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| import spaces | |
| import torch | |
| from diffusers import StableDiffusionPipeline, UNet2DConditionModel | |
| import gradio as gr | |
| model_id = "UX4567/Stable-Diffusion-v1-3.0" | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| print("Model load ho raha hai...") | |
| trained_unet = UNet2DConditionModel.from_pretrained( | |
| model_id, | |
| torch_dtype=torch.float16 | |
| ) | |
| pipe = StableDiffusionPipeline.from_pretrained( | |
| "runwayml/stable-diffusion-v1-5", | |
| unet=trained_unet, | |
| torch_dtype=torch.float16, | |
| safety_checker=None # thoda fast hoga | |
| ).to(device) | |
| def generate_image(prompt): | |
| if not prompt.strip(): | |
| return None | |
| # Quality booster | |
| enhanced_prompt = f"{prompt}, ultra sharp, highly detailed, cinematic lighting, 8k" | |
| negative_prompt = "blurry, low quality, low-res, distorted, ugly, bad anatomy, watermark, text, deformed" | |
| image = pipe( | |
| prompt=enhanced_prompt, | |
| negative_prompt=negative_prompt, | |
| num_inference_steps=35, | |
| guidance_scale=8.5, # 7.5 se 8.5 - thoda zyada sharp | |
| width=512, | |
| height=768 # tere cyberpunk wale ke liye vertical better lagega | |
| ).images[0] | |
| return image | |
| # Better UI - tere screenshot jaisa | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Calico Image Generator\nApne fine-tuned Stable Diffusion model se creative images generate karein!") | |
| with gr.Group(): | |
| prompt_box = gr.Textbox(label="Enter your prompt", value="a futuristic cyberpunk city at night", lines=2) | |
| with gr.Row(): | |
| clear_btn = gr.Button("Clear") | |
| submit_btn = gr.Button("Submit", variant="primary") | |
| output_img = gr.Image(label="Generated Image") | |
| gr.Markdown("Share via Link se share kar sakta hai tu!") | |
| submit_btn.click(fn=generate_image, inputs=prompt_box, outputs=output_img) | |
| clear_btn.click(lambda: ("", None), inputs=None, outputs=[prompt_box, output_img]) | |
| demo.launch() |