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import gradio as gr
import os
import modules.wdtagger
# Daftar model dan ControlNet
models = ["Model A", "Model B", "Model C"]
vae = ["VAE A", "VAE B", "VAE C"]
controlnet_types = ["Canny", "Depth", "Normal", "Pose"]
schedulers = ["Euler", "LMS", "DDIM"]
# Fungsi placeholder
def load_model(selected_model):
return f"Model {selected_model} telah dimuat."
def generate_image(prompt, neg_prompt, width, height, scheduler, num_steps, num_images, cfg_scale, seed, model):
# Logika untuk menghasilkan gambar dari teks menggunakan model
return [f"Gambar {i+1} untuk prompt '{prompt}' dengan model '{model}'" for i in range(num_images)], {"prompt": prompt, "neg_prompt": neg_prompt}
def process_image(image, prompt, neg_prompt, model):
# Logika untuk memproses gambar menggunakan model
return f"Proses gambar dengan prompt '{prompt}' dan model '{model}'"
def controlnet_process(image, controlnet_type, model):
# Logika untuk memproses gambar menggunakan ControlNet
return f"Proses gambar dengan ControlNet '{controlnet_type}' dan model '{model}'"
def controlnet_process_func(image, controlnet_type, model):
# Update fungsi sesuai kebutuhan
return controlnet_process(image, controlnet_type, model)
def intpaint_func (image, controlnet_type, model):
# Update fungsi sesuai kebutuhan
return controlnet_process(image, controlnet_type, model)
def intpaint_func (image, controlnet_type, model):
# Update fungsi sesuai kebutuhan
return controlnet_process(image, controlnet_type, model)
with gr.Blocks(css= "style.css") as app:
# Dropdown untuk memilih model di luar tab dengan lebar kecil
with gr.Row():
model_dropdown = gr.Dropdown(choices=models, label="Model", value="Model B")
vae_dropdown = gr.Dropdown(choices=vae, label="VAE", value="VAE C")
# Tab untuk Text-to-Image
with gr.Tab("Text-to-Image"):
with gr.Row():
with gr.Column(scale=1):
prompt_input = gr.Textbox(label="Prompt", placeholder="Masukkan prompt teks", lines=2, elem_id="prompt-input")
neg_prompt_input = gr.Textbox(label="Neg Prompt", placeholder="Masukkan negasi prompt", lines=2, elem_id="neg-prompt-input")
generate_button = gr.Button("Generate", elem_id="generate-button", scale=0.13)
with gr.Row():
with gr.Column():
with gr.Row():
scheduler_input = gr.Dropdown(choices=schedulers, label="Sampling method", value=schedulers[0])
seed_input = gr.Number(label="Seed", value=-1)
with gr.Row():
width_input = gr.Slider(minimum=128, maximum=2048, step=128, label="Width", value=512)
batch_size = gr.Slider(minimum=1, maximum=24, step=1, label="Batch size", value=1)
with gr.Row():
height_input = gr.Slider(minimum=128, maximum=2048, step=128, label="Height", value=512)
batch_count = gr.Slider(minimum=1, maximum=24, step=1, label="Batch Count", value=1)
with gr.Row():
num_steps_input = gr.Slider(minimum=1, maximum=100, step=1, label="Sampling steps", value=20)
cfg_scale_input = gr.Slider(minimum=1, maximum=20, step=1, label="CFG Scale", value=7)
with gr.Accordion("Hires. fix", open=False):
use_hires = gr.Checkbox(label="Use Hires?", value=False, scale=0)
with gr.Row():
upscaler = gr.Dropdown(choices=schedulers, label="Upscaler", value=schedulers[0])
upscale_by = gr.Slider(minimum=1, maximum=8, step=1, label="Upscale by", value=2)
with gr.Row():
hires_steps = gr.Slider(minimum=1, maximum=50, step=1, label="Hires Steps", value=20)
denois_strength = gr.Slider(minimum=0, maximum=1, step=0.02, label="Denoising Strength", value=2)
with gr.Column():
# Gallery untuk output gambar
output_gallery = gr.Gallery(label="Hasil Gambar")
# Output teks JSON di bawah gallery
output_text = gr.Textbox(label="Output JSON", placeholder="Hasil dalam format JSON", lines=2)
def update_images(prompt, neg_prompt, width, height, scheduler, num_steps, num_images, cfg_scale, seed, model):
# Update fungsi sesuai kebutuhan
return generate_image(prompt, neg_prompt, width, height, scheduler, num_steps, num_images, cfg_scale, seed, model)
generate_button.click(fn=update_images, inputs=[prompt_input, neg_prompt_input, width_input, height_input, scheduler_input, num_steps_input, batch_size, batch_count, cfg_scale_input, seed_input, model_dropdown, vae_dropdown], outputs=[output_gallery, output_text])
# Tab untuk Image-to-Image
with gr.Tab("Image-to-Image"):
with gr.Row():
with gr.Column(scale=1):
prompt_input_i2i = gr.Textbox(label="Prompt", placeholder="Masukkan prompt teks", lines=2, elem_id="prompt-input")
neg_prompt_input_i2i = gr.Textbox(label="Neg Prompt", placeholder="Masukkan negasi prompt", lines=2, elem_id="neg-prompt-input")
generate_button = gr.Button("Generate", elem_id="generate-button", scale=0.13)
with gr.Row():
with gr.Column():
image_input = gr.Image(label="Unggah Gambar")
generate_button_i2i = gr.Button("Generate")
with gr.Row():
scheduler_input = gr.Dropdown(choices=schedulers, label="Sampling method", value=schedulers[0])
seed_input = gr.Number(label="Seed", value=-1)
with gr.Row():
steps = gr.Slider(minimum=1, maximum=100, step=1, label="Steps", value=20)
cfg_scale = gr.Slider(minimum=1, maximum=24, step=1, label="CFG Scale", value=7)
with gr.Row():
strength = gr.Slider(minimum=0, maximum=1, step=0.1, label="Strength", value=0.6)
with gr.Column():
output_image_i2i = gr.Image(label="Hasil Gambar")
def process_image_func(image, prompt, neg_prompt, model):
# Update fungsi sesuai kebutuhan
return process_image(image, prompt, neg_prompt, model)
generate_button_i2i.click(fn=process_image_func, inputs=[image_input, prompt_input_i2i, neg_prompt_input_i2i, model_dropdown, vae_dropdown], outputs=output_image_i2i)
# Tab untuk ControlNet
with gr.Tab("ControlNet"):
with gr.Row():
with gr.Column():
controlnet_dropdown = gr.Dropdown(choices=controlnet_types, label="Pilih Tipe ControlNet")
controlnet_image_input = gr.Image(label="Unggah Gambar untuk ControlNet")
controlnet_button = gr.Button("Proses dengan ControlNet")
with gr.Column():
controlnet_output_image = gr.Image(label="Hasil ControlNet")
controlnet_button.click(fn=controlnet_process_func, inputs=[controlnet_image_input, controlnet_dropdown, model_dropdown, vae_dropdown], outputs=controlnet_output_image)
# Tab untuk Intpainting
with gr.Tab ("Inpainting"):
with gr.Row():
with gr.Column():
image = gr.ImageMask(sources=["upload"], layers=False, transforms=[], format="png", label="base image", show_label=True)
btn = gr.Button("Inpaint!", elem_id="run_button")
prompt = gr.Textbox(placeholder="Your prompt (what you want in place of what is erased)", show_label=False, elem_id="prompt")
negative_prompt = gr.Textbox(label="negative_prompt", placeholder="Your negative prompt", info="what you don't want to see in the image")
guidance_scale = gr.Number(value=7.5, minimum=1.0, maximum=20.0, step=0.1, label="guidance_scale")
steps = gr.Number(value=20, minimum=10, maximum=30, step=1, label="steps")
strength = gr.Number(value=0.99, minimum=0.01, maximum=1.0, step=0.01, label="strength")
scheduler = gr.Dropdown(label="Schedulers", choices=schedulers, value="EulerDiscreteScheduler")
with gr.Column():
image_out = gr.Image(label="Output", elem_id="output-img")
btn.click(fn=intpaint_func, inputs=[image, prompt, negative_prompt, guidance_scale, steps, strength, scheduler], outputs=[image_out])
# Tab untuk Describe
with gr.Tab("Describe"):
with gr.Row():
with gr.Column():
# Components
image = gr.Image(type="pil", image_mode="RGBA", label="Input")
submit_button = gr.Button(value="Submit", variant="primary", size="lg")
model_repo = gr.Dropdown(modules.wdtagger.dropdown_list, value=modules.wdtagger.dropdown_list[0], label="Model")
general_thresh = gr.Slider(0, 1, step=modules.wdtagger.args.score_slider_step, value=args.score_general_threshold, label="General Tags Threshold", scale=3)
general_mcut_enabled = gr.Checkbox(value=False, label="Use MCut threshold", scale=1)
character_thresh = gr.Slider(0, 1, step=modules.wdtagger.args.score_slider_step, value=args.score_character_threshold, label="Character Tags Threshold", scale=3)
character_mcut_enabled = gr.Checkbox(value=False, label="Use MCut threshold", scale=1)
clear_button = gr.ClearButton(components=[image, model_repo, general_thresh, general_mcut_enabled, character_thresh, character_mcut_enabled], variant="secondary", size="lg")
with gr.Column():
sorted_general_strings = gr.Textbox(label="Output (string)")
rating = gr.Label(label="Rating")
character_res = gr.Label(label="Output (characters)")
general_res = gr.Label(label="Output (tags)")
clear_button.add([sorted_general_strings, rating, character_res, general_res])
submit_button.click(modules.wdtagger.predictor.predict, inputs=[image, model_repo, general_thresh, general_mcut_enabled, character_thresh, character_mcut_enabled], outputs=[sorted_general_strings, rating, character_res, general_res])
# Jalankan antarmuka
app.launch() |