{"id":18610039,"url":"https://github.com/koushiknavuluri/stable-diffusion-xl-api","last_synced_at":"2025-08-05T06:24:09.844Z","repository":{"id":186022649,"uuid":"673215426","full_name":"KoushikNavuluri/stable-diffusion-xl-api","owner":"KoushikNavuluri","description":"Reverse engineered API of Stable Diffusion XL 1.0 ( Midjourney Alternative ), A text-to-image generative AI model that creates beautiful 1024x1024 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Stable Diffusion XL ( API )\n\n   Reverse engineered API of Stable Diffusion XL 1.0 ( Midjourney Alternative ) via https://replicate.com/ , A text-to-image generative AI model that creates beautiful 1024x1024 images.\n\n\u003cimg src=\"https://github.com/KoushikNavuluri/stable-diffusion-xl-api/assets/103725723/50a81ef7-4f4e-4b46-a881-a55726b8e211\" width=\"900\" \u003e   \n\n# Table of Contents\n\n- [Stable Diffusion XL ( API )](#stable-diffusion-xl---api--)\n  * [Prerequisites](#prerequisites)\n  * [Installation](#installation)\n  * [Usage](#usage)\n  * [Send Prompt to generate image](#send-prompt-to-generate-image)\n    + [Output](#output)\n  * [Example Images Generated](#example-images-generated)\n  * [Advanced Generation using parameters](#advanced-generation-using-parameters)\n    + [List of parameters](#list-of-parameters)\n  * [CLI Version](#cli-version)\n  * [Disclaimer](#disclaimer)\n  * [License](#license)\n\n## Prerequisites\n\nTo use this API, you need to have the following:\n\nPython installed on your system\nrequests library installed \n```bash\n  pip install requests\n\n```\n\n## Installation\n\nTo use the Claude AI Unofficial API, you can either clone the GitHub repository or directly download the Python file.\n\nTerminal :\n\n    pip install sdxl\n    \nor\n\nClone the repository:\n\n    git clone https://github.com/KoushikNavuluri/stable-diffusion-xl-api.git\n\n## Usage\nImport the claude_api module in your Python script:\n\n    from sdxl import ImageGenerator\n\n* Next, you need to create an instance of the ImageGenerator class:\n  \n```bash\nclient = ImageGenerator()\n```\n## Send Prompt to generate image\n```bash\nimages = client.gen_image(\n    \"Vibrant, Headshot of a serene, meditating individual surrounded by soft, ambient lighting.\")\nprint(images)\n```\n\n### Output\n\n\n\u003cimg src=\"https://github.com/KoushikNavuluri/stable-diffusion-xl-api/assets/103725723/045c629e-5d0b-4ad0-bfaf-4abff7f2f7be\" width=\"600\" \u003e\n\n\n## Example Images Generated\n\n\n\u003cimg src=\"https://github.com/KoushikNavuluri/stable-diffusion-xl-api/assets/103725723/7588d73e-d224-44b9-9e65-efb05c63cb6f\" width=\"200\" \u003e\n\n\u003cimg src=\"https://github.com/KoushikNavuluri/stable-diffusion-xl-api/assets/103725723/99813d96-9174-4d70-be3e-b8f638299429\" width=\"200\"\u003e\n\n\u003cimg src=\"https://github.com/KoushikNavuluri/stable-diffusion-xl-api/assets/103725723/8cd02b68-a9d4-4b43-a824-c980c115dae8\" width=\"200\" \u003e\n\n\u003cimg src=\"https://github.com/KoushikNavuluri/stable-diffusion-xl-api/assets/103725723/14039a28-3605-41c7-8a97-33f7982a3f13\" width=\"200\"\u003e\n\n\n\n\n\n## Advanced Generation using parameters\n\n```bash\n#Parameters set to their default values\nimages = client.gen_image(prompt=\n    \"Vibrant, Headshot of a serene, meditating individual surrounded by soft, ambient lighting.\",count=1, width=1024, height=1024, refine=\"expert_ensemble_refiner\", scheduler=\"DDIM\", guidance_scale=7.5, high_noise_frac=0.8, prompt_strength=0.8, num_inference_steps=50)\nprint(images)\n```\n### List of parameters\n\n      *   prompt = Input text prompt\n      *   width  = Width of output image(max:1024)\n      *   height = height of output image(max:1024)\n      *   count  = Number of images to output. (minimum: 1; maximum: 4) \n      *   refine = Which refine style to use ( no_refiner or expert_ensemble_refiner or base_image_refiner )\n      *   scheduler = scheduler (valid_schedulers = [\"DDIM\" or \"DPMSolverMultistep\" or \"HeunDiscrete\" or \"KarrasDPM\" or \"K_EULER_ANCESTRAL\" or \"K_EULER\" or \"PNDM\"])\n      *   guidance_scale = Scale for classifier-free guidance (minimum: 1; maximum: 50) \n      *   prompt_strength = Prompt strength in image (maximum: 1) \n      *   num_inference_steps = Number of denoising steps (minimum: 1; maximum: 500) \n      *   high_noise_frac = for expert_ensemble_refiner, the fraction of noise to use (maximum: 1)\n      \n## CLI Version\n\nFor cli version you can check example folder in this repository (filename:cli.py)\n\n\u003e How to:\n\n```bash\npython main.py \"beautiful landscape with two kittens,realistic,4k\" --count 1 --width 1024 --height 1024 --refine expert_ensemble_refiner --scheduler DDIM --guidance_scale 7.5 --high_noise_frac 0.6 --prompt_strength 0.9 --num_inference_steps 40\n\n```\n\n## Disclaimer\n\nThis project provides an unofficial API for Replicate's Stable Diffusion XL and is not affiliated with or endorsed by Replicate or Stable Diffusion. Use it at your own risk.\n\n## License\nThis project is licensed under the [MIT](https://choosealicense.com/licenses/mit/) License - see the LICENSE file for details.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkoushiknavuluri%2Fstable-diffusion-xl-api","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkoushiknavuluri%2Fstable-diffusion-xl-api","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkoushiknavuluri%2Fstable-diffusion-xl-api/lists"}