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gui_main.py
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gui_main.py
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import json
import logging
from pathlib import Path
from enum import Enum
from copy import deepcopy
import flet as ft
from sd_batch_runner.generate import get_controlnet_list,get_checkpoint_list,get_latent_upscale_mode_list,get_sampler_list,get_scheduler_list,get_sam_model_list,async_generate,cancel_generate
from sd_batch_runner.lora import update_lora_command,LoraType, lora_clear_cache
from sd_batch_runner.util import get_time_str, get_image_file_list
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
formatter = logging.Formatter("%(asctime)s %(name)s:%(lineno)s %(funcName)s [%(levelname)s]: %(message)s")
handler = logging.StreamHandler()
handler.setFormatter(formatter)
logger.addHandler(handler)
def validate_image_rule(image_rule):
if type(image_rule) == int:
return ("generation_result", image_rule)
elif type(image_rule) == str:
image_path = Path(image_rule)
if image_path.is_file():
return ("image_file", image_rule)
elif image_path.is_dir():
return ("image_directory", [image_rule, "random" , "@random"])
else:
return ("image_file", image_rule)
#raise ValueError(f"unknown rule {image_rule=}")
elif type(image_rule) == list:
image_path = Path(image_rule[0])
#if image_path.is_file() and image_path.suffix in (".mp4", ".MP4"):
if image_path.suffix in (".mp4", ".MP4"):
if type(image_rule[1]) in (int, float):
return ("movie_file", image_rule)
else:
raise ValueError(f"unknown rule {image_rule[1]=} must be int or float")
#elif image_path.is_dir():
else:
sort_rule = "random"
rule = "@random"
if len(image_rule) == 3:
sort_rule = image_rule[1]
rule = image_rule[2]
elif len(image_rule) == 2:
rule = image_rule[1]
return ("image_directory", [image_rule[0], sort_rule , rule])
#else:
# raise ValueError(f"unknown rule {image_rule=}")
else:
raise ValueError(f"unknown rule {image_rule=}")
def validate_focus_rule(image_rule):
focus_target = ""
focus_scale = 1.0
if type(image_rule) == list:
if type(image_rule[0]) == list:
focus_target = image_rule[1]
focus_scale = image_rule[2]
image_rule = image_rule[0]
if len(image_rule) == 1:
image_rule = image_rule[0]
return image_rule, focus_target, focus_scale
def get_controlnet_type_list():
json_path = Path("controlnet.json")
info = {}
if json_path.is_file():
with open(json_path, "r", encoding="utf-8") as f:
info = json.load(f)
else:
logger.info(f"{json_path} not found")
return list(info.keys())
def get_lora_dir_env_list():
json_path = Path("lora_dir.json")
info = {}
if json_path.is_file():
with open(json_path, "r", encoding="utf-8") as f:
info = json.load(f)
else:
logger.info(f"{json_path} not found")
return list(info.keys())
def get_preset_tags_list():
json_path = Path("preset_tags.json")
info = {}
if json_path.is_file():
with open(json_path, "r", encoding="utf-8") as f:
info = json.load(f)
else:
logger.info(f"{json_path} not found")
return list(info.keys())
def str_to_bool(val):
val = val.lower()
if val in ('y', 'yes', 't', 'true', 'on', '1'):
return True
elif val in ('n', 'no', 'f', 'false', 'off', '0'):
return False
else:
raise ValueError("invalid truth value %r" % (val,))
def str_to_token(val):
return val.split(',')
def create_picker_control(page, info_text, picker_type, on_pick_ok):
# "dir", "png", "mp4", "txt"
def on_click(e: ft.ControlEvent):
def on_pick(e: ft.FilePickerResultEvent):
if picker_type == "dir":
if e.path:
on_pick_ok(Path(e.path).as_posix())
else:
if e.files:
on_pick_ok(Path(e.files[0].path).as_posix())
page.overlay.remove(pick_files_dialog)
page.update()
pick_files_dialog = ft.FilePicker(on_result=on_pick)
page.overlay.append(pick_files_dialog)
page.update()
if picker_type == "dir":
pick_files_dialog.get_directory_path( f"Select Directory ({info_text})" )
else:
if picker_type == "png":
dialog_title=f"Select Png File ({info_text})"
allowed_extensions = ["png","PNG"]
elif picker_type == "mp4":
dialog_title=f"Select Mp4 File ({info_text})"
allowed_extensions = ["mp4","MP4"]
elif picker_type == "txt":
dialog_title=f"Select Text File ({info_text})"
allowed_extensions = ["txt","TXT"]
else:
raise ValueError(f"unknown picker type {picker_type}")
pick_files_dialog.pick_files(
dialog_title=dialog_title,
allow_multiple=False,
file_type=ft.FilePickerFileType.CUSTOM,
allowed_extensions = allowed_extensions
)
btn = ft.IconButton(icon=ft.Icons.FOLDER, on_click=on_click)
return btn
def open_file(filepath):
import os, sys, subprocess
if sys.platform == "win32":
os.startfile(filepath)
else:
opener = "open" if sys.platform == "darwin" else "xdg-open"
subprocess.call([opener, filepath])
def read_text_as_list(filepath):
result = []
p = Path(filepath)
with p.open('r') as f :
while True:
line = f.readline()
if not line:
break
line = line.strip()
result.append(line)
return result
def create_seq_json_from_tags(tag_list, tag_src_img_list, opt, debug):
from sd_batch_runner.util import config_clear_cache,config_get_default_generation_setting
config_clear_cache()
lora_clear_cache()
gen = config_get_default_generation_setting(True)
seq = {
"common" : {
"prompt":{
"character_lora" : "",
"character_lora2" : "",
"style_lora" : "",
"style_lora2" : "",
"pose_lora" : "",
"pose_lora2" : "",
"item_lora" : "",
"item_lora2" : "",
"header" : "",
"footer" : "",
},
"seed" : "@random_per_seq",
"generation_setting" : {
"width" : gen["width"],
"height" : gen["height"],
"negative_prompt" : gen["negative_prompt"],
},
},
"seq" : [
{
"type" : "txt2img"
}
]
}
def create_seq():
new_seq = []
for tag, img_path in zip(tag_list,tag_src_img_list):
item = {
"type" : opt["type"],
"prompt" : {
"footer" : tag
},
"output_scale" : opt["output_scale"],
"output_filename" : Path(img_path).with_suffix(".png").name
}
if opt["type"] == "img2img":
item["input_image"] = [ [img_path], "", 1.0 ]
controlnet = []
for c in opt["controlnet"]:
#logger.info(c)
if c["enable"]:
controlnet.append({
"type" : c["type"],
"image" : [ [img_path], "", 1.0 ],
"cn_target" : "",
"weight" : c["weight"],
"guidance_start" : c["guidance_start"],
"guidance_end" : c["guidance_end"]
})
if controlnet:
item["controlnet"] = controlnet
from PIL import Image
img = Image.open(img_path)
w = (gen["width"] + gen["height"]) * img.size[0] / (img.size[0] + img.size[1])
h = (gen["width"] + gen["height"]) * img.size[1] / (img.size[0] + img.size[1])
item["generation_setting"] = {
"width" : int(w//8*8),
"height" : int(h//8*8),
}
if opt["type"] == "img2img":
item["generation_setting"]["denoising_strength"] = opt["denoising_strength"]
new_seq.append(item)
return new_seq
def create_debug_seq():
new_seq = []
#d_tag_list = [tag_list[0], tag_list[len(tag_list)//2]]
#d_tag_src_img_list = [tag_src_img_list[0], tag_src_img_list[len(tag_list)//2]]
d_tag_list = [tag_list[0]]
d_tag_src_img_list = [tag_src_img_list[0]]
count = 0
for tag, img_path in zip(d_tag_list, d_tag_src_img_list):
item = {
"type" : "txt2img",
"prompt" : {
"footer" : tag
},
"output_scale" : opt["output_scale"],
"input_image" : [ [img_path], "", 1.0 ],
}
from PIL import Image
img = Image.open(img_path)
w = (gen["width"] + gen["height"]) * img.size[0] / (img.size[0] + img.size[1])
h = (gen["width"] + gen["height"]) * img.size[1] / (img.size[0] + img.size[1])
item["generation_setting"] = {
"width" : int(w//8*8),
"height" : int(h//8*8),
}
item["generation_setting"]["denoising_strength"] = opt["denoising_strength"]
for main_type in ["txt2img","img2img"]:
item["type"] = main_type
for c_type in ["depth","tile","line"]:
for w,s,e in [(0.25,0,0.5),(0.5,0,0.5),(1.0,0,0.5),(0.25,0,0.75),(0.5,0,0.75),(1.0,0,0.75),(0.25,0,1.0),(0.5,0,1.0),(1.0,0,1.0)]:
item["controlnet"] = [
{
"type" : c_type,
"image" : [ [img_path], "", 1.0 ],
"cn_target" : "",
"weight" : w,
"guidance_start" : s,
"guidance_end" : e
}
]
if main_type == "txt2img":
item["output_filename"] = f"{str(count).zfill(5)}_{main_type}_{c_type}_{str(int(w*100)).zfill(3)}_{str(int(s*100)).zfill(3)}_{str(int(e*100)).zfill(3)}.png"
else:
item["output_filename"] = f"{str(count).zfill(5)}_{main_type}{str(int(opt['denoising_strength']*100)).zfill(3)}_{c_type}_{str(int(w*100)).zfill(3)}_{str(int(s*100)).zfill(3)}_{str(int(e*100)).zfill(3)}.png"
new_seq.append(item.copy())
count += 1
return new_seq
if debug:
seq["seq"] = create_debug_seq()
else:
seq["seq"] = create_seq()
return json.dumps(seq, indent=4, ensure_ascii=False)
class ConfigType(str, Enum):
Controlnet_Module = "controlnet_module",
Controlnet_Model = "controlnet_model",
Controlnet_Weight = "controlnet_weight",
Controlnet_ResizeMode = "controlnet_resize_mode",
Controlnet_LowVram = "controlnet_low_vram",
Controlnet_ProcessorRes = "controlnet_processor_res",
Controlnet_Tha = "controlnet_threshold_a",
Controlnet_Thb = "controlnet_threshold_b",
Controlnet_GuidanceStart = "controlnet_guidance_start",
Controlnet_GuidanceEnd = "controlnet_guidance_end",
Controlnet_ControlMode = "controlnet_control_mode",
Controlnet_PixelPerfect = "controlnet_pixel_perfect",
Controlnet_HrOption = "controlnet_hr_option",
LoraEnv_CharacterDir = "loraenv_character_dir_path",
LoraEnv_StyleDir = "loraenv_style_dir_path",
LoraEnv_PoseDir = "loraenv_pose_dir_path",
LoraEnv_ItemDir = "loraenv_item_dir_path",
PresetTags_Prompt = "preset_tags_prompt",
PresetTags_NegPrompt = "preset_tags_negative_prompt",
PresetTags_IsFooter = "preset_tags_is_footer",
DefaultCheckPoint = "default_checkpoint",
LoraEnv = "lora_dir_env"
LoraGenerateTag_EnableCharacter = "lora_generate_tag_enable_character",
LoraGenerateTag_EnableStyle = "lora_generate_tag_enable_style",
LoraGenerateTag_EnablePose = "lora_generate_tag_enable_pose",
LoraGenerateTag_EnableItem = "lora_generate_tag_enable_item",
LoraGenerateTag_TagThCharacter = "lora_generate_tag_tag_th_character",
LoraGenerateTag_TagThStyle = "lora_generate_tag_tag_th_style",
LoraGenerateTag_TagThPose = "lora_generate_tag_tag_th_pose",
LoraGenerateTag_TagThItem = "lora_generate_tag_tag_th_item",
LoraGenerateTag_ProhibitedTagsCharacter = "lora_generate_tag_prohibited_tags_character",
LoraGenerateTag_ProhibitedTagsStyle = "lora_generate_tag_prohibited_tags_style",
LoraGenerateTag_ProhibitedTagsPose = "lora_generate_tag_prohibited_tags_pose",
LoraGenerateTag_ProhibitedTagsItem = "lora_generate_tag_prohibited_tags_item",
LoraBlockWeight_EnableLbwCharacter = "lbw_enable_lbw_character",
LoraBlockWeight_PresetCharacter = "lbw_preset_character",
LoraBlockWeight_SssCharacter = "lbw_start_stop_step_character",
LoraBlockWeight_SssValueCharacter = "lbw_start_stop_step_value_character",
LoraBlockWeight_EnableLbwCharacter2 = "lbw_enable_lbw_character2",
LoraBlockWeight_PresetCharacter2 = "lbw_preset_character2",
LoraBlockWeight_SssCharacter2 = "lbw_start_stop_step_character2",
LoraBlockWeight_SssValueCharacter2 = "lbw_start_stop_step_value_character2",
LoraBlockWeight_EnableLbwStyle = "lbw_enable_lbw_style",
LoraBlockWeight_PresetStyle = "lbw_preset_style",
LoraBlockWeight_SssStyle = "lbw_start_stop_step_style",
LoraBlockWeight_SssValueStyle = "lbw_start_stop_step_value_style",
LoraBlockWeight_EnableLbwStyle2 = "lbw_enable_lbw_style2",
LoraBlockWeight_PresetStyle2 = "lbw_preset_style2",
LoraBlockWeight_SssStyle2 = "lbw_start_stop_step_style2",
LoraBlockWeight_SssValueStyle2 = "lbw_start_stop_step_value_style2",
LoraBlockWeight_EnableLbwPose = "lbw_enable_lbw_pose",
LoraBlockWeight_PresetPose = "lbw_preset_pose",
LoraBlockWeight_SssPose = "lbw_start_stop_step_pose",
LoraBlockWeight_SssValuePose = "lbw_start_stop_step_value_pose",
LoraBlockWeight_EnableLbwPose2 = "lbw_enable_lbw_pose2",
LoraBlockWeight_PresetPose2 = "lbw_preset_pose2",
LoraBlockWeight_SssPose2 = "lbw_start_stop_step_pose2",
LoraBlockWeight_SssValuePose2 = "lbw_start_stop_step_value_pose2",
LoraBlockWeight_EnableLbwItem = "lbw_enable_lbw_item",
LoraBlockWeight_PresetItem = "lbw_preset_item",
LoraBlockWeight_SssItem = "lbw_start_stop_step_item",
LoraBlockWeight_SssValueItem = "lbw_start_stop_step_value_item",
LoraBlockWeight_EnableLbwItem2 = "lbw_enable_lbw_item2",
LoraBlockWeight_PresetItem2 = "lbw_preset_item2",
LoraBlockWeight_SssItem2 = "lbw_start_stop_step_item2",
LoraBlockWeight_SssValueItem2 = "lbw_start_stop_step_value_item2",
GenTxt2Img_EnableHr = "txt2img_enable_hr",
GenTxt2Img_DenoisingStr = "txt2img_denoising_strength",
GenTxt2Img_1pWidth = "txt2img_firstphase_width",
GenTxt2Img_1pHeight = "txt2img_firstphase_height",
GenTxt2Img_HrScale = "txt2img_hr_scale",
GenTxt2Img_HrUpscaler = "txt2img_hr_upscaler",
GenTxt2Img_Hr2pSteps = "txt2img_hr_second_pass_steps",
GenTxt2Img_HrResizeX = "txt2img_hr_resize_x",
GenTxt2Img_HrResizeY = "txt2img_hr_resize_y",
GenImg2Img_ResizeMode = "img2img_resize_mode",
GenImg2Img_DenoisingStr = "img2img_denoising_strength",
GenImg2Img_ImgCfgScale = "img2img_image_cfg_scale",
GenImg2Img_MaskBlur = "img2img_mask_blur",
GenImg2Img_InpaintingFill = "img2img_inpainting_fill",
GenImg2Img_InpaintFullRes = "img2img_inpaint_full_res",
GenImg2Img_InpaintFullResPadding = "img2img_inpaint_full_res_padding",
GenImg2Img_InpaintingMaskInvert = "img2img_inpainting_mask_invert",
GenImg2Img_InitialNoiseMul = "img2img_initial_noise_multiplier",
CommonGen_SamplerName = "common_sampler_name",
CommonGen_Scheduler = "common_scheduler",
CommonGen_Steps = "common_steps",
CommonGen_CfgScale = "common_cfg_scale",
CommonGen_Width = "common_width",
CommonGen_Height = "common_height",
CommonGen_RestoreFaces = "common_restore_faces",
CommonGen_Tiling = "common_tiling",
CommonGen_DnSaveSamples = "common_do_not_save_samples",
CommonGen_DnSaveGrid = "common_do_not_save_grid",
CommonGen_NegPrompt = "common_negative_prompt",
CommonGen_Eta = "common_eta",
CommonGen_SendImages = "common_send_images",
CommonGen_SaveImages = "common_save_images",
PromptGen_ModelName = "promptgen_model_name",
PromptGen_Text = "promptgen_text",
PromptGen_MinLength = "promptgen_min_length",
PromptGen_MaxLength = "promptgen_max_length",
PromptGen_NumBeams = "promptgen_num_beams",
PromptGen_Temp = "promptgen_temperature",
PromptGen_RepPenalty = "promptgen_repetition_penalty",
PromptGen_LengthPref = "promptgen_length_preference",
PromptGen_SamplingMode = "promptgen_sampling_mode",
PromptGen_TopK = "promptgen_top_k",
PromptGen_TopP = "promptgen_top_p",
OWGen_OWSteps = "owgen_overwrite_steps",
OWGen_OWSamplerName = "owgen_overwrite_sampler_name",
OWGen_OWScheduler = "owgen_overwrite_scheduler",
OWGen_OWCfgScale = "owgen_overwrite_cfg_scale",
OWGen_OWWidth = "owgen_overwrite_width",
OWGen_OWHeight = "owgen_overwrite_height",
OWGen_OWPrompt = "owgen_overwrite_prompt",
OWGen_OWNegPrompt = "owgen_overwrite_negative_prompt",
OWGen_OWSeed = "owgen_overwrite_seed",
OWGen_AddLora = "owgen_add_lora",
OWGen_AddPromptGen = "owgen_add_prompt_gen",
Adetailer_Model = "adetailer_model",
Adetailer_Prompt = "adetailer_prompt",
Adetailer_NegPrompt = "adetailer_negative_prompt",
Adetailer_Model2 = "adetailer_model2",
Adetailer_Prompt2 = "adetailer_prompt2",
Adetailer_NegPrompt2 = "adetailer_negative_prompt2",
Adetailer_Model3 = "adetailer_model3",
Adetailer_Prompt3 = "adetailer_prompt3",
Adetailer_NegPrompt3 = "adetailer_negative_prompt3",
Sam_SamModelName = "segment_anything_sam_model_name",
Sam_DinoModelName = "segment_anything_dino_model_name",
Input_Prompt_CharacterLora = "input_prompt_character_lora",
Input_Prompt_CharacterLora2 = "input_prompt_character_lora2",
Input_Prompt_StyleLora = "input_prompt_style_lora",
Input_Prompt_StyleLora2 = "input_prompt_style_lora2",
Input_Prompt_PoseLora = "input_prompt_pose_lora",
Input_Prompt_PoseLora2 = "input_prompt_pose_lora2",
Input_Prompt_ItemLora = "input_prompt_item_lora",
Input_Prompt_ItemLora2 = "input_prompt_item_lora2",
Input_Prompt_PresetTags = "input_prompt_preset_tags",
Input_Prompt_Header = "input_prompt_header",
Input_Prompt_Footer = "input_prompt_footer",
Input_CheckPoint = "input_checkpoint"
Input_Seed = "input_seed",
Input_OW_PngInfo = "input_overwrite_pnginfo",
Input_PromptGen_Type = "input_promptgen_type",
Input_PromptGen_IsFooter = "input_promptgen_is_footer",
Input_Seq_Type = "input_seq_type",
Input_Seq_InputImage = "input_seq_input_image",
Input_Seq_OutputScale = "input_seq_output_scale",
Input_Seq_OutputFileName = "input_seq_output_filename",
Input_Seq_ControlnetType = "input_seq_controlnet_type",
Input_Seq_ControlnetImage = "input_seq_controlnet_image",
Input_Seq_ControlnetCNTarget = "input_seq_controlnet_cn_target",
DD_OPTION_MAP = {
ConfigType.Controlnet_HrOption : ["Both","Low res only","High res only"],
ConfigType.Controlnet_ResizeMode : ["Just Resize","Crop and Resize","Resize and Fill"],
#"module" : controlnet_module_list,
#"model" : controlnet_model_list,
ConfigType.Controlnet_ControlMode : ["0","1","2"],
ConfigType.LoraBlockWeight_SssCharacter : ["none","start","stop","step"],
ConfigType.LoraBlockWeight_SssCharacter2 : ["none","start","stop","step"],
ConfigType.LoraBlockWeight_SssStyle : ["none","start","stop","step"],
ConfigType.LoraBlockWeight_SssStyle2 : ["none","start","stop","step"],
ConfigType.LoraBlockWeight_SssPose : ["none","start","stop","step"],
ConfigType.LoraBlockWeight_SssPose2 : ["none","start","stop","step"],
ConfigType.LoraBlockWeight_SssItem : ["none","start","stop","step"],
ConfigType.LoraBlockWeight_SssItem2 : ["none","start","stop","step"],
#"hr_upscaler" : latent_upscale_mode_list,
ConfigType.GenImg2Img_ResizeMode : ["0","1","2","3"],
#"sampler_name": sampler_list,
#"scheduler" : scheduler_list,
ConfigType.PromptGen_ModelName : ["AUTOMATIC/promptgen-lexart", "AUTOMATIC/promptgen-majinai-safe", "AUTOMATIC/promptgen-majinai-unsafe", "promptgen-lexart", "promptgen-majinai-safe", "promptgen-majinai-unsafe"],
ConfigType.PromptGen_SamplingMode : ["Top K","Top P"],
ConfigType.Adetailer_Model : ["none", "face_yolov8n.pt", "face_yolov8s.pt", "hand_yolov8n.pt", "person_yolov8n-seg.pt", "person_yolov8s-seg.pt", "mediapipe_face_full", "mediapipe_face_short", "mediapipe_face_mesh" ],
ConfigType.Adetailer_Model2 : ["none", "face_yolov8n.pt", "face_yolov8s.pt", "hand_yolov8n.pt", "person_yolov8n-seg.pt", "person_yolov8s-seg.pt", "mediapipe_face_full", "mediapipe_face_short", "mediapipe_face_mesh" ],
ConfigType.Adetailer_Model3 : ["none", "face_yolov8n.pt", "face_yolov8s.pt", "hand_yolov8n.pt", "person_yolov8n-seg.pt", "person_yolov8s-seg.pt", "mediapipe_face_full", "mediapipe_face_short", "mediapipe_face_mesh" ],
ConfigType.Input_Seed : ["@random_once","@random_per_seq","@random"],
ConfigType.Input_PromptGen_Type : ["once","per_seq","any_time"],
ConfigType.Input_Seq_Type : ["txt2img","img2img","copy"],
}
CONFIG_MAP = {
# ui_type, format_func, data_name
#
ConfigType.Controlnet_Module : ["dd", str, "module"],
ConfigType.Controlnet_Model : ["dd", str, "model"],
ConfigType.Controlnet_Weight : ["num", float, "weight"],
ConfigType.Controlnet_ResizeMode : ["dd", str, "resize_mode" ],
ConfigType.Controlnet_LowVram : ["bool", bool, "low_vram" ],
ConfigType.Controlnet_ProcessorRes : ["num", float, "processor_res" ],
ConfigType.Controlnet_Tha : ["num", float, "threshold_a" ],
ConfigType.Controlnet_Thb : ["num", float, "threshold_b" ],
ConfigType.Controlnet_GuidanceStart : ["num", float, "guidance_start" ],
ConfigType.Controlnet_GuidanceEnd : ["num", float, "guidance_end" ],
ConfigType.Controlnet_ControlMode : ["dd", int, "control_mode" ],
ConfigType.Controlnet_PixelPerfect : ["bool", bool, "pixel_perfect" ],
ConfigType.Controlnet_HrOption : ["dd", str, "hr_option" ],
ConfigType.LoraEnv_CharacterDir : ["dir", str, "character_dir_path"],
ConfigType.LoraEnv_StyleDir : ["dir", str, "style_dir_path"],
ConfigType.LoraEnv_PoseDir : ["dir", str, "pose_dir_path"],
ConfigType.LoraEnv_ItemDir : ["dir", str, "item_dir_path"],
ConfigType.PresetTags_Prompt : ["str", str, "prompt"],
ConfigType.PresetTags_NegPrompt : ["str", str, "negative_prompt"],
ConfigType.PresetTags_IsFooter : ["bool", bool, "is_footer"],
ConfigType.DefaultCheckPoint : ["dd", str, "default_checkpoint"],
ConfigType.LoraEnv : ["dd", str, "lora_dir_env"],
ConfigType.LoraGenerateTag_EnableCharacter : ["bool", bool, "enable_character"],
ConfigType.LoraGenerateTag_EnableStyle : ["bool", bool, "enable_style"],
ConfigType.LoraGenerateTag_EnablePose : ["bool", bool, "enable_pose"],
ConfigType.LoraGenerateTag_EnableItem : ["bool", bool, "enable_item"],
ConfigType.LoraGenerateTag_TagThCharacter : ["num", float, "tag_th_character"],
ConfigType.LoraGenerateTag_TagThStyle : ["num", float, "tag_th_style"],
ConfigType.LoraGenerateTag_TagThPose : ["num", float, "tag_th_pose"],
ConfigType.LoraGenerateTag_TagThItem : ["num", float, "tag_th_item"],
ConfigType.LoraGenerateTag_ProhibitedTagsCharacter : ["list", str_to_token, "prohibited_tags_character"],
ConfigType.LoraGenerateTag_ProhibitedTagsStyle : ["list", str_to_token, "prohibited_tags_style"],
ConfigType.LoraGenerateTag_ProhibitedTagsPose : ["list", str_to_token, "prohibited_tags_pose"],
ConfigType.LoraGenerateTag_ProhibitedTagsItem : ["list", str_to_token, "prohibited_tags_item"],
ConfigType.LoraBlockWeight_EnableLbwCharacter : ["bool", bool, "character_enable_lbw"],
ConfigType.LoraBlockWeight_PresetCharacter : ["str", str, "character_preset"],
ConfigType.LoraBlockWeight_SssCharacter : ["dd", str, "character_start_stop_step"],
ConfigType.LoraBlockWeight_SssValueCharacter : ["num", int, "character_start_stop_step_value"],
ConfigType.LoraBlockWeight_EnableLbwCharacter2 : ["bool", bool, "character2_enable_lbw"],
ConfigType.LoraBlockWeight_PresetCharacter2 : ["str", str, "character2_preset"],
ConfigType.LoraBlockWeight_SssCharacter2 : ["dd", str, "character2_start_stop_step"],
ConfigType.LoraBlockWeight_SssValueCharacter2 : ["num", int, "character2_start_stop_step_value"],
ConfigType.LoraBlockWeight_EnableLbwStyle : ["bool", bool, "style_enable_lbw"],
ConfigType.LoraBlockWeight_PresetStyle : ["str", str, "style_preset"],
ConfigType.LoraBlockWeight_SssStyle : ["dd", str, "style_start_stop_step"],
ConfigType.LoraBlockWeight_SssValueStyle : ["num", int, "style_start_stop_step_value"],
ConfigType.LoraBlockWeight_EnableLbwStyle2 : ["bool", bool, "style2_enable_lbw"],
ConfigType.LoraBlockWeight_PresetStyle2 : ["str", str, "style2_preset"],
ConfigType.LoraBlockWeight_SssStyle2 : ["dd", str, "style2_start_stop_step"],
ConfigType.LoraBlockWeight_SssValueStyle2 : ["num", int, "style2_start_stop_step_value"],
ConfigType.LoraBlockWeight_EnableLbwPose : ["bool", bool, "pose_enable_lbw"],
ConfigType.LoraBlockWeight_PresetPose : ["str", str, "pose_preset"],
ConfigType.LoraBlockWeight_SssPose : ["dd", str, "pose_start_stop_step"],
ConfigType.LoraBlockWeight_SssValuePose : ["num", int, "pose_start_stop_step_value"],
ConfigType.LoraBlockWeight_EnableLbwPose2 : ["bool", bool, "pose2_enable_lbw"],
ConfigType.LoraBlockWeight_PresetPose2 : ["str", str, "pose2_preset"],
ConfigType.LoraBlockWeight_SssPose2 : ["dd", str, "pose2_start_stop_step"],
ConfigType.LoraBlockWeight_SssValuePose2 : ["num", int, "pose2_start_stop_step_value"],
ConfigType.LoraBlockWeight_EnableLbwItem : ["bool", bool, "item_enable_lbw"],
ConfigType.LoraBlockWeight_PresetItem : ["str", str, "item_preset"],
ConfigType.LoraBlockWeight_SssItem : ["dd", str, "item_start_stop_step"],
ConfigType.LoraBlockWeight_SssValueItem : ["num", int, "item_start_stop_step_value"],
ConfigType.LoraBlockWeight_EnableLbwItem2 : ["bool", bool, "item2_enable_lbw"],
ConfigType.LoraBlockWeight_PresetItem2 : ["str", str, "item2_preset"],
ConfigType.LoraBlockWeight_SssItem2 : ["dd", str, "item2_start_stop_step"],
ConfigType.LoraBlockWeight_SssValueItem2 : ["num", int, "item2_start_stop_step_value"],
ConfigType.GenTxt2Img_EnableHr : ["bool", bool, "enable_hr"],
ConfigType.GenTxt2Img_DenoisingStr : ["num", float, "denoising_strength"],
ConfigType.GenTxt2Img_1pWidth : ["num", int, "firstphase_width"],
ConfigType.GenTxt2Img_1pHeight : ["num", int, "firstphase_height"],
ConfigType.GenTxt2Img_HrScale : ["num", float, "hr_scale"],
ConfigType.GenTxt2Img_HrUpscaler : ["dd", str, "hr_upscaler"],
ConfigType.GenTxt2Img_Hr2pSteps : ["num", int, "hr_second_pass_steps"],
ConfigType.GenTxt2Img_HrResizeX : ["num", int, "hr_resize_x"],
ConfigType.GenTxt2Img_HrResizeY : ["num", int, "hr_resize_y"],
ConfigType.GenImg2Img_ResizeMode : ["dd", int, "resize_mode"],
ConfigType.GenImg2Img_DenoisingStr : ["num", float, "denoising_strength"],
ConfigType.GenImg2Img_ImgCfgScale : ["num", float, "image_cfg_scale"],
ConfigType.GenImg2Img_MaskBlur : ["num", int, "mask_blur"],
ConfigType.GenImg2Img_InpaintingFill : ["num", int, "inpainting_fill"],
ConfigType.GenImg2Img_InpaintFullRes : ["bool", bool, "inpaint_full_res"],
ConfigType.GenImg2Img_InpaintFullResPadding : ["num", int, "inpaint_full_res_padding"],
ConfigType.GenImg2Img_InpaintingMaskInvert : ["num", int, "inpainting_mask_invert"],
ConfigType.GenImg2Img_InitialNoiseMul : ["num", float, "initial_noise_multiplier"],
ConfigType.CommonGen_SamplerName : ["dd", str, "sampler_name"],
ConfigType.CommonGen_Scheduler : ["dd", str, "scheduler"],
ConfigType.CommonGen_Steps : ["num", int, "steps"],
ConfigType.CommonGen_CfgScale : ["num", float, "cfg_scale"],
ConfigType.CommonGen_Width : ["num", int, "width"],
ConfigType.CommonGen_Height : ["num", int, "height"],
ConfigType.CommonGen_RestoreFaces : ["bool", bool, "restore_faces"],
ConfigType.CommonGen_Tiling : ["bool", bool, "tiling"],
ConfigType.CommonGen_DnSaveSamples : ["bool", bool, "do_not_save_samples"],
ConfigType.CommonGen_DnSaveGrid : ["bool", bool, "do_not_save_grid"],
ConfigType.CommonGen_NegPrompt : ["str", str, "negative_prompt"],
ConfigType.CommonGen_Eta : ["num", float, "eta"],
ConfigType.CommonGen_SendImages : ["bool", bool, "send_images"],
ConfigType.CommonGen_SaveImages : ["bool", bool, "save_images"],
ConfigType.PromptGen_ModelName : ["dd", str, "model_name"],
ConfigType.PromptGen_Text : ["str", str, "text"],
ConfigType.PromptGen_MinLength : ["num", int, "min_length"],
ConfigType.PromptGen_MaxLength : ["num", int, "max_length"],
ConfigType.PromptGen_NumBeams : ["num", int, "num_beams"],
ConfigType.PromptGen_Temp : ["num", float, "temperature"],
ConfigType.PromptGen_RepPenalty : ["num", float, "repetition_penalty"],
ConfigType.PromptGen_LengthPref : ["num", float, "length_preference"],
ConfigType.PromptGen_SamplingMode : ["dd", str, "sampling_mode"],
ConfigType.PromptGen_TopK : ["num", int, "top_k"],
ConfigType.PromptGen_TopP : ["num", float, "top_p"],
ConfigType.OWGen_OWSteps : ["bool", bool, "overwrite_steps"],
ConfigType.OWGen_OWSamplerName : ["bool", bool, "overwrite_sampler_name"],
ConfigType.OWGen_OWScheduler : ["bool", bool, "overwrite_scheduler"],
ConfigType.OWGen_OWCfgScale : ["bool", bool, "overwrite_cfg_scale"],
ConfigType.OWGen_OWWidth : ["bool", bool, "overwrite_width"],
ConfigType.OWGen_OWHeight : ["bool", bool, "overwrite_height"],
ConfigType.OWGen_OWPrompt : ["bool", bool, "overwrite_prompt"],
ConfigType.OWGen_OWNegPrompt : ["bool", bool, "overwrite_negative_prompt"],
ConfigType.OWGen_OWSeed : ["bool", bool, "overwrite_seed"],
ConfigType.OWGen_AddLora : ["bool", bool, "add_lora"],
ConfigType.OWGen_AddPromptGen : ["bool", bool, "add_prompt_gen"],
ConfigType.Adetailer_Model : ["dd", str, "1_ad_model"],
ConfigType.Adetailer_Prompt : ["str", str, "1_ad_prompt"],
ConfigType.Adetailer_NegPrompt : ["str", str, "1_ad_negative_prompt"],
ConfigType.Adetailer_Model2 : ["dd", str, "2_ad_model"],
ConfigType.Adetailer_Prompt2 : ["str", str, "2_ad_prompt"],
ConfigType.Adetailer_NegPrompt2 : ["str", str, "2_ad_negative_prompt"],
ConfigType.Adetailer_Model3 : ["dd", str, "3_ad_model"],
ConfigType.Adetailer_Prompt3 : ["str", str, "3_ad_prompt"],
ConfigType.Adetailer_NegPrompt3 : ["str", str, "3_ad_negative_prompt"],
ConfigType.Sam_SamModelName : ["dd", str, "sam_model_name"],
ConfigType.Sam_DinoModelName : ["str", str, "dino_model_name"],
ConfigType.Input_Prompt_CharacterLora : ["lora", str, "character_lora"],
ConfigType.Input_Prompt_CharacterLora2 : ["lora", str, "character_lora2"],
ConfigType.Input_Prompt_StyleLora : ["lora", str, "style_lora"],
ConfigType.Input_Prompt_StyleLora2 : ["lora", str, "style_lora2"],
ConfigType.Input_Prompt_PoseLora : ["lora", str, "pose_lora"],
ConfigType.Input_Prompt_PoseLora2 : ["lora", str, "pose_lora2"],
ConfigType.Input_Prompt_ItemLora : ["lora", str, "item_lora"],
ConfigType.Input_Prompt_ItemLora2 : ["lora", str, "item_lora2"],
ConfigType.Input_Prompt_PresetTags : ["tags", str, "preset_tags"],
ConfigType.Input_Prompt_Header : ["large_str", str, "header"],
ConfigType.Input_Prompt_Footer : ["large_str", str, "footer"],
ConfigType.Input_CheckPoint : ["dd", str, "checkpoint"],
ConfigType.Input_Seed : ["dd", str, "seed"],
ConfigType.Input_OW_PngInfo : ["image2", str, "png_info"],
ConfigType.Input_PromptGen_Type : ["dd", str, "type"],
ConfigType.Input_PromptGen_IsFooter : ["bool", bool, "is_footer"],
ConfigType.Input_Seq_Type : ["dd", str, "type"],
ConfigType.Input_Seq_InputImage : ["image", str, "input_image"],
ConfigType.Input_Seq_OutputScale : ["num", float, "output_scale"],
ConfigType.Input_Seq_OutputFileName : ["str", str, "output_filename"],
ConfigType.Input_Seq_ControlnetType : ["dd", str, "type"],
ConfigType.Input_Seq_ControlnetImage : ["image", str, "image"],
ConfigType.Input_Seq_ControlnetCNTarget : ["cn_target", str, "cn_target"],
}
class ConfigItem:
def __init__(self, name:str, val, ui_type, options, format_func, page=None):
self.name = name
self.org_val = val
self.val = val
self.ui_type = ui_type
self.options = options
self.format_func = format_func
self.page : ft.Page = page
def _create_picker_control(self, picker_type, on_pick_ok):
return create_picker_control(self.page, self.name, picker_type, on_pick_ok)
def _create_dir_control(self):
big_label_style= ft.TextStyle( size=20 )
row = ft.Row(controls=[],alignment= ft.MainAxisAlignment.CENTER)
controls = []
def on_pick_ok(v):
txt.value = v
self.val = self.format_func(txt.value)
def on_change(e: ft.ControlEvent):
val = e.control.value
self.val = self.format_func(val)
btn = self._create_picker_control("dir", on_pick_ok)
controls.append(btn)
txt = ft.TextField(self.val,label=self.name, label_style=big_label_style, expand=True, dense=True, on_change=on_change, text_size=15)
controls.append(txt)
row.controls = controls
return row
def _create_image_control(self, ui_type):
def update_value(v):
if ui_type == "image":
self.val[0] = v if type(v)==list else [v]
else:
self.val = v
if ui_type == "image":
image_rule, focus_target, focus_scale = validate_focus_rule(self.val)
self.val = ["", focus_target, focus_scale]
update_value(image_rule)
else:
image_rule = self.val
input_type, rule = validate_image_rule(image_rule)
big_label_style= ft.TextStyle( size=20 )
row = ft.Row(controls=[],alignment= ft.MainAxisAlignment.CENTER)
def create_control(input_type, rule):
controls = [label, type_cont]
if input_type == "image_file":
def on_pick_ok_image_file(v):
text.value = v
update_value(text.value)
def on_change_image_file(e: ft.ControlEvent):
update_value(text.value)
btn = self._create_picker_control("png", on_pick_ok_image_file)
controls.append(btn)
text = ft.TextField(rule, label="input image_file path", expand=True, on_change=on_change_image_file, text_size=15)
controls.append(text)
elif input_type == "image_directory":
def on_pick_ok_image_dir(v):
text.value = v
update_value([text.value, dd1.value, dd2.value])
def on_change_image_directory(e: ft.ControlEvent):
update_value([text.value, dd1.value, dd2.value])
btn = self._create_picker_control("dir", on_pick_ok_image_dir)
controls.append(btn)
text = ft.TextField(rule[0], label="input image_directory path", expand=True, on_change=on_change_image_directory, text_size=15)
controls.append(text)
opt = [ft.dropdown.Option(o) for o in ["random","sort"]]
dd1 = ft.Dropdown(rule[1],label="pick rule", width=150, options=opt, on_change=on_change_image_directory, options_fill_horizontally=True, text_size=15)
controls.append(dd1)
opt = [ft.dropdown.Option(o) for o in ["@random","@random_per_seq","@random_once"]]
dd2 = ft.Dropdown(rule[2],label="pick timing", width=150, options=opt, on_change=on_change_image_directory, options_fill_horizontally=True, text_size=15)
controls.append(dd2)
elif input_type == "movie_file":
def on_pick_ok_movie_file(v):
text.value = v
update_value([text.value, float(num.value)])
def on_change_movie_file(e: ft.ControlEvent):
update_value([text.value, float(num.value)])
btn = self._create_picker_control("mp4", on_pick_ok_movie_file)
controls.append(btn)
text = ft.TextField(rule[0], label="input movie_file path", expand=True, on_change=on_change_movie_file, text_size=15)
controls.append(text)
num = ft.TextField(rule[1], label="input interval seconds", input_filter=ft.InputFilter(regex_string=r"^(\d+(\.\d*)?|\.\d+)$", allow=True), on_change=on_change_movie_file, text_size=15)
controls.append(num)
elif input_type == "generation_result":
def on_change_generation_result(e: ft.ControlEvent):
update_value(int(num.value))
num = ft.TextField(rule, label="input generation number", expand=True, input_filter=ft.InputFilter(regex_string=r"^(\d+)$", allow=True), on_change=on_change_generation_result, text_size=15)
controls.append(num)
if ui_type == "image":
controls.append(f_text)
controls.append(f_num)
return controls
default_value = {
"image_file" : "",
"image_directory" : ["","random","@random"],
"movie_file" : ["", 1.0],
"generation_result" : 0,
}
label = ft.Text(self.name, width=100)
def on_change(e: ft.ControlEvent):
input_type = type_cont.value
update_value(default_value[input_type])
row.controls = create_control(input_type, default_value[input_type])
self.page.update()
if ui_type == "image":
opt = [ft.dropdown.Option(o) for o in ["image_file","image_directory","movie_file","generation_result"]]
else:
opt = [ft.dropdown.Option(o) for o in ["image_file","image_directory"]]
type_cont = ft.Dropdown(input_type,label="input_type", label_style=big_label_style, width=150, options=opt, on_change=on_change, options_fill_horizontally=True, text_size=15)
if ui_type == "image":
def on_change_focus(e: ft.ControlEvent):
self.val[1] = f_text.value
self.val[2] = f_num.value
f_text = ft.TextField(focus_target, label="focus target (ex. face)", width=200, on_change=on_change_focus, text_size=15)
f_num = ft.TextField(focus_scale, label="input focus scale", width=100, input_filter=ft.InputFilter(regex_string=r"^(\d+(\.\d*)?|\.\d+)$", allow=True), on_change=on_change_focus, text_size=15)
row.controls = create_control(input_type, rule)
return row
def _create_lora_selector(self, on_click_func):
conf2type={
"character_lora":LoraType.Character,
"character_lora2":LoraType.Character,
"style_lora":LoraType.Style,
"style_lora2":LoraType.Style,
"pose_lora":LoraType.Pose,
"pose_lora2":LoraType.Pose,
"item_lora":LoraType.Item,
"item_lora2":LoraType.Item,
}
def get_lora_list(lora_type:LoraType):
from sd_batch_runner.lora import get_lora_files_and_thumbs
lora_list = get_lora_files_and_thumbs(lora_type, (200,200))
lora_controls = []
def create_item(lora, thumb):
controls = [ ]
if thumb:
controls.append( ft.Image(src_base64=thumb) )
controls.append( ft.ElevatedButton(text=lora, width=200, on_click=on_click_func, data=lora) )
return ft.Column( controls, alignment=ft.MainAxisAlignment.CENTER, horizontal_alignment=ft.CrossAxisAlignment.CENTER )
for lora, _, thumb in lora_list:
lora_controls.append( ft.Container(create_item(lora, thumb), border=ft.border.all(5, ft.Colors.BLACK45) ) )
return lora_controls, [l[0] for l in lora_list], [l[1] for l in lora_list]
def _get_lora_list(lora_type:LoraType):
from sd_batch_runner.lora import get_lora_files_and_preview_paths
lora_list = get_lora_files_and_preview_paths(lora_type)
lora_controls = []
def create_item(lora, thumb):
controls = [ ]
if thumb:
controls.append( ft.Image(src=thumb, width=200, height=200) )
controls.append( ft.ElevatedButton(text=lora, width=200, on_click=on_click_func, data=lora) )
return ft.Column( controls, alignment=ft.MainAxisAlignment.CENTER, horizontal_alignment=ft.CrossAxisAlignment.CENTER )
for lora, thumb in lora_list:
lora_controls.append( ft.Container(create_item(lora, thumb), border=ft.border.all(5, ft.Colors.BLACK45) ) )
return lora_controls, [l[0] for l in lora_list]
dialog = ft.AlertDialog(
title=ft.Text(f"Select {self.name}"),
)
lora_list, lora_name_list, lora_date_list = get_lora_list( conf2type[self.name] )
lora_dict = {}
lora_date_dict = {}
for lc, ln in zip(lora_list, lora_name_list):
lora_dict[ln] = lc
for ld, ln in zip(lora_date_list, lora_name_list):
lora_date_dict[ln] = ld
visible_lora_name_list = lora_name_list.copy()
def on_filter_change(e: ft.ControlEvent):
nonlocal visible_lora_name_list
filter = filter_text.value
filter = filter.lower()
filter_list = filter.split("|")
filter_list = [f for f in filter_list if f]
if len(filter_list) == 0:
visible_lora_name_list = lora_name_list.copy()
else:
result = []
for f in filter_list:
result += [name for name in lora_name_list if name.lower().find(f) != -1]
visible_lora_name_list = list(dict.fromkeys(result))
if sort_type_radio.value == "name":
visible_lora_name_list = sorted(visible_lora_name_list, reverse= sort_order_radio.value == "descending")
else:
# date
name_date_list = [ (n, lora_date_dict[n]) for n in visible_lora_name_list]
name_date_list.sort(key=lambda x: x[1], reverse= sort_order_radio.value == "descending")
visible_lora_name_list = [ n[0] for n in name_date_list]
lora_col.controls = show_lora_list()
self.page.update()
filter_text = ft.TextField("", label="filter", on_change=on_filter_change)