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| import gradio as gr | |
| from torchvision import transforms | |
| import torch | |
| from main_inference import generate_mixed_image, generate_image, progress_video | |
| import matplotlib.colors as mcolors | |
| def run_generate_mixed_image(prompt1,prompt2): | |
| image = generate_mixed_image(prompt1,prompt2) | |
| return image | |
| def run_generate_image(prompt1,noise_checkbox): | |
| image = generate_image(prompt1,noised_image=noise_checkbox) | |
| return image | |
| def run_generate_image_with_color_doninance(prompt1,color,color_loss_scale,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,True,color,color_loss_scale,noised_image_checkbox_1) | |
| return image | |
| def run_process_video(prompt): | |
| # Ask for text input | |
| video = progress_video(prompt) | |
| return video | |
| description_text_to_image = """ ### Text to Image Generation | |
| 1. Write a Text Prompt. | |
| 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. | |
| 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. | |
| 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_progress_video = """ ### Get the full generation process video | |
| 1. Write a Text Prompt. | |
| 2. Output will be the video which contains frames of generated image, during various inference steps | |
| """ | |
| # 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') | |
| 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") | |
| video_output = gr.Video() | |
| 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") | |
| color_loss_scale = gr.inputs.Slider(minimum=0, maximum=255, default=40, step=1,label="Color Loss") | |
| 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() | |
| 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", "a dog playing in garden", "people enjoying around sea"], | |
| # inputs=[text_input,red_color_slider,green_color_slider,blue_color_slider,noised_image_checkbox], | |
| # outputs=image_input1, | |
| # fn=run_generate_image, | |
| # cache_examples=True, | |
| # examples_per_page=4) | |
| run_generate_image_button.click(run_generate_image, | |
| inputs=[text_input,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() | |
| 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", "a dog playing in garden", "people enjoying around sea"], | |
| # inputs=[text_input4,red_color_slider,green_color_slider,blue_color_slider,noised_image_checkbox], | |
| # outputs=image_input3, | |
| # fn=run_generate_image_with_color_doninance, | |
| # cache_examples=True, | |
| # examples_per_page=4) | |
| run_generate_image_with_color_doninance_button.click(run_generate_image_with_color_doninance, | |
| inputs=[text_input4,color,color_loss_scale,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() | |
| 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 = ["examples/12830823_87d2654e31.jpg", "examples/27782020_4dab210360.jpg", "examples/44129946_9eeb385d77.jpg"], | |
| # inputs=[text_input,red_color_slider_1,green_color_slider_1,blue_color_slider_1,noised_image_checkbox], | |
| # outputs=image_input4, | |
| # fn=run_generate_mixed_image, | |
| # cache_examples=True, | |
| # examples_per_page=4) | |
| run_generate_mixed_image_button.click(run_generate_mixed_image, | |
| inputs=[text_input2,text_input3,noised_image_checkbox_2], | |
| outputs=image_input4) | |
| #################################################################################################################### | |
| with gr.Tab("progress_video"): | |
| # Images | |
| with gr.Row(variant="panel"): | |
| with gr.Column(scale=1): | |
| text_input5.render() | |
| with gr.Column(scale=1): | |
| video_output.render() | |
| # Submit & Clear | |
| with gr.Row(): | |
| with gr.Column(): | |
| run_progress_video_button = gr.Button("progress_video", variant='primary') | |
| clear_btn_progress_video = gr.Button("Clear", variant="secondary") | |
| gr.Markdown(description_progress_video) | |
| # gr.Examples(examples = ["examples/12830823_87d2654e31.jpg", "examples/27782020_4dab210360.jpg", "examples/44129946_9eeb385d77.jpg"], | |
| # inputs=[text_input5], | |
| # outputs=video_output, | |
| # fn=run_process_video, | |
| # examples_per_page=4) | |
| run_progress_video_button.click(run_process_video, | |
| inputs=[ | |
| text_input5, | |
| ], | |
| outputs=video_output) | |
| ####################################################################################################################### | |
| ####################################################################################################################### | |
| 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) | |