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| import gradio as gr | |
| import json | |
| # Load the JSON workflow | |
| with open("/home/user/app/1workflo.json", "r") as file: | |
| workflow = json.load(file) | |
| def generate_linkedin_headshot(image, prompt): | |
| # Here you would integrate your logic to process the image and prompt | |
| # using the ComfyUI workflow. This is a placeholder for demonstration. | |
| # Assuming you have a function `apply_comfyui_workflow` that takes an image, | |
| # prompt, and the workflow JSON to produce the output. | |
| processed_image = apply_comfyui_workflow(image, prompt, workflow) | |
| return processed_image | |
| # Define the Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# LinkedIn Headshot Generator") | |
| with gr.Row(): | |
| with gr.Column(): | |
| image_input = gr.Image(label="Upload your headshot", type="pil") | |
| prompt_input = gr.Textbox(label="Describe the professional look you want (e.g., 'business casual, smiling')") | |
| with gr.Column(): | |
| output_image = gr.Image(label="Generated LinkedIn Headshot") | |
| generate_button = gr.Button("Generate Headshot") | |
| generate_button.click(fn=generate_linkedin_headshot, inputs=[image_input, prompt_input], outputs=output_image) | |
| # Launch the app | |
| demo.launch() | |