[KEY_PAGEDOWN].update(disabled = not Thumb.check_page_down())
if event == 'CANVAS_motion':
x = canvas.user_bind_event.x
y = canvas.user_bind_event.y
filename, frame = Thumb.pixel2file(x, y)
window[KEY_TXTIMG].update(filename)
img = cv2.imencode('.png', frame)[1].tobytes()
window['CANVAS'].update(img)
update_param(filename, False)
if event == 'CANVAS_click_on':
image_file, frame = Thumb.select_file()
window[KEY_IMG_SEL].update(image_file)
img = cv2.imencode('.png', frame)[1].tobytes()
window['CANVAS'].update(img)
logger.debug(f'{event｝ {image_file｝')
update_param(filename, True)
if event == 'CANVAS_click_off':
pass
if event == 'CANVAS_double_click':
ftype = my_thumbnail.get_file_type(image_file)
if ftype== 0 or ftype == 1 or ftype == 2:
sdt.image_disp(image_file, image_file)
# ウィンドウ終了処理
window.close()
return image_file
#-----Test routine-----
if __name__ == "__main__":
# アプリケーション・ログ設定
module = os.path.basename(__file__)
module_name = os.path.splitext(module)[0]
logger = my_logging.get_module_logger_sel(module_name, 3)
def_file = 'sd_results3/sd_00001_0.png'
imgfile = image_dialog('sd_results3/result_100.csv', def_file, 'Results Image file select', my_thumbnail.DEF_THEME, 10, 3, logger = logger)
logger.info('\nFinished.\n')
※ 上記ソースコードは表示の都合上、半角コード '}' が 全角 '｝'になっていることに注意
opt_list = [
['cpu', 'store_true', 'cpu mode'],
['log', '3', 'Log level(-1/0/1/2/3/4/5) Default value is \'3\''],
:
]
・初期値が「''（空文字列）」の場合、パラメータは登録するが「基本情報の表示」で表示されない| 機能 | 戻り値 | 関数 |
| コマンド入力関連 | ||
| コマンドライン・オプションの設定 | parser | parse_args(parser, pars_list): |
| オプション・リストを変更する | bool | change_option(opt_list, key, val) |
| コマンドライン・オプションチェック | res | is_option(opt, key) |
| 基本情報の表示 | - | display_info(opt, title) |
| 画像関連 | ||
| イメージ変換 PIL → OpenCV | image | pil2cv(image) |
| pil2cv_np(image) | ||
| イメージ変換 OpenCV → PIL | image | cv2pil(image) |
| cv2pil_np(image) | ||
| イメージファイルの表示 | - | image_disp(image_path = , dispname = , maxsize = 800, wait_s = 0) |
| OpenCV イメージ 結果の保存と表示 | - | image_save(image, save_path = '', dispname = '', maxsize = 1000, wait_s = 0) |
| PIL イメージ 結果の保存と表示 | - | image_save2(image, save_path = '', dispname = '', maxsize = 1000, wait_s = 0) |
| コントロールイメージ作成 | image | make_inpaint_condition(image, image_mask) |
| その他 | ||
| モデルを調べる（SD1.5 モデルは SD1.5/フォルダ内にある前提） | bool | is_sd15(model) |
| ポーズ・ファイルか調べる | bool | is_pose(filepath) |
| フォルダ内で連番のファイル名を得る | filenale | make_filename_by_seq(dirname, filename, seq_digit = 3, ex = '') |
| 生成画像のファイル名からシード値を得る | seed | path2seed(filepath) |
| 経過時間(秒)を hh:mm:ssフォーマットに変換 | hh:mm:ss | elapsed_time_str(seconds) |
| ランダムなシード値を得る | seed | get_random_seed_value(n) |
| 日本語から英語に翻訳 | 英語文字列 | trans_jp2en(str) |
| メモリー開放 | - | device_empty_cache(device) |
| 作業フォルダ名を得る | work_path | get_work_path(logger = None) |
| ソース・マスク画像ファイル名を得る | src_path, mask_path | get_source_mask_path(image_path, logger = None) |
| ポーズ画像画像ファイル名を得る | pose_path | get_pose_path(image_path, logger = None) |
| diffusers parameter | ||
| log 出力 | - | log_debug(msg, logger) |
| log_info(msg, logger) | ||
| --device | device | _get_device(opt, logger = None) |
| --result_image_path | result_image_path | _get_result_image_path(opt, logger = None) |
| --result_path | result_path | _get_result_path(opt, logger = None) |
| --result_file | result_file | _get_result_file(opt, logger = None) |
| --prompt（日本語） | prompt（英語） | _get_prompt(opt, logger = None) |
| --neg_prompt（日本語） | neg_prompt（英語） | _get_negative_prompt(opt, logger = None) |
| --model_dir | model_dir | _get_model_dir(opt, logger = None) |
| --model_path | model_path | _get_model_path(opt, logger = None) |
| --ctrl_model_dir | ctrl_model_dir | _get_controlnet_model_dir(opt, logger = None) |
| --ctrl_model_path | ctrl_model_path | _get_controlnet_model_path(opt, logger = None) |
| --image_path | image_path | _get_source_image_path(opt, logger = None) |
| --image_path から PIL画像オブジェクトを得る | image | _get_source_image(opt, logger = None) |
| --ctrl_image_path | ctrl_image_path | _get_control_image_path(opt, logger = None) |
| --ctrl_image_path から PIL画像オブジェクトを得る | image | _get_control_image(opt, logger = None) |
| パスから画像を読んでリサイズする | image | _get_resize_image(image_path, max_size, logger) |
| --height, --width | height, width | _get_image_size(opt, logger = None) |
| --max_size | max_size | _get_max_size(opt, logger = None) |
| --seed（-1 の時は乱数生成） | seed | _get_seed_value(opt, logger = None) |
| --num_inference_steps | num_inference_steps | _get_inference_steps(opt, logger = None) |
| --guidance_scale | guidance_scale | _get_guidance_scale(opt, logger = None) |
| --image_guidance_scale | image_guidance_scale | _get_image_guidance_scale(opt, logger = None) |
| --strength | strength | _get_strength(opt, logger = None) |
| --cc_scale | cc_scale | _get_controlnet_conditioning_scale(opt, logger = None) |
# -*- coding: utf-8 -*-
##--------------------------------------------------
## sd_test basic tools Ver 0.07
##
## 2025.08.02 Masahiro Izutsu
##--------------------------------------------------
## sd_tools.py
## Ver 0.00 2025.07.17 Trial version
## Ver 0.05 2025.07.20 sd_100.py 統合版対応
## Ver 0.06 2025.07.27 sd_081 IP-Adapter 対応
## Ver 0.07 2025.08.02 sd_051 ADetailer 対応
# タイトル
title = 'sd_test basic tools Ver 0.07'
# Color Escape Code
GREEN = '\033[1;32m'
RED = '\033[1;31m'
NOCOLOR = '\033[0m'
YELLOW = '\033[1;33m'
CYAN = '\033[1;36m'
BLUE = '\033[1;34m'
# インポート＆初期設定
import os
import re
import glob
import random
import argparse
import numpy as np
import cv2
from PIL import Image
import torch
import my_imagetool
# 定数定義
IMAGES_WORK_DIR = 'images_work'
## ----- コマンド入力関連 --------------
# 初期値
def_result_image = ''
def_cpu = 'store_true'
def_log = '3'
def_model_dir = ''
def_model_path = ''
def_ctrl_model_dir = ''
def_ctrl_model_path = ''
def_image_path = ''
def_control_image_path = ''
def_max_size = 0
def_prompt = ''
def_seed = -1
def_width = 512
def_height = 512
def_step = 30
def_scale = 7.0
def_image_scale = 1.5
def_cc_scale = 1.0
def_strength = 0.5
def_neg_prompt = ' '
def_ip_image_path = ''
def_ip_scale = 0.5
def_mode = 'store_false'
def_ext = ''
# コマンドライン・オプション (argparse) 名前/初期値/ヘルプ
opt_list = [
['pros_sel','','sd_tools'], # 0
['result_image', def_result_image, 'path to output image file'], # 1
['cpu', def_cpu, 'cpu mode'], # 2
['log', def_log, 'Log level(-1/0/1/2/3/4/5) Default value is \'3\''], # 3
['model_dir', def_model_dir, 'Model directory'], # 4
['model_path', def_model_path, 'Model Path'], # 5
['ctrl_model_dir', def_ctrl_model_dir, 'ControlNet Model directory'], # 6
['ctrl_model_path', def_ctrl_model_path, 'ControlNet Model Path'], # 7
['image_path', def_image_path, 'Sourcs image file path'], # 8
['ctrl_image_path', '', 'Control image file path'], # 9
['max_size', def_max_size, 'image max size (0=source)'], # 10
['prompt', def_prompt, 'Prompt text'], # 11
['seed', def_seed, 'Seed parameter (-1 = rundom)'], # 12
['width', def_width, 'image size width'], # 13
['height', def_height, 'image size height'], # 14
['step', def_step, 'infer step'], # 15
['scale', def_scale, 'gaidanse scale'], # 16
['image_scale', def_image_scale, 'image gaidanse scale'], # 17
['cc_scale', def_cc_scale, 'controlnet conditioning scale'], # 18
['strength', def_strength, 'strength value'], # 19
['neg_prompt', def_neg_prompt, 'Negative Prompt text'], # 20
['ip_image_path', def_ip_image_path, 'IP-Adapter image filr path'], # 21
['ip_scale', def_ip_scale, 'IP-Adapter scale'], # 22
['mode', def_mode, 'aplication mode'],
['ext', def_ext, 'Extensions'],
]
# コマンドライン・オプションの設定
def parse_args(parser, pars_list):
if parser == None:
parser = argparse.ArgumentParser()
for pars in pars_list:
p = '--' + pars[0]
if pars[1] == 'store_true' or pars[1] == 'store_false':
parser.add_argument(p, dest = pars[0], action = pars[1], help = pars[2])
else:
parser.add_argument(p, default = pars[1], help = pars[2])
return parser
# オプション・リストを変更する
def change_option(opt_list, key, val):
bf = False
for ol in opt_list:
if ol[0] == key:
ol[1] = val
bf = True
return bf
def _get_process_name(opt_list):
return opt_list[0][2]
def _show_opt_list(opt_list):
for ol in opt_list:
print(ol)
# 基本情報の表示
def display_info(opt, title):
if title != '':
print('\n' + GREEN + title + ': Starting application...' + '\n' + NOCOLOR)
opt_dict = vars(opt) # NameSpace型を辞書型に変換
keys = opt_dict.keys() # key一覧取得
for key in keys:
if opt_dict[key] != '':
s = key + ' ' * 24
s0 = s[:24]
print(f' --{YELLOW｝{s0｝ : {NOCOLOR｝ {opt_dict[key]｝')
if title != '':
print(' ')
# コマンドライン・オプションチェック
def is_option(opt, key):
opt_dict = vars(opt) # NameSpace型を辞書型に変換
res = opt_dict.get(key)
if res == '': res = None
return res
## ----- 画像関連 ----------------------
# チャネル数の取得
def get_image_channel(image_path):
pil_image = Image.open(image_path)
ch = 0
if pil_image.mode == 'L' or pil_image.mode == 'P': ch = 1
elif pil_image.mode == 'RGB': ch = 3
elif pil_image.mode == 'RGBA': ch = 4
return ch
# イメージ変換 PIL → OpenCV
def pil2cv(image):
new_image = np.array(image, dtype=np.uint8)
if new_image.ndim == 2: # モノクロ
pass
elif new_image.shape[2] == 3: # カラー
new_image = cv2.cvtColor(new_image, cv2.COLOR_RGB2BGR)
elif new_image.shape[2] == 4: # 透過
new_image = cv2.cvtColor(new_image, cv2.COLOR_RGBA2BGRA)
return new_image
def pil2cv_np(image):
new_image = np.array(image, dtype=np.uint8)
if new_image.ndim == 2: # モノクロ
pass
elif new_image.shape[2] == 3: # カラー
new_image = new_image[:, :, ::-1]
elif new_image.shape[2] == 4: # 透過
new_image = new_image[:, :, [2, 1, 0, 3]]
return new_image
# イメージ変換 OpenCV → PIL
def cv2pil(image):
new_image = image.copy()
if new_image.ndim == 2: # モノクロ
pass
elif new_image.shape[2] == 3: # カラー
new_image = cv2.cvtColor(new_image, cv2.COLOR_BGR2RGB)
elif new_image.shape[2] == 4: # 透過
new_image = cv2.cvtColor(new_image, cv2.COLOR_BGRA2RGBA)
new_image = Image.fromarray(new_image)
return new_image
def cv2pil_np(image):
new_image = image.copy()
if new_image.ndim == 2: # モノクロ
pass
elif new_image.shape[2] == 3: # カラー
new_image = cv2.cvtColor(new_image, cv2.COLOR_BGR2RGB)
elif new_image.shape[2] == 4: # 透過
new_image = cv2.cvtColor(new_image, cv2.COLOR_BGRA2RGBA)
new_image = Image.fromarray(new_image)
return new_image
# イメージファイルの表示
def image_disp(image_path = '', dispname = '', maxsize = 800, wait_s = 0):
image = cv2.imread(image_path)
dispf = dispname != ''
my_imagetool.image_disp(image, winname = dispname, dispf = dispf, save_path = '', maxsize = maxsize, wait_s = wait_s)
# OpenCV イメージ 結果の保存と表示
def image_save(image, save_path = '', dispname = '', maxsize = 800, wait_s = 0):
dispf = dispname != ''
my_imagetool.image_disp(image, winname = dispname, dispf = dispf, save_path = save_path, maxsize = maxsize, wait_s = wait_s)
# PIL イメージ 結果の保存と表示
def image_save2(image, save_path = '', dispname = '', maxsize = 800, wait_s = 0):
image = pil2cv(image)
dispf = dispname != ''
my_imagetool.image_disp(image, winname = dispname, dispf = dispf, save_path = save_path, maxsize = maxsize, wait_s = wait_s)
# コントロールイメージ作成
def make_inpaint_condition(image, image_mask):
image = np.array(image.convert("RGB")).astype(np.float32) / 255.0
image_mask = np.array(image_mask.convert("L")).astype(np.float32) / 255.0
assert image.shape[0:1] == image_mask.shape[0:1], "image and image_mask must have the same image size"
image[image_mask > 0.5] = -1.0 # set as masked pixel
image = np.expand_dims(image, 0).transpose(0, 3, 1, 2)
image = torch.from_numpy(image)
return image
# 線画作成
def line_drawing_image(img):
# 画像のコントラストを調整
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = cv2.equalizeHist(gray)
# ガウシアンブラーを適用
gray_blurred = cv2.GaussianBlur(gray, (5, 5), 0)
# エッジ検出で線画を生成（反転）
edges = cv2.adaptiveThreshold(gray_blurred, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 11, 7)
edges = 255 - edges
return edges
## -------------------------------------
# モデルを調べる（SD1.5 モデルは SD1.5/フォルダ内にある前提）
# in: model モデル名
# out: bool True = SD1.5, False = SDXL
def is_sd15(model):
return ('SD1.5' in model)
# ポーズ・ファイルか調べる
def is_pose(filepath):
s = os.path.splitext(filepath)
return s[0][-5:] == '_pose'
# フォルダ内で連番のファイル名を得る（ヘッダ + 連番 で検索）
# in: filename ヘッダー名.拡張子
# seq_digit 連番桁数
# ex 追加文字列
# out: 新しいファイル名
def make_filename_by_seq(dirname, filename, seq_digit = 3, ex = ''):
filename_without_ext, ext = os.path.splitext(filename)
pattern = f"{filename_without_ext｝_([0-9]*){ext｝"
prog = re.compile(pattern)
files = glob.glob(
os.path.join(dirname, f"{filename_without_ext｝_[0-9]*{ext｝")
)
max_seq = -1
kn = len(filename_without_ext) + seq_digit + 1 # ヘッダ + 連番桁数 + 1 (_)
for f in files:
fn0, _ = os.path.splitext(os.path.basename(f))
fn1 = fn0[: min(len(fn0), kn)] + ext
m = prog.match(os.path.basename(fn1)) # ファイル名 kn まで比較
if m:
max_seq = max(max_seq, int(m.group(1)))
new_filename = f"{filename_without_ext｝_{max_seq+1:0{seq_digit｝｝_{ex｝{ext｝"
return new_filename
# 生成画像のファイル名からシード値を得る
def path2seed(filepath):
s = os.path.splitext(os.path.basename(filepath))[0]
n = s.rfind('_')
return int(s[n + 1:])
# 経過時間(秒)を hh:mm:ssフォーマットに変換
def elapsed_time_str(seconds):
seconds = int(seconds + 0.5) # 秒数を四捨五入
h = seconds // 3600 # 時の取得
m = (seconds - h * 3600) // 60 # 分の取得
s = seconds - h * 3600 - m * 60 # 秒の取得
return f"{h:02｝:{m:02｝:{s:02｝" # hh:mm:ss形式の文字列で返す
# ランダムなシード値を得る
def get_random_seed_value(n):
seed = int(n)
if seed == -1:
seed = random.randint(0, 2**32-1)
return seed
# 日本語から英語に翻訳
def trans_jp2en(str):
from translate import Translator
if len(str) != len(str.encode('utf-8')):
trans = Translator('en','ja').translate
prompt = trans(str) # 日本語→英語
else:
prompt = str
return prompt
# メモリー開放
def device_empty_cache(device):
if device == 'cuda':
torch.cuda.empty_cache()
elif device == 'mps':
torch.mps.empty_cache()
# 作業フォルダ名を得る
def get_work_path(logger = None):
work_path = os.getcwd().replace(os.sep,'/') + '/' + IMAGES_WORK_DIR
log_debug(f'work_path: {work_path｝', logger)
return work_path
# ソース・マスク画像ファイル名を得る
def get_source_mask_path(image_path, logger = None):
work_path = get_work_path()
file = work_path + '/' + os.path.basename(image_path)
s = os.path.splitext(file)
src_path = s[0] + '_src' + s[1]
mask_path = s[0] + '_mask' + s[1]
log_debug(f'src_path: {src_path｝', logger)
log_debug(f'mask_path: {mask_path｝', logger)
return src_path, mask_path
# ポーズ画像画像ファイル名を得る
def get_pose_path(image_path, logger = None):
work_path = get_work_path()
file = work_path + '/' + os.path.basename(image_path)
s = os.path.splitext(file)
pose_path = s[0] + '_pose' + s[1]
log_debug(f'pose_path: {pose_path｝', logger)
return pose_path
## ----- diffusers parameter -----------
# log 出力
def log_debug(msg, logger):
if logger is not None:
logger.debug(msg)
def log_info(msg, logger):
if logger is not None:
logger.info(msg)
# -- device --
def _get_device(opt, logger = None):
gpu_d = torch.cuda.is_available() # GPU 確認
if not opt.cpu and not gpu_d:
opt.cpu = True
device = 'cpu' if opt.cpu else 'cuda'
log_debug(f'device: {device｝', logger)
return device
# -- result_image_path --
def _get_result_image_path(opt, logger = None):
result_image_path = opt.result_image
log_debug(f'result_image_path: {result_image_path｝', logger)
return result_image_path
# -- result_path --
def _get_result_path(opt, logger = None):
result_path = os.path.dirname(opt.result_image)
log_debug(f'result_path: {result_path｝', logger)
return result_path
# -- result_file --
def _get_result_file(opt, logger = None):
result_file = os.path.basename(opt.result_image)
log_debug(f'result_file: {result_file｝', logger)
return result_file
# -- prompt --
def _get_prompt(opt, logger = None):
prompt = def_prompt if is_option(opt, 'prompt') == None else trans_jp2en(opt.prompt)
log_debug(f'prompt: {prompt｝', logger)
return prompt
# -- negative prompt --
def _get_negative_prompt(opt, logger = None):
neg_prompt = def_neg_prompt if is_option(opt, 'neg_prompt') == None else trans_jp2en(opt.neg_prompt)
log_debug(f'neg_prompt: {neg_prompt｝', logger)
return neg_prompt
# -- model_dir --
def _get_model_dir(opt, logger = None):
model_dir = def_model_dir if is_option(opt, 'model_dir') == None else opt.model_dir
log_debug(f'model_dir: {model_dir｝', logger)
return model_dir
# -- model_path --
def _get_model_path(opt, logger = None):
model_dir = _get_model_dir(opt, logger)
path = def_model_path if is_option(opt, 'model_path') == None else opt.model_path
model_path = path if model_dir == '' else model_dir + '/' + path
log_debug(f'model_path: {model_path｝', logger)
return model_path
# -- controlnet model_dir --
def _get_controlnet_model_dir(opt, logger = None):
ctrl_model_dir = def_ctrl_model_dir if is_option(opt, 'ctrl_model_dir') == None else opt.ctrl_model_dir
log_debug(f'ctrl_model_dir: {ctrl_model_dir｝', logger)
return ctrl_model_dir
# -- controlnet model_path --
def _get_controlnet_model_path(opt, logger = None):
ctrl_model_dir = _get_controlnet_model_dir(opt, logger)
path = def_ctrl_model_path if is_option(opt, 'ctrl_model_path') == None else opt.ctrl_model_path
ctrl_model_path = path if ctrl_model_dir == '' else ctrl_model_dir + '/' + path
log_debug(f'controlnet model_path: {ctrl_model_path｝', logger)
return ctrl_model_path
# -- source image path --
def _get_source_image_path(opt, logger = None):
image_path = def_image_path if is_option(opt, 'image_path') == None else opt.image_path
log_debug(f'image_path: {image_path｝', logger)
return image_path
# -- source image --
def _get_source_image(opt, logger = None):
image_path = def_image_path if is_option(opt, 'image_path') == None else opt.image_path
max_size = def_max_size if is_option(opt, 'max_size') == None else int(opt.max_size)
image = _get_resize_image(image_path, max_size, logger)
log_debug(f'image_path: {image_path｝', logger)
return image
# -- control image path --
def _get_control_image_path(opt, logger = None):
ctrl_image_path = def_control_image_path if is_option(opt, 'ctrl_image_path') == None else opt.ctrl_image_path
log_debug(f'ctrl_image_path: {ctrl_image_path｝', logger)
return ctrl_image_path
# -- control source image --
def _get_control_image(opt, logger = None):
ctrl_image_path = def_ctrl_image_path if is_option(opt, 'ctrl_image_path') == None else opt.ctrl_image_path
max_size = def_max_size if is_option(opt, 'max_size') == None else int(opt.max_size)
image = _get_resize_image(ctrl_image_path, max_size, logger)
log_debug(f'ctrl_image_path: {ctrl_image_path｝', logger)
return image
# -- resize image --
def _get_resize_image(image_path, max_size, logger = None):
image = Image.open(image_path)
w, h = image.size
bf, h, w = my_imagetool.check_size(h, w, maxsize = max_size)
if bf:
image = image.resize((w, h), resample=Image.BICUBIC)
log_debug(f'image size: width = {w｝, height = {h｝', logger)
return image
# -- height, width --
def _get_image_size(opt, logger = None):
width = def_width if is_option(opt, 'width') == None else int(opt.width)
height = def_height if is_option(opt, 'height') == None else int(opt.height)
log_debug(f'width: {width｝, height: {height｝', logger)
return height, width
# -- max_size --
def _get_max_size(opt, logger = None):
max_size = def_max_size if is_option(opt, 'max_size') == None else int(opt.max_size)
log_debug(f'max_size: {max_size｝', logger)
return max_size
# -- seed --
def _get_seed_value(opt, logger = None):
seed = def_seed if is_option(opt, 'seed') == None else get_random_seed_value(opt.seed)
log_debug(f'seed: {seed｝', logger)
return seed
# -- num_inference_steps --
def _get_inference_steps(opt, logger = None):
num_inference_steps = def_step if is_option(opt, 'step') == None else int(opt.step)
log_debug(f'step: {num_inference_steps｝', logger)
return num_inference_steps
# -- guidance_scale --
def _get_guidance_scale(opt, logger = None):
guidance_scale = def_scale if is_option(opt, 'scale') == None else float(opt.scale)
log_debug(f'scale: {guidance_scale｝', logger)
return guidance_scale
# -- image guidance_scale --
def _get_image_guidance_scale(opt, logger = None):
image_guidance_scale = def_image_scale if is_option(opt, 'image_scale') == None else float(opt.image_scale)
log_debug(f'image guidance scale: {image_guidance_scale｝', logger)
return image_guidance_scale
# -- strength --
def _get_strength(opt, logger = None):
strength = def_strength if is_option(opt, 'strength') == None else float(opt.strength)
log_debug(f'strength: {strength｝', logger)
return strength
# -- controlnet conditioning scale --
def _get_controlnet_conditioning_scale(opt, logger = None):
cc_scale = def_cc_scale if is_option(opt, 'cc_scale') == None else float(opt.cc_scale)
log_debug(f'controlnet conditioning scale: {cc_scale｝', logger)
return cc_scale
## ----- diffusers parameter(option) ---
# -- ip-adapter image path --
def _get_ip_image_path(opt, logger = None):
ip_image_path = def_ip_image_path if is_option(opt, 'ip_image_path') == None else opt.ip_image_path
log_debug(f'ip_image_path: {ip_image_path｝', logger)
return ip_image_path
# -- ip source image --
def _get_ip_image(opt, logger = None):
ip_image_path = def_ip_image_path if is_option(opt, 'ip_image_path') == None else opt.ip_image_path
if os.path.isfile(ip_image_path):
max_size = def_max_size if is_option(opt, 'max_size') == None else int(opt.max_size)
image = _get_resize_image(ip_image_path, max_size, logger)
log_debug(f'ip_image_path: {ip_image_path｝', logger)
else:
image = None
return image
# -- guidance_scale --
def _get_ip_scale(opt, logger = None):
ip_scale = def_ip_scale if is_option(opt, 'ip_scale') == None else float(opt.ip_scale)
log_debug(f'ip adaoter scale: {ip_scale｝', logger)
return ip_scale
## -------------------------------------
#-----Test routine-----
if __name__ == "__main__":
source_path = './images/kamo.jpg'
source_path = './images/sd_040_test.png'
opt_list = [
['result_image', './sd_results/sd.png', 'path to output image file'],
['cpu', 'store_true', 'cpu mode'],
['log', '3', 'Log level(-1/0/1/2/3/4/5) Default value is \'3\''],
['model_dir', '/StabilityMatrix/Data/Models/StableDiffusion', 'Model directory'],
['model_path', 'SD1.5/v1-5-pruned-emaonly.safetensors', 'Model Path'],
['prompt', '満開の欄', 'Prompt text'],
['seed', -1, 'Seed parameter (-1 = rundom)'],
['width', 512, 'image size width'],
['height', 512, 'image size height'],
['step', 30, 'infer step'],
['scale', 7.0, 'gaidanse scale'],
]
parser = parse_args(None, opt_list)
opt = parser.parse_args()
display_info(opt, title)
#------------
print('*** 画像表示 test ***')
image_disp(source_path, source_path)
print('*** 線画作成 test ***')
img = cv2.imread(source_path)
img2 = line_drawing_image(img)
image_save(img2, 'test1.png', dispname = title)
'''
# OpenCV 保存と表示
img = cv2.imread(source_path)
image_save(img, 'test1.png', dispname = title)
# PIL 保存と表示
img = Image.open(source_path)
image_save2(img, 'test2.png', dispname = title)
'''
#------------
print('*** diffusers parameter test ***')
print(f'device : {_get_device(opt)｝')
#------------
※ 上記ソースコードは表示の都合上、半角コード '}' が 全角 '｝'になっていることに注意
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