mirror of
https://github.com/nod-ai/SHARK-Studio.git
synced 2026-01-09 13:57:54 -05:00
Simplify ui further, add CLI option to load a default config
This commit is contained in:
Ean Garvey
@@ -23,7 +23,6 @@ p = argparse.ArgumentParser(
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##############################################################################
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# Stable Diffusion Params
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##############################################################################
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p.add_argument(
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"-a",
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"--app",
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@@ -595,9 +594,10 @@ p.add_argument(
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# Web UI flags
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##############################################################################
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p.add_argument(
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"--default_config",
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"--defaults",
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default="sdxl-turbo.json",
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type=str,
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help="Path to the default API request .json file. Works for CLI and webui."
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)
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p.add_argument(
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@@ -14,6 +14,7 @@ from apps.shark_studio.web.utils.file_utils import (
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get_checkpoints_path,
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get_checkpoints,
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get_configs_path,
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get_configs,
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write_default_sd_configs,
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)
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from apps.shark_studio.api.sd import (
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@@ -148,7 +149,14 @@ def pull_sd_configs(
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def load_sd_cfg(sd_json: dict, load_sd_config: str):
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new_sd_config = none_to_str_none(json.loads(view_json_file(load_sd_config)))
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if os.path.exists(load_sd_config):
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config = load_sd_config
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elif os.path.exists(os.path.join(get_configs_path(), load_sd_config)):
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config = os.path.join(get_configs_path(), load_sd_config)
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else:
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print("Default config not found as absolute path or in configs folder. Using sdxl-turbo as default config.")
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config = sd_json
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new_sd_config = none_to_str_none(json.loads(view_json_file(config)))
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if sd_json:
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for key in new_sd_config:
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sd_json[key] = new_sd_config[key]
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@@ -241,17 +249,17 @@ def base_model_changed(base_model_id):
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) + get_checkpoints(model_type="checkpoints")
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if "turbo" in base_model_id:
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new_steps = gr.Dropdown(
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value=cmd_opts.steps,
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value=2,
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choices=[1, 2],
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label="\U0001F3C3\U0000FE0F Steps",
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allow_custom_value=False,
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allow_custom_value=True,
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)
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if "stable-diffusion-xl-base-1.0" in base_model_id:
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new_steps = gr.Dropdown(
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value=40,
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choices=[20, 25, 30, 35, 40, 45, 50],
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label="\U0001F3C3\U0000FE0F Steps",
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allow_custom_value=False,
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allow_custom_value=True,
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)
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elif ".py" in base_model_id:
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new_steps = gr.Dropdown(
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@@ -262,7 +270,7 @@ def base_model_changed(base_model_id):
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)
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else:
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new_steps = gr.Dropdown(
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value=cmd_opts.steps,
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value=20,
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choices=[10, 20, 30, 40, 50],
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label="\U0001F3C3\U0000FE0F Steps",
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allow_custom_value=True,
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@@ -276,70 +284,197 @@ def base_model_changed(base_model_id):
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new_steps,
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]
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init_config = global_obj.get_init_config()
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init_config = none_to_str_none(json.loads(view_json_file(init_config)))
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with gr.Blocks(title="Stable Diffusion") as sd_element:
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with gr.Column(elem_id="ui_body"):
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with gr.Row():
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with gr.Column(scale=2, min_width=600):
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with gr.Accordion(
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label="\U0001F4D0\U0000FE0F Device Settings", open=False
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):
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device = gr.Dropdown(
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elem_id="device",
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label="Device",
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value=global_obj.get_device_list()[0],
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choices=global_obj.get_device_list(),
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allow_custom_value=False,
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with gr.Group(elem_id="prompt_box_outer"):
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prompt = gr.Textbox(
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label="\U00002795\U0000FE0F Prompt",
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value=init_config["prompt"][0],
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lines=4,
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elem_id="prompt_box",
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show_copy_button=True,
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)
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with gr.Row():
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ondemand = gr.Checkbox(
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value=cmd_opts.lowvram,
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label="Low VRAM",
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interactive=True,
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visible=False,
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negative_prompt = gr.Textbox(
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label="\U00002796\U0000FE0F Negative Prompt",
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value=init_config["negative_prompt"][0],
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lines=4,
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elem_id="negative_prompt_box",
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show_copy_button=True,
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)
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with gr.Accordion(
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label="\U0001F4D0\U0000FE0F Advanced Settings", open=True
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):
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with gr.Accordion(
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label="Device Settings", open=False
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):
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device = gr.Dropdown(
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elem_id="device",
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label="Device",
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value=init_config["device"] if init_config["device"] else "rocm",
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choices=global_obj.get_device_list(),
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allow_custom_value=True,
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)
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target_triple = gr.Textbox(
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elem_id="target_triple",
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label="Architecture",
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value="",
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value=init_config["target_triple"],
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)
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precision = gr.Radio(
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label="Precision",
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value=cmd_opts.precision,
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choices=[
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"fp16",
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"fp32",
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],
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with gr.Row():
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ondemand = gr.Checkbox(
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value=init_config["ondemand"],
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label="Low VRAM",
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interactive=True,
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visible=False,
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)
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precision = gr.Radio(
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label="Precision",
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value=init_config["precision"],
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choices=[
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"fp16",
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"fp32",
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],
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visible=False,
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)
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with gr.Row():
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height = gr.Slider(
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512,
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1024,
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value=512,
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step=512,
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label="\U00002195\U0000FE0F Height",
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interactive=False, # DEMO
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visible=False, # DEMO
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)
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width = gr.Slider(
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512,
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1024,
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value=512,
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step=512,
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label="\U00002194\U0000FE0F Width",
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interactive=False, # DEMO
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visible=False, # DEMO
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)
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with gr.Accordion(
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label="\U0001F9EA\U0000FE0F Input Image Processing",
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open=False,
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visible=False,
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):
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strength = gr.Slider(
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0,
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1,
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value=init_config["strength"],
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step=0.01,
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label="Denoising Strength",
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)
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resample_type = gr.Dropdown(
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value=init_config["resample_type"],
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choices=resampler_list,
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label="Resample Type",
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allow_custom_value=True,
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)
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with gr.Row():
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sd_model_info = f"Checkpoint Path: {str(get_checkpoints_path())}"
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base_model_id = gr.Dropdown(
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label="\U000026F0\U0000FE0F Base Model",
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info="Select or enter HF model ID",
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elem_id="custom_model",
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value=init_config["base_model_id"],
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choices=sd_default_models,
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allow_custom_value=True,
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) # base_model_id
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with gr.Row(equal_height=True):
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seed = gr.Textbox(
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value=init_config["seed"],
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label="\U0001F331\U0000FE0F Seed",
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info="An integer, -1 for random",
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show_copy_button=True,
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)
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scheduler = gr.Dropdown(
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elem_id="scheduler",
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label="\U0001F4C5\U0000FE0F Scheduler",
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info="\U000E0020", # forces same height as seed
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value=init_config["scheduler"],
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choices=scheduler_model_map.keys(),
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allow_custom_value=False,
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)
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with gr.Row():
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steps = gr.Dropdown(
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value=20,
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choices=[10, 15, 20],
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label="\U0001F3C3\U0000FE0F Steps",
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allow_custom_value=True,
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)
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guidance_scale = gr.Slider(
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0,
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5, #DEMO
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value=4,
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step=0.1,
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label="\U0001F5C3\U0000FE0F CFG Scale",
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)
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with gr.Row():
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batch_count = gr.Slider(
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1,
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100,
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value=init_config["batch_count"],
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step=1,
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label="Batch Count",
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interactive=True,
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visible=True,
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)
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sd_model_info = f"Checkpoint Path: {str(get_checkpoints_path())}"
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base_model_id = gr.Dropdown(
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label="\U000026F0\U0000FE0F Base Model",
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info="Select or enter HF model ID",
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elem_id="custom_model",
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value="stabilityai/sdxl-turbo",
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choices=sd_default_models,
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allow_custom_value=True,
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) # base_model_id
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with gr.Row():
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height = gr.Slider(
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512,
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1024,
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value=512,
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step=512,
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label="\U00002195\U0000FE0F Height",
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interactive=False, # DEMO
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visible=False, # DEMO
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)
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width = gr.Slider(
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512,
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1024,
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value=512,
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step=512,
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label="\U00002194\U0000FE0F Width",
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interactive=False, # DEMO
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visible=False, # DEMO
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)
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batch_size = gr.Slider(
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1,
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4,
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value=init_config["batch_size"],
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step=1,
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label="Batch Size",
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interactive=False, # DEMO
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visible=True,
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)
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compiled_pipeline = gr.Checkbox(
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value=init_config["compiled_pipeline"],
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label="Faster txt2img (SDXL only)",
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visible=False, # DEMO
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)
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with gr.Row(elem_classes=["fill"], visible=False):
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Path(get_configs_path()).mkdir(
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parents=True, exist_ok=True
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)
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write_default_sd_configs(get_configs_path())
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default_config_file = global_obj.get_init_config()
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sd_json = gr.JSON(
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elem_classes=["fill"],
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value=view_json_file(default_config_file),
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)
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with gr.Row():
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with gr.Row():
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load_sd_config = gr.Dropdown(
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label="Load Config",
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value=cmd_opts.defaults,
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choices=get_configs(),
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allow_custom_value=True,
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)
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with gr.Row():
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save_sd_config = gr.Button(
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value="Save Config", size="sm"
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)
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clear_sd_config = gr.ClearButton(
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value="Clear Config",
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size="sm",
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components=sd_json,
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)
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# with gr.Row():
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sd_config_name = gr.Textbox(
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value="Config Name",
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info="Name of the file this config will be saved to.",
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interactive=True,
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show_label=False,
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)
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with gr.Accordion(
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label="\U00002696\U0000FE0F Model Weights",
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open=False,
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@@ -350,7 +485,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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label="Checkpoint Weights",
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info="Select or enter HF model ID",
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elem_id="custom_model",
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value="None",
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value=init_config["custom_weights"],
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allow_custom_value=True,
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choices=["None"]
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+ get_checkpoints(os.path.basename(str(base_model_id))),
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@@ -363,11 +498,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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label=f"VAE Model",
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info=sd_vae_info,
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elem_id="custom_model",
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value=(
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os.path.basename(cmd_opts.custom_vae)
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if cmd_opts.custom_vae
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else "None"
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),
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value=init_config["custom_vae"],
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choices=["None"] + get_checkpoints("vae"),
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allow_custom_value=True,
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scale=1,
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@@ -380,7 +511,7 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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label=f"Standalone LoRA Weights",
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info=sd_lora_info,
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elem_id="lora_weights",
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value=None,
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value=init_config["embeddings"][0] if (len(init_config["embeddings"].keys()) > 1) else "None",
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multiselect=True,
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choices=[] + get_checkpoints("lora"),
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scale=2,
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@@ -405,68 +536,6 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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outputs=[embeddings_config],
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show_progress=False,
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)
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with gr.Accordion(
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label="\U0001F9EA\U0000FE0F Input Image Processing",
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open=False,
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visible=False,
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):
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strength = gr.Slider(
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0,
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1,
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value=cmd_opts.strength,
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step=0.01,
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label="Denoising Strength",
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)
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resample_type = gr.Dropdown(
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value=cmd_opts.resample_type,
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choices=resampler_list,
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label="Resample Type",
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allow_custom_value=True,
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)
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with gr.Group(elem_id="prompt_box_outer"):
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prompt = gr.Textbox(
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label="\U00002795\U0000FE0F Prompt",
|
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value=cmd_opts.prompt[0],
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lines=2,
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elem_id="prompt_box",
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show_copy_button=True,
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)
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negative_prompt = gr.Textbox(
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label="\U00002796\U0000FE0F Negative Prompt",
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value=cmd_opts.negative_prompt[0],
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lines=2,
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elem_id="negative_prompt_box",
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show_copy_button=True,
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)
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with gr.Row(equal_height=True):
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seed = gr.Textbox(
|
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value=cmd_opts.seed,
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label="\U0001F331\U0000FE0F Seed",
|
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info="An integer, -1 for random",
|
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show_copy_button=True,
|
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)
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scheduler = gr.Dropdown(
|
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elem_id="scheduler",
|
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label="\U0001F4C5\U0000FE0F Scheduler",
|
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info="\U000E0020", # forces same height as seed
|
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value="EulerAncestralDiscrete",
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choices=scheduler_model_map.keys(),
|
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allow_custom_value=False,
|
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)
|
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with gr.Row():
|
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steps = gr.Dropdown(
|
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value=cmd_opts.steps,
|
||||
choices=[1, 2],
|
||||
label="\U0001F3C3\U0000FE0F Steps",
|
||||
allow_custom_value=True,
|
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)
|
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guidance_scale = gr.Slider(
|
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0,
|
||||
5, #DEMO
|
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value=cmd_opts.guidance_scale,
|
||||
step=0.1,
|
||||
label="\U0001F5C3\U0000FE0F CFG Scale",
|
||||
)
|
||||
with gr.Accordion(
|
||||
label="Controlnet Options",
|
||||
open=False,
|
||||
@@ -628,30 +697,6 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
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object_fit="fit",
|
||||
preview=True,
|
||||
)
|
||||
with gr.Row():
|
||||
batch_count = gr.Slider(
|
||||
1,
|
||||
100,
|
||||
value=cmd_opts.batch_count,
|
||||
step=1,
|
||||
label="Batch Count",
|
||||
interactive=True,
|
||||
visible=True,
|
||||
)
|
||||
batch_size = gr.Slider(
|
||||
1,
|
||||
4,
|
||||
value=cmd_opts.batch_size,
|
||||
step=1,
|
||||
label="Batch Size",
|
||||
interactive=True,
|
||||
visible=False, # DEMO
|
||||
)
|
||||
compiled_pipeline = gr.Checkbox(
|
||||
True,
|
||||
label="Faster txt2img (SDXL only)",
|
||||
visible=False, # DEMO
|
||||
)
|
||||
with gr.Row():
|
||||
stable_diffusion = gr.Button("Start")
|
||||
unload = gr.Button("Unload Models")
|
||||
@@ -661,90 +706,43 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
show_progress=False,
|
||||
)
|
||||
stop_batch = gr.Button("Stop", visible=False)
|
||||
with gr.Tab(label="Config", id=102) as sd_tab_config:
|
||||
with gr.Column(elem_classes=["sd-right-panel"]):
|
||||
with gr.Row(elem_classes=["fill"]):
|
||||
Path(get_configs_path()).mkdir(
|
||||
parents=True, exist_ok=True
|
||||
)
|
||||
write_default_sd_configs(get_configs_path())
|
||||
default_config_file = os.path.join(
|
||||
get_configs_path(),
|
||||
"sdxl-turbo.json",
|
||||
)
|
||||
sd_json = gr.JSON(
|
||||
elem_classes=["fill"],
|
||||
value=view_json_file(default_config_file),
|
||||
)
|
||||
with gr.Row():
|
||||
with gr.Column(scale=3):
|
||||
load_sd_config = gr.FileExplorer(
|
||||
label="Load Config",
|
||||
file_count="single",
|
||||
root_dir=(
|
||||
cmd_opts.configs_path
|
||||
if cmd_opts.configs_path
|
||||
else get_configs_path()
|
||||
),
|
||||
height=200,
|
||||
)
|
||||
with gr.Column(scale=1):
|
||||
save_sd_config = gr.Button(
|
||||
value="Save Config", size="sm"
|
||||
)
|
||||
clear_sd_config = gr.ClearButton(
|
||||
value="Clear Config",
|
||||
size="sm",
|
||||
components=sd_json,
|
||||
)
|
||||
# with gr.Row():
|
||||
sd_config_name = gr.Textbox(
|
||||
value="Config Name",
|
||||
info="Name of the file this config will be saved to.",
|
||||
interactive=True,
|
||||
show_label=False,
|
||||
)
|
||||
load_sd_config.change(
|
||||
fn=load_sd_cfg,
|
||||
inputs=[sd_json, load_sd_config],
|
||||
outputs=[
|
||||
prompt,
|
||||
negative_prompt,
|
||||
sd_init_image,
|
||||
height,
|
||||
width,
|
||||
steps,
|
||||
strength,
|
||||
guidance_scale,
|
||||
seed,
|
||||
batch_count,
|
||||
batch_size,
|
||||
scheduler,
|
||||
base_model_id,
|
||||
custom_weights,
|
||||
custom_vae,
|
||||
precision,
|
||||
device,
|
||||
target_triple,
|
||||
ondemand,
|
||||
compiled_pipeline,
|
||||
resample_type,
|
||||
cnet_config,
|
||||
embeddings_config,
|
||||
sd_json,
|
||||
],
|
||||
)
|
||||
save_sd_config.click(
|
||||
fn=save_sd_cfg,
|
||||
inputs=[sd_json, sd_config_name],
|
||||
outputs=[sd_config_name],
|
||||
)
|
||||
save_sd_config.click(
|
||||
fn=save_sd_cfg,
|
||||
inputs=[sd_json, sd_config_name],
|
||||
outputs=[sd_config_name],
|
||||
)
|
||||
with gr.Tab(label="Log", id=103) as sd_tab_log:
|
||||
# with gr.Tab(label="Config", id=102) as sd_tab_config:
|
||||
# with gr.Group():#elem_classes=["sd-right-panel"]):
|
||||
# with gr.Row(elem_classes=["fill"], visible=False):
|
||||
# Path(get_configs_path()).mkdir(
|
||||
# parents=True, exist_ok=True
|
||||
# )
|
||||
# write_default_sd_configs(get_configs_path())
|
||||
# default_config_file = global_obj.get_init_config()
|
||||
# sd_json = gr.JSON(
|
||||
# elem_classes=["fill"],
|
||||
# value=view_json_file(default_config_file),
|
||||
# )
|
||||
# with gr.Row():
|
||||
# with gr.Row():
|
||||
# load_sd_config = gr.Dropdown(
|
||||
# label="Load Config",
|
||||
# value=cmd_opts.defaults,
|
||||
# choices=get_configs(),
|
||||
# allow_custom_value=True,
|
||||
# )
|
||||
# with gr.Row():
|
||||
# save_sd_config = gr.Button(
|
||||
# value="Save Config", size="sm"
|
||||
# )
|
||||
# clear_sd_config = gr.ClearButton(
|
||||
# value="Clear Config",
|
||||
# size="sm",
|
||||
# components=sd_json,
|
||||
# )
|
||||
# # with gr.Row():
|
||||
# sd_config_name = gr.Textbox(
|
||||
# value="Config Name",
|
||||
# info="Name of the file this config will be saved to.",
|
||||
# interactive=True,
|
||||
# show_label=False,
|
||||
# )
|
||||
with gr.Tab(label="Log", id=103, visible=False) as sd_tab_log:
|
||||
with gr.Row():
|
||||
std_output = gr.Textbox(
|
||||
value=f"{sd_model_info}\n"
|
||||
@@ -765,7 +763,41 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
inputs=[base_model_id],
|
||||
outputs=[custom_weights, steps],
|
||||
)
|
||||
|
||||
load_sd_config.change(
|
||||
fn=load_sd_cfg,
|
||||
inputs=[sd_json, load_sd_config],
|
||||
outputs=[
|
||||
prompt,
|
||||
negative_prompt,
|
||||
sd_init_image,
|
||||
height,
|
||||
width,
|
||||
steps,
|
||||
strength,
|
||||
guidance_scale,
|
||||
seed,
|
||||
batch_count,
|
||||
batch_size,
|
||||
scheduler,
|
||||
base_model_id,
|
||||
custom_weights,
|
||||
custom_vae,
|
||||
precision,
|
||||
device,
|
||||
target_triple,
|
||||
ondemand,
|
||||
compiled_pipeline,
|
||||
resample_type,
|
||||
cnet_config,
|
||||
embeddings_config,
|
||||
sd_json,
|
||||
],
|
||||
)
|
||||
save_sd_config.click(
|
||||
fn=save_sd_cfg,
|
||||
inputs=[sd_json, sd_config_name],
|
||||
outputs=[sd_config_name],
|
||||
)
|
||||
pull_kwargs = dict(
|
||||
fn=pull_sd_configs,
|
||||
inputs=[
|
||||
|
||||
@@ -100,6 +100,15 @@ def get_checkpoints(model_type="checkpoints"):
|
||||
ckpt_files.extend(files)
|
||||
return sorted(ckpt_files, key=str.casefold)
|
||||
|
||||
def get_configs():
|
||||
return sorted(
|
||||
[
|
||||
os.path.basename(x)
|
||||
for x in glob.glob(os.path.join(get_configs_path(), "*.json"))
|
||||
],
|
||||
key=str.casefold,
|
||||
)
|
||||
|
||||
|
||||
def get_checkpoint_pathfile(checkpoint_name, model_type="checkpoints"):
|
||||
return os.path.join(get_checkpoints_path(model_type), checkpoint_name)
|
||||
|
||||
@@ -1,12 +1,18 @@
|
||||
import gc
|
||||
from ...api.utils import get_available_devices
|
||||
|
||||
from apps.shark_studio.modules.shared_cmd_opts import cmd_opts
|
||||
import os
|
||||
from apps.shark_studio.web.utils.file_utils import get_configs_path
|
||||
"""
|
||||
The global objects include SD pipeline and config.
|
||||
Maintaining the global objects would avoid creating extra pipeline objects when switching modes.
|
||||
Also we could avoid memory leak when switching models by clearing the cache.
|
||||
"""
|
||||
|
||||
def view_json_file(file_path):
|
||||
content = ""
|
||||
with open(file_path, "r") as fopen:
|
||||
content = fopen.read()
|
||||
return content
|
||||
|
||||
def _init():
|
||||
global _sd_obj
|
||||
@@ -89,6 +95,16 @@ def get_device_list():
|
||||
global _devices
|
||||
return _devices
|
||||
|
||||
def get_init_config():
|
||||
global _init_config
|
||||
if os.path.exists(cmd_opts.defaults):
|
||||
_init_config = cmd_opts.defaults
|
||||
elif os.path.exists(os.path.join(get_configs_path(), cmd_opts.defaults)):
|
||||
_init_config = os.path.join(get_configs_path(), cmd_opts.defaults)
|
||||
else:
|
||||
print("Default config not found as absolute path or in configs folder. Using sdxl-turbo as default config.")
|
||||
_init_config = os.path.join(get_configs_path(), "sdxl-turbo.json")
|
||||
return _init_config
|
||||
|
||||
def get_sd_status():
|
||||
global _sd_obj
|
||||
|
||||
Reference in New Issue
Block a user