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| import gradio as gr | |
| import threading | |
| import os | |
| import torch | |
| os.environ["OMP_NUM_THREADS"] = str(os.cpu_count()) | |
| torch.set_num_threads(os.cpu_count()) | |
| model1 = gr.load("models/prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA") | |
| model2 = gr.load("models/Purz/face-projection") | |
| stop_event = threading.Event() | |
| def generate_images(text, selected_model, steps, cfg_scale, seed, width, height): | |
| stop_event.clear() | |
| if selected_model == "Model 1 (Turbo Realism)": | |
| model = model1 | |
| elif selected_model == "Model 2 (Face Projection)": | |
| model = model2 | |
| else: | |
| return ["Invalid model selection."] * 3 | |
| # Convert seed to integer (handle empty/None) | |
| try: | |
| seed = int(seed) if seed not in [None, ""] else -1 | |
| except: | |
| seed = -1 | |
| results = [] | |
| for i in range(3): | |
| if stop_event.is_set(): | |
| return ["Image generation stopped by user."] * 3 | |
| modified_text = f"{text} variation {i+1}" | |
| result = model( | |
| modified_text, | |
| #num_inference_steps=int(steps), | |
| guidance_scale=float(cfg_scale), | |
| height=int(height), | |
| width=int(width), | |
| seed=seed if seed != -1 else None | |
| ) | |
| results.append(result) | |
| return results | |
| def stop_generation(): | |
| """Stops the ongoing image generation by setting the stop_event flag.""" | |
| stop_event.set() | |
| return ["Generation stopped."] * 3 | |
| with gr.Blocks() as interface: | |
| gr.Markdown( | |
| "### ⚠ Sorry for the inconvenience. The Space is currently running on the CPU, which might affect performance. We appreciate your understanding." | |
| ) | |
| with gr.Row(): | |
| text_input = gr.Textbox(label="Prompt", placeholder="Type your imagination here...") | |
| model_selector = gr.Radio( | |
| ["Model 1 (Turbo Realism)", "Model 2 (Face Projection)"], | |
| label="Model Selection", | |
| value="Model 1 (Turbo Realism)" | |
| ) | |
| with gr.Accordion("Advanced Parameters", open=False): | |
| with gr.Row(): | |
| steps = gr.Slider(1, 150, value=25, label="Inference Steps", info="(20-50 for quality/speed balance)") | |
| cfg_scale = gr.Slider(1.0, 20.0, value=7.5, label="CFG Scale", info="(7-12 for good balance)") | |
| seed = gr.Number(label="Seed", value=-1, precision=0, info="-1 for random") | |
| with gr.Row(): | |
| width = gr.Dropdown( | |
| choices=["512", "640", "768", "896", "1024"], | |
| value="512", | |
| label="Width", | |
| allow_custom_value=True | |
| ) | |
| height = gr.Dropdown( | |
| choices=["512", "640", "768", "896", "1024"], | |
| value="512", | |
| label="Height", | |
| allow_custom_value=True | |
| ) | |
| with gr.Row(): | |
| generate_button = gr.Button("Generate 3 Images 🎨", variant="primary") | |
| stop_button = gr.Button("Stop Generation", variant="stop") | |
| with gr.Row(): | |
| output1 = gr.Image(label="Variant 1", type="pil", show_label=True) | |
| output2 = gr.Image(label="Variant 2", type="pil", show_label=True) | |
| output3 = gr.Image(label="Variant 3", type="pil", show_label=True) | |
| generate_button.click( | |
| generate_images, | |
| inputs=[text_input, model_selector, steps, cfg_scale, seed, width, height], | |
| outputs=[output1, output2, output3] | |
| ) | |
| stop_button.click( | |
| stop_generation, | |
| inputs=[], | |
| outputs=[output1, output2, output3] | |
| ) | |
| interface.launch() |