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caption ui redesign

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2025-02-15 12:57:19 -05:00
parent af3a5d9866
commit e95bd93f67
12 changed files with 186 additions and 109 deletions
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modules/ui_caption.py
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import gradio as gr
from modules import shared, ui_common, generation_parameters_copypaste
from modules.interrogate import openclip
def update_vlm_params(*args):
vlm_max_tokens, vlm_num_beams, vlm_temperature, vlm_do_sample = args
shared.opts.interrogate_vlm_max_length = vlm_max_tokens
shared.opts.interrogate_vlm_num_beams = vlm_num_beams
shared.opts.interrogate_vlm_temperature = vlm_temperature
shared.opts.interrogate_vlm_do_sample = vlm_do_sample
def create_ui():
with gr.Row(equal_height=False, variant='compact', elem_classes="caption"):
with gr.Column(variant='compact'):
with gr.Row():
image = gr.Image(type='pil', label="Image")
with gr.Tabs(elem_id="mode_caption"):
with gr.Tab("CLiP Interrogate"):
with gr.Row():
clip_model = gr.Dropdown([], value=shared.opts.interrogate_clip_model, label='CLiP model')
ui_common.create_refresh_button(clip_model, openclip.refresh_clip_models, lambda: {"choices": openclip.refresh_clip_models()}, 'refresh_interrogate_models')
blip_model = gr.Dropdown(list(openclip.caption_models), value=shared.opts.interrogate_blip_model, label='Caption model')
mode = gr.Dropdown(openclip.caption_types, label='Mode', value='fast')
with gr.Accordion(label='Advanced', open=False, visible=True):
with gr.Row():
caption_max_length = gr.Slider(label='Max length', value=shared.opts.interrogate_clip_max_length, minimum=16, maximum=512, min_width=300)
chunk_size = gr.Slider(label='Chunk size', value=1024, minimum=256, maximum=4096, min_width=300)
with gr.Row():
min_flavors = gr.Slider(label='Min flavors', value=2, minimum=1, maximum=16, min_width=300)
max_flavors = gr.Slider(label='Max flavors', value=8, minimum=1, maximum=64, min_width=300)
flavor_intermediate_count = gr.Slider(label='Intermediates', value=1024, minimum=256, maximum=4096)
caption_max_length.change(fn=openclip.update_interrogate_params, inputs=[caption_max_length, chunk_size, min_flavors, max_flavors, flavor_intermediate_count], outputs=[])
chunk_size.change(fn=openclip.update_interrogate_params, inputs=[caption_max_length, chunk_size, min_flavors, max_flavors, flavor_intermediate_count], outputs=[])
min_flavors.change(fn=openclip.update_interrogate_params, inputs=[caption_max_length, chunk_size, min_flavors, max_flavors, flavor_intermediate_count], outputs=[])
max_flavors.change(fn=openclip.update_interrogate_params, inputs=[caption_max_length, chunk_size, min_flavors, max_flavors, flavor_intermediate_count], outputs=[])
flavor_intermediate_count.change(fn=openclip.update_interrogate_params, inputs=[caption_max_length, chunk_size, min_flavors, max_flavors, flavor_intermediate_count], outputs=[])
with gr.Accordion(label='Batch', open=False, visible=True):
with gr.Row():
batch_files = gr.File(label="Files", show_label=True, file_count='multiple', file_types=['image'], type='file', interactive=True, height=100)
with gr.Row():
batch_folder = gr.File(label="Folder", show_label=True, file_count='directory', file_types=['image'], type='file', interactive=True, height=100)
with gr.Row():
batch_str = gr.Text(label="Folder", value="", interactive=True)
with gr.Row():
batch = gr.Text(label="Prompts", lines=10)
with gr.Row():
clip_model = gr.Dropdown([], value='ViT-L-14/openai', label='CLiP Batch Model')
ui_common.create_refresh_button(clip_model, openclip.refresh_clip_models, lambda: {"choices": openclip.refresh_clip_models()}, 'refresh_interrogate_models')
with gr.Row(elem_id='interrogate_buttons_batch'):
btn_interrogate_batch = gr.Button("Batch interrogate", elem_id="interrogate_btn_interrogate", variant='primary')
with gr.Row():
save_output = gr.Checkbox(label='Save output', value=True, elem_id="extras_save_output")
with gr.Row(elem_id='interrogate_buttons_image'):
btn_interrogate_img = gr.Button("Interrogate", elem_id="interrogate_btn_interrogate", variant='primary')
btn_analyze_img = gr.Button("Analyze", elem_id="interrogate_btn_analyze", variant='primary')
with gr.Tab("VLM Caption"):
from modules.interrogate import vqa
with gr.Row():
vqa_question = gr.Dropdown(label="Predefined question", allow_custom_value=False, choices=vqa.vlm_prompts, value=vqa.vlm_prompts[2])
with gr.Row():
vqa_prompt = gr.Textbox(label="Prompt", placeholder="optionally enter custom prompt", lines=2)
with gr.Row(elem_id='interrogate_buttons_query'):
vqa_model = gr.Dropdown(list(vqa.vlm_models), value=list(vqa.vlm_models)[0], label='VLM Model')
with gr.Accordion(label='Advanced', open=False, visible=True):
with gr.Row():
vlm_max_tokens = gr.Slider(label='Max tokens', value=shared.opts.interrogate_vlm_max_length, minimum=16, maximum=4096, step=1)
vlm_num_beams = gr.Slider(label='Num beams', value=shared.opts.interrogate_vlm_num_beams, minimum=1, maximum=16, step=1)
vlm_temperature = gr.Slider(label='Temperature', value=shared.opts.interrogate_vlm_temperature, minimum=0.1, maximum=1.0, step=0.01)
with gr.Row():
vlm_do_sample = gr.Checkbox(label='Use sample', value=shared.opts.interrogate_vlm_do_sample)
vlm_max_tokens.change(fn=update_vlm_params, inputs=[vlm_max_tokens, vlm_num_beams, vlm_temperature, vlm_do_sample], outputs=[])
vlm_num_beams.change(fn=update_vlm_params, inputs=[vlm_max_tokens, vlm_num_beams, vlm_temperature, vlm_do_sample], outputs=[])
vlm_temperature.change(fn=update_vlm_params, inputs=[vlm_max_tokens, vlm_num_beams, vlm_temperature, vlm_do_sample], outputs=[])
vlm_do_sample.change(fn=update_vlm_params, inputs=[vlm_max_tokens, vlm_num_beams, vlm_temperature, vlm_do_sample], outputs=[])
with gr.Row(elem_id='interrogate_buttons_query'):
vqa_submit = gr.Button("Caption", elem_id="interrogate_btn_interrogate", variant='primary')
with gr.Column(variant='compact'):
with gr.Row():
prompt = gr.Textbox(label="Answer", lines=8, placeholder="ai generated image description")
with gr.Row(elem_id="interrogate_labels"):
medium = gr.Label(elem_id="interrogate_label_medium", label="Medium", num_top_classes=5, visible=False)
artist = gr.Label(elem_id="interrogate_label_artist", label="Artist", num_top_classes=5, visible=False)
movement = gr.Label(elem_id="interrogate_label_movement", label="Movement", num_top_classes=5, visible=False)
trending = gr.Label(elem_id="interrogate_label_trending", label="Trending", num_top_classes=5, visible=False)
flavor = gr.Label(elem_id="interrogate_label_flavor", label="Flavor", num_top_classes=5, visible=False)
with gr.Row(elem_id='copy_buttons_interrogate'):
copy_interrogate_buttons = generation_parameters_copypaste.create_buttons(["txt2img", "img2img", "control", "extras"])
btn_interrogate_img.click(openclip.interrogate_image, inputs=[image, clip_model, blip_model, mode], outputs=[prompt])
btn_analyze_img.click(openclip.analyze_image, inputs=[image, clip_model, blip_model], outputs=[medium, artist, movement, trending, flavor])
btn_interrogate_batch.click(fn=openclip.interrogate_batch, inputs=[batch_files, batch_folder, batch_str, clip_model, blip_model, mode, save_output], outputs=[batch])
vqa_submit.click(vqa.interrogate, inputs=[vqa_question, vqa_prompt, image, vqa_model], outputs=[prompt])
for tabname, button in copy_interrogate_buttons.items():
generation_parameters_copypaste.register_paste_params_button(generation_parameters_copypaste.ParamBinding(paste_button=button, tabname=tabname, source_text_component=prompt, source_image_component=image,))
generation_parameters_copypaste.add_paste_fields("caption", image, None)