| import gradio as gr | |
| import requests | |
| from PIL import Image | |
| from io import BytesIO | |
| import base64 | |
| api_url = "https://5cb20b40-572c-426f-9466-995256f9b6eb.id.repl.co/generate_image" | |
| def generate_image(model="FaeTastic", prompt="", seed=0, negative_prompt="", sampler="k_dpmpp_2s_a", steps=50): | |
| data = "?model=" + model + "&prompt=" + prompt + "&seed=" + str(seed) + "&negative_prompt=" + negative_prompt + "&sampler=" + sampler + "&steps=" + str(steps) | |
| response = requests.post(api_url + data, timeout=400) | |
| if response.status_code == 200: | |
| img_base64 = response.json()["url"] | |
| img_bytes = base64.b64decode(img_base64) | |
| img = Image.open(BytesIO(img_bytes)) | |
| return img | |
| else: | |
| return None | |
| inputs = [ | |
| gr.inputs.Dropdown(['Anygen', 'FaeTastic', 'HASDX', 'NeverEnding Dream', 'Openniji', 'PFG', 'PRMJ', 'ProtoGen', 'RealBiter' 'RCNZ Dumb Monkey', 'Uhmami', 'Unstable Ink Dream', 'Woop-Woop Photo' ], label="Model", default="FaeTastic"), | |
| gr.inputs.Textbox(label="Prompt"), | |
| gr.inputs.Number(label="Seed", default=0), | |
| gr.inputs.Textbox(label="Negative Prompt", default=""), | |
| gr.inputs.Dropdown(["k_lms", "k_heun", "k_euler", "k_euler_a", "k_dpm_2", "k_dpm_2_a", "DDIM", "k_dpm_fast", "k_dpm_adaptive", "k_dpmpp_2m", "k_dpmpp_2s_a", "k_dpmpp_sde"], label="Sampler", default="k_dpmpp_2s_a"), | |
| gr.inputs.Number(label="Steps", default=50) | |
| ] | |
| outputs = gr.outputs.Image(label="Generated Image", type="pil") | |
| interface = gr.Interface(generate_image, inputs, outputs, title="", | |
| description="<center>Some of the best Semi-realistic Diffusion Models</center>", | |
| examples=[]) | |
| interface.launch() | |