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| import os | |
| import base64 | |
| import io | |
| from typing import TypedDict | |
| import requests | |
| import gradio as gr | |
| from PIL import Image | |
| # Read Baseten configuration from environment variables. | |
| BTEN_API_KEY = os.getenv("API_KEY") | |
| URL = os.getenv("URL") | |
| def image_to_base64(image: Image.Image) -> str: | |
| with io.BytesIO() as buffer: | |
| image.save(buffer, format="PNG") | |
| return base64.b64encode(buffer.getvalue()).decode("utf-8") | |
| def ensure_image(img) -> Image.Image: | |
| if isinstance(img, Image.Image): | |
| return img | |
| elif isinstance(img, str): | |
| return Image.open(img) | |
| elif isinstance(img, dict) and "name" in img: | |
| return Image.open(img["name"]) | |
| else: | |
| raise ValueError("Cannot convert input to a PIL Image.") | |
| def call_baseten_generate(image: Image.Image, prompt: str, steps: int, strength: float, height: int, width: int, lora_name: str, remove_bg: bool) -> Image.Image | None: | |
| image = ensure_image(image) | |
| b64_image = image_to_base64(image) | |
| payload = { | |
| "image": b64_image, | |
| "prompt": prompt, | |
| "steps": steps, | |
| "strength": strength, | |
| "height": height, | |
| "width": width, | |
| "lora_name": lora_name, | |
| "bgrm": remove_bg, | |
| } | |
| headers = {"Authorization": f"Api-Key {BTEN_API_KEY or os.getenv('API_KEY')}"} | |
| try: | |
| if not URL: | |
| raise ValueError("The URL environment variable is not set.") | |
| response = requests.post(URL, headers=headers, json=payload) | |
| if response.status_code == 200: | |
| data = response.json() | |
| gen_b64 = data.get("generated_image", None) | |
| if gen_b64: | |
| return Image.open(io.BytesIO(base64.b64decode(gen_b64))) | |
| else: | |
| return None | |
| else: | |
| print(f"Error: HTTP {response.status_code}\n{response.text}") | |
| return None | |
| except Exception as e: | |
| print(f"Error: {e}") | |
| return None | |
| # ================== MODE CONFIG ===================== | |
| Mode = TypedDict("Mode", { | |
| "model": str, | |
| "prompt": str, | |
| "default_strength": float, | |
| "default_height": int, | |
| "default_width": int, | |
| "models": list[str], | |
| "remove_bg": bool, | |
| }) | |
| MODE_DEFAULTS: dict[str, Mode] = { | |
| "Subject Generation": { | |
| "model": "subject_99000_512", | |
| "prompt": "A detailed portrait with soft lighting", | |
| "default_strength": 1.2, | |
| "default_height": 512, | |
| "default_width": 512, | |
| "models": ["zendsd_512_146000", "subject_99000_512", "zen_26000_512"], | |
| "remove_bg": True, | |
| }, | |
| "Background Generation": { | |
| "model": "bg_canny_58000_1024", | |
| "prompt": "A vibrant background with dynamic lighting and textures", | |
| "default_strength": 1.2, | |
| "default_height": 1024, | |
| "default_width": 1024, | |
| "models": ["bgwlight_15000_1024", "bg_canny_58000_1024", "gen_back_7000_1024"], | |
| "remove_bg": True, | |
| }, | |
| "Canny": { | |
| "model": "canny_21000_1024", | |
| "prompt": "A futuristic cityscape with neon lights", | |
| "default_strength": 1.2, | |
| "default_height": 1024, | |
| "default_width": 1024, | |
| "models": ["canny_21000_1024"], | |
| "remove_bg": True, | |
| }, | |
| "Depth": { | |
| "model": "depth_9800_1024", | |
| "prompt": "A scene with pronounced depth and perspective", | |
| "default_strength": 1.2, | |
| "default_height": 1024, | |
| "default_width": 1024, | |
| "models": ["depth_9800_1024"], | |
| "remove_bg": True, | |
| }, | |
| "Deblurring": { | |
| "model": "deblurr_1024_10000", | |
| "prompt": "A scene with pronounced depth and perspective", | |
| "default_strength": 1.2, | |
| "default_height": 1024, | |
| "default_width": 1024, | |
| "models": ["deblurr_1024_10000"], | |
| "remove_bg": False, | |
| }, | |
| } | |
| # ================== PRESET EXAMPLES ===================== | |
| MODE_EXAMPLES = { | |
| "Subject Generation": [ | |
| ["assets/subj1.jpg", "Close-up portrait of a fruit bowl", "assets/subj1_out.jpg"], | |
| ["assets/subj2.jpg", "A penguin standing in snow", "assets/subj2_out.jpg"], | |
| ["assets/subj3.jpg", "A cat with glowing eyes", "assets/subj3_out.jpg"], | |
| ["assets/subj4.jpg", "A child playing with bubbles", "assets/subj4_out.jpg"], | |
| ["assets/subj5.jpg", "A stylish young man in neon lights", "assets/subj5_out.jpg"], | |
| ["assets/subj6.jpg", "Old man with a mysterious look", "assets/subj6_out.jpg"], | |
| ], | |
| "Background Generation": [ | |
| ["assets/bg1.jpg", "Modern living room with plants", "assets/bg1_out.jpg"], | |
| ["assets/bg2.jpg", "Fantasy forest background", "assets/bg2_out.jpg"], | |
| ["assets/bg3.jpg", "Futuristic cityscape", "assets/bg3_out.jpg"], | |
| ["assets/bg4.jpg", "Minimalist white studio", "assets/bg4_out.jpg"], | |
| ["assets/bg5.jpg", "Snowy mountain landscape", "assets/bg5_out.jpg"], | |
| ["assets/bg6.jpg", "Golden sunset over the sea", "assets/bg6_out.jpg"], | |
| ], | |
| "Canny": [ | |
| ["assets/canny1.jpg", "A neon cyberpunk city skyline", "assets/canny1_out.jpg"], | |
| ["assets/canny2.jpg", "A robot walking in the fog", "assets/canny2_out.jpg"], | |
| ["assets/canny3.jpg", "A futuristic vehicle parked under a bridge", "assets/canny3_out.jpg"], | |
| ["assets/canny4.jpg", "Sci-fi lab interior with glowing machinery", "assets/canny4_out.jpg"], | |
| ["assets/canny5.jpg", "A portrait of a woman outlined in neon", "assets/canny5_out.jpg"], | |
| ["assets/canny6.jpg", "Post-apocalyptic abandoned street", "assets/canny6_out.jpg"], | |
| ], | |
| "Depth": [ | |
| ["assets/depth1.jpg", "A narrow alleyway with deep perspective", "assets/depth1_out.jpg"], | |
| ["assets/depth2.jpg", "A mountain road vanishing into the distance", "assets/depth2_out.jpg"], | |
| ["assets/depth3.jpg", "A hallway with strong depth of field", "assets/depth3_out.jpg"], | |
| ["assets/depth4.jpg", "A misty forest path stretching far away", "assets/depth4_out.jpg"], | |
| ["assets/depth5.jpg", "A bridge over a deep canyon", "assets/depth5_out.jpg"], | |
| ["assets/depth6.jpg", "An underground tunnel with receding arches", "assets/depth6_out.jpg"], | |
| ], | |
| "Deblurring": [ | |
| ["assets/deblur1.jpg", "", "assets/deblur1_out.jpg"], | |
| ["assets/deblur2.jpg", "", "assets/deblur2_out.jpg"], | |
| ["assets/deblur3.jpg", "", "assets/deblur3_out.jpg"], | |
| ["assets/deblur4.jpg", "", "assets/deblur4_out.jpg"], | |
| ["assets/deblur5.jpg", "", "assets/deblur5_out.jpg"], | |
| ["assets/deblur6.jpg", "", "assets/deblur6_out.jpg"], | |
| ], | |
| } | |
| # ================== UI ===================== | |
| header = """ | |
| <h1>🌍 ZenCtrl / FLUX</h1> | |
| <div align="center" style="line-height: 1;"> | |
| <a href="https://github.com/FotographerAI/ZenCtrl/tree/main" target="_blank"><img src="https://img.shields.io/badge/GitHub-Repo-181717.svg"></a> | |
| <a href="https://huggingface.co/spaces/fotographerai/ZenCtrl" target="_blank"><img src="https://img.shields.io/badge/🤗_HuggingFace-Space-ffbd45.svg"></a> | |
| <a href="https://discord.com/invite/b9RuYQ3F8k" target="_blank"><img src="https://img.shields.io/badge/Discord-Join-7289da.svg?logo=discord"></a> | |
| </div> | |
| """ | |
| with gr.Blocks(title="🌍 ZenCtrl") as demo: | |
| gr.HTML(header) | |
| gr.Markdown("# ZenCtrl Demo") | |
| with gr.Tabs(): | |
| for mode in MODE_DEFAULTS: | |
| with gr.Tab(mode): | |
| defaults = MODE_DEFAULTS[mode] | |
| gr.Markdown(f"### {mode} Mode") | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| input_image = gr.Image(label="Input Image", type="pil") | |
| generate_button = gr.Button("Generate") | |
| with gr.Blocks(): | |
| model_dropdown = gr.Dropdown( | |
| label="Model", | |
| choices=defaults["models"], | |
| value=defaults["model"], | |
| interactive=True, | |
| ) | |
| remove_bg_checkbox = gr.Checkbox( | |
| label="Remove Background", value=defaults["remove_bg"] | |
| ) | |
| with gr.Column(scale=2): | |
| output_image = gr.Image(label="Generated Image", type="pil") | |
| prompt_box = gr.Textbox( | |
| label="Prompt", value=defaults["prompt"], lines=2 | |
| ) | |
| with gr.Accordion("Generation Parameters", open=False): | |
| with gr.Row(): | |
| step_slider = gr.Slider( | |
| minimum=2, maximum=28, value=2, step=2, label="Steps" | |
| ) | |
| strength_slider = gr.Slider( | |
| minimum=0.5, | |
| maximum=2.0, | |
| value=defaults["default_strength"], | |
| step=0.1, | |
| label="Strength", | |
| ) | |
| with gr.Row(): | |
| height_slider = gr.Slider( | |
| minimum=512, | |
| maximum=1360, | |
| value=defaults["default_height"], | |
| step=1, | |
| label="Height", | |
| ) | |
| width_slider = gr.Slider( | |
| minimum=512, | |
| maximum=1360, | |
| value=defaults["default_width"], | |
| step=1, | |
| label="Width", | |
| ) | |
| def on_generate_click(model_name, prompt, steps, strength, height, width, remove_bg, image): | |
| return call_baseten_generate(image, prompt, steps, strength, height, width, model_name, remove_bg) | |
| generate_button.click( | |
| fn=on_generate_click, | |
| inputs=[ | |
| model_dropdown, | |
| prompt_box, | |
| step_slider, | |
| strength_slider, | |
| height_slider, | |
| width_slider, | |
| remove_bg_checkbox, | |
| input_image, | |
| ], | |
| outputs=[output_image], | |
| ) | |
| # ---------------- Templates -------------------- | |
| gr.Dataset( | |
| label="Presets (Input / Prompt / Output)", | |
| headers=["Input", "Prompt", "Output"], | |
| components=[input_image, prompt_box, output_image], | |
| samples=MODE_EXAMPLES.get(mode, []), | |
| samples_per_page=6, | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |