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| import gradio as gr | |
| from torchvision import transforms | |
| import torch | |
| from main_inference import generate_mixed_image, generate_image | |
| from style_guidence import generate_with_prompt_style | |
| import matplotlib.colors as mcolors | |
| style_file_maps = { | |
| '3D Female Cyborgs':"style_embeddings/3d_female_cyborgs.bin", | |
| '80s Anime':"style_embeddings/80s_anime.bin", | |
| 'Anders Zorn':"style_embeddings/anders_zorn.bin", | |
| "Angus Mcbride":"style_embeddings/angus_mcbride.bin", | |
| "Breack Core":"style_embeddings/breakcore.bin", | |
| "Brittney Williams":"style_embeddings/brittney_williams.bin", | |
| "Bull vs Bear":"style_embeddings/bull_vs_bear.bin", | |
| "Caitlin FairChild":"style_embeddings/caitlin_fairchild.bin", | |
| "Exodus Styling":"style_embeddings/exodus_styling.bin", | |
| "FoorByv2":"style_embeddings/foorbyv2.bin" | |
| } | |
| def run_generate_mixed_image(prompt1,prompt2,num_of_inf_steps,noised_image): | |
| image = generate_mixed_image(prompt1,prompt2,num_of_inf_steps,noised_image) | |
| return image | |
| def run_generate_image(prompt1,num_of_inf_steps,noise_checkbox): | |
| image = generate_image(prompt1,num_inference_steps=num_of_inf_steps,noised_image=noise_checkbox) | |
| return image | |
| def run_generate_image_with_color_doninance(prompt1,color,color_loss_scale,num_of_inf_steps,noised_image_checkbox_1): | |
| # Convert the hexadecimal color code to RGB values | |
| rgba_color = mcolors.hex2color(color) | |
| # Multiply the RGB values by 255 to get them in the [0, 255] range | |
| rgb_values = [int(val * 255) for val in rgba_color] | |
| image = generate_image(prompt1,num_of_inf_steps,True,rgb_values,color_loss_scale,noised_image_checkbox_1) | |
| return image | |
| def run_generate_image_with_style(prompt,style,num_of_inf_steps): | |
| output = generate_with_prompt_style(prompt, style_file_maps[style],num_of_inf_steps) | |
| return output | |
| description_text_to_image = """ ### Text to Image Generation | |
| 1. Write a Text Prompt and number of inference steps, the more the better results but execution time will be high. | |
| 2. Output will be an image based on the text prompt provided. | |
| 3. Check if you want to see noised version of the image | |
| """ | |
| description_generate_mixed_image = """ ### Mix Image Generation | |
| 1. Write Two Text prompts and number of inference steps, the more the better results but execution time will be high. | |
| 2. Output will a image which is mix of both of the text provided. | |
| 3. Check if you want to see noised version of the image | |
| """ | |
| description_generate_image_with_color_dominance = """ ### Generate Images with color dominance | |
| 1. Write a Text Prompt and number of inference steps, the more the better results but execution time will be high. | |
| 2. Select a color | |
| 3. Choose Color loss value | |
| 4. Get the generated Image | |
| 5. Check if you want to see noised version of the image | |
| """ | |
| description_generate_prompt_with_style = """ ### Get a generated image in the selection of your style | |
| 1. Write a Text Prompt and number of inference steps, the more the better results but execution time will be high. | |
| 2. Select a style to dominate the photo | |
| 3. Get the Output | |
| """ | |
| # Description | |
| title = "<center><strong><font size='8'>The Stable Diffusion</font></strong></center>" | |
| image_input1 = gr.Image(type='pil') | |
| image_input2 = gr.Image(type='filepath') | |
| image_input3 = gr.Image(type='pil') | |
| image_input4 = gr.Image(type='pil') | |
| image_input5 = gr.Image(type='pil') | |
| text_input = gr.Text(label="Enter Text Prompt") | |
| text_input2 = gr.Text(label="Enter Text Prompt") | |
| text_input3 = gr.Text(label="Enter Text Prompt") | |
| text_input4 = gr.Text(label = "Enter Text Prompt") | |
| text_input5 = gr.Text(label = "Enter Text Prompt") | |
| num_of_inf_steps_slider1 = gr.inputs.Slider(minimum=0, maximum=50, default=30, step=1,label="Num of Inference Steps") | |
| num_of_inf_steps_slider2 = gr.inputs.Slider(minimum=0, maximum=50, default=30, step=1,label="Num of Inference Steps") | |
| num_of_inf_steps_slider3 = gr.inputs.Slider(minimum=0, maximum=50, default=30, step=1,label="Num of Inference Steps") | |
| num_of_inf_steps_slider4 = gr.inputs.Slider(minimum=0, maximum=50, default=30, step=1,label="Num of Inference Steps") | |
| color = gr.ColorPicker(label="Select a Color",description="Choose a color from the color picker:") | |
| noised_image_checkbox = gr.inputs.Checkbox(default=False, label="Show Noised Image") | |
| noised_image_checkbox_1 = gr.inputs.Checkbox(default=False, label="Show Noised Image") | |
| noised_image_checkbox_2 = gr.inputs.Checkbox(default=False, label="Show Noised Image") | |
| noised_image_checkbox_3 = gr.inputs.Checkbox(default=False, label="Show Noised Image") | |
| color_loss_scale = gr.inputs.Slider(minimum=0, maximum=255, default=40, step=1,label="Color Loss") | |
| style_options = ['3D Female Cyborgs', '80s Anime','Anders Zorn',"Angus Mcbride","Breack Core", "Brittney Williams","Bull vs Bear","Caitlin FairChild","Exodus Styling","FoorByv2"] | |
| selected_style = gr.Dropdown(style_options,label="Select a Style to Follow",default="Anders Zorn") | |
| css = "h1 { text-align: center } .about { text-align: justify; padding-left: 10%; padding-right: 10%; }" | |
| with gr.Blocks(css=css, title='Play with Stable Diffusion') as demo: | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| # Title | |
| gr.Markdown(title) | |
| with gr.Tab("Generate Image"): | |
| # Images | |
| with gr.Row(variant="panel"): | |
| with gr.Column(scale=1): | |
| text_input.render() | |
| num_of_inf_steps_slider1.render() | |
| noised_image_checkbox.render() | |
| with gr.Column(scale=1): | |
| image_input1.render() | |
| # Submit & Clear | |
| with gr.Row(): | |
| with gr.Column(): | |
| run_generate_image_button = gr.Button("generate_image", variant='primary') | |
| clear_btn_text_to_image = gr.Button("Clear", variant="secondary") | |
| gr.Markdown(description_text_to_image) | |
| # gr.Examples(examples = [["A White cat",10,False]], | |
| # inputs=[text_input,num_of_inf_steps_slider1,noised_image_checkbox], | |
| # outputs=image_input1, | |
| # fn=run_generate_image, | |
| # cache_examples=True, | |
| # examples_per_page=3) | |
| run_generate_image_button.click(run_generate_image, | |
| inputs=[text_input,num_of_inf_steps_slider1,noised_image_checkbox], | |
| outputs=image_input1) | |
| with gr.Tab("Generate Image with Color Dominance"): | |
| # Images | |
| with gr.Row(variant="panel"): | |
| with gr.Column(scale=1): | |
| text_input4.render() | |
| color_loss_scale.render() | |
| num_of_inf_steps_slider2.render() | |
| noised_image_checkbox_1.render() | |
| color.render() | |
| with gr.Column(scale=1): | |
| image_input3.render() | |
| # Submit & Clear | |
| with gr.Row(): | |
| with gr.Column(): | |
| run_generate_image_with_color_doninance_button = gr.Button("generate_image_with_color_doninance", variant='primary') | |
| clear_btn_text_to_image = gr.Button("Clear", variant="secondary") | |
| gr.Markdown(description_generate_image_with_color_dominance) | |
| # gr.Examples(examples = [["A White cat",'#000000',40,20,True]], | |
| # inputs=[text_input4,color,color_loss_scale,num_of_inf_steps_slider2,noised_image_checkbox_1], | |
| # outputs=image_input3, | |
| # fn=run_generate_image_with_color_doninance, | |
| # cache_examples=True, | |
| # examples_per_page=1) | |
| run_generate_image_with_color_doninance_button.click(run_generate_image_with_color_doninance, | |
| inputs=[text_input4,color,color_loss_scale,num_of_inf_steps_slider2,noised_image_checkbox_1], | |
| outputs=image_input3) | |
| #################################################################################################################### | |
| with gr.Tab("Generate Mixed Image"): | |
| # Images | |
| with gr.Row(variant="panel"): | |
| with gr.Column(scale=1): | |
| text_input2.render() | |
| text_input3.render() | |
| num_of_inf_steps_slider3.render() | |
| noised_image_checkbox_2.render() | |
| with gr.Column(scale=1): | |
| image_input4.render() | |
| # Submit & Clear | |
| with gr.Row(): | |
| with gr.Column(): | |
| run_generate_mixed_image_button = gr.Button("generate_mixed_image", variant='primary') | |
| clear_btn_image_to_image = gr.Button("Clear", variant="secondary") | |
| gr.Markdown(description_generate_mixed_image) | |
| # gr.Examples(examples = [["A White cat","A white tiger with aggressive pose",20,True]], | |
| # inputs=[text_input2,text_input3,num_of_inf_steps_slider3,noised_image_checkbox_2], | |
| # outputs=image_input4, | |
| # fn=run_generate_mixed_image, | |
| # cache_examples=True, | |
| # examples_per_page=1) | |
| run_generate_mixed_image_button.click(run_generate_mixed_image, | |
| inputs=[text_input2,text_input3,num_of_inf_steps_slider3,noised_image_checkbox_2], | |
| outputs=image_input4) | |
| #################################################################################################################### | |
| with gr.Tab("Generate Image with Style"): | |
| # Images | |
| with gr.Row(variant="panel"): | |
| with gr.Column(scale=1): | |
| text_input5.render() | |
| num_of_inf_steps_slider4.render() | |
| selected_style.render() | |
| with gr.Column(scale=1): | |
| image_input5.render() | |
| # Submit & Clear | |
| with gr.Row(): | |
| with gr.Column(): | |
| run_progress_video_button = gr.Button("generate_image", variant='primary') | |
| clear_btn_progress_video = gr.Button("Clear", variant="secondary") | |
| gr.Markdown(description_generate_prompt_with_style) | |
| # gr.Examples(examples = [["A White cat","Anders Zorn",20]], | |
| # inputs=[text_input5,selected_style,num_of_inf_steps_slider4], | |
| # outputs=image_input5, | |
| # fn=run_generate_image_with_style, | |
| # examples_per_page=1) | |
| run_progress_video_button.click(run_generate_image_with_style, | |
| inputs=[ | |
| text_input5,selected_style,num_of_inf_steps_slider4 | |
| ], | |
| outputs=image_input5) | |
| ####################################################################################################################### | |
| ####################################################################################################################### | |
| def clear(): | |
| return None, None | |
| def clear_text(): | |
| return None, None, None | |
| clear_btn_text_to_image.click(clear, outputs=[image_input1, image_input1]) | |
| clear_btn_image_to_image.click(clear, outputs=[image_input2, image_input3]) | |
| clear_btn_progress_video.click(clear, outputs=[image_input2, image_input3]) | |
| demo.queue() | |
| demo.launch(debug=True) | |