from typing import cast from comfydeploy import ComfyDeploy import asyncio import os import gradio as gr from gradio.components.image_editor import EditorValue from PIL import Image import requests import dotenv from gradio_imageslider import ImageSlider from io import BytesIO import base64 import glob import numpy as np dotenv.load_dotenv() API_KEY = os.environ.get("API_KEY") DEPLOYMENT_ID = os.environ.get("DEPLOYMENT_ID", "DEPLOYMENT_ID_NOT_SET") if not API_KEY: raise ValueError( "Please set API_KEY and DEPLOYMENT_ID in your environment variables" ) if DEPLOYMENT_ID == "DEPLOYMENT_ID_NOT_SET": raise ValueError("Please set DEPLOYMENT_ID in your environment variables") client = ComfyDeploy(bearer_auth=API_KEY) def get_base64_from_image(image: Image.Image) -> str: buffered: BytesIO = BytesIO() image.save(buffered, format="PNG") return base64.b64encode(buffered.getvalue()).decode("utf-8") async def process_image( image: Image.Image | str | None, mask: Image.Image | str | None, progress: gr.Progress = gr.Progress(), ) -> Image.Image | None: progress(0, desc="Starting...") if image is None or mask is None: return None if isinstance(mask, str): mask = Image.open(mask) if isinstance(image, str): image = Image.open(image) image_base64 = get_base64_from_image(image) mask_base64 = get_base64_from_image(mask) # Prepare inputs inputs: dict = { "image": f"data:image/png;base64,{image_base64}", "mask": f"data:image/png;base64,{mask_base64}", } # Call ComfyDeploy API try: result = client.run.create( request={"deployment_id": DEPLOYMENT_ID, "inputs": inputs} ) if result and result.object: run_id: str = result.object.run_id progress(0, desc="Starting processing...") # Wait for the result while True: run_result = client.run.get(run_id=run_id) if not run_result.object: continue progress_value = ( run_result.object.progress if run_result.object.progress is not None else 0 ) status = ( run_result.object.live_status if run_result.object.live_status is not None else "Cold starting..." ) progress(progress_value, desc=f"Status: {status}") if run_result.object.status == "success": for output in run_result.object.outputs or []: if output.data and output.data.images: image_url: str = output.data.images[0].url # Download and return both the original and processed images response: requests.Response = requests.get(image_url) processed_image: Image.Image = Image.open( BytesIO(response.content) ) return processed_image return None elif run_result.object.status == "failed": print("Processing failed") return None await asyncio.sleep(2) # Wait for 2 seconds before checking again except Exception as e: print(f"Error: {e}") return None def resize(image: Image.Image, shortest_side: int = 768) -> Image.Image: if image.width <= shortest_side and image.height <= shortest_side: return image if image.width < image.height: return image.resize( size=(shortest_side, int(shortest_side * image.height / image.width)) ) return image.resize( size=(int(shortest_side * image.width / image.height), shortest_side) ) async def run_async( image_and_mask: EditorValue | None, progress: gr.Progress = gr.Progress(), ) -> tuple[Image.Image, Image.Image] | None: if not image_and_mask: return None alpha_channel = image_and_mask["layers"][0] alpha_channel = cast(np.ndarray, alpha_channel) mask_np = np.where(alpha_channel[:, :, 3] == 0, 0, 255).astype(np.uint8) image_np = image_and_mask["background"] image_np = cast(np.ndarray, image_np) # Save mask to ./masks.png mask = Image.fromarray(mask_np) mask = resize(mask) # mask.save("mask.png") # Save image to ./images.png image = Image.fromarray(image_np) image = resize(image) # image.save("image.png") output = await process_image( image, # type: ignore mask, # type: ignore progress, ) if output is None: return None return output, image def run_sync(*args): return asyncio.run(run_async(*args)) with gr.Blocks() as demo: gr.Markdown(""" # 🧹 Room Cleaner Upload an image and and use pen tool (pencil icon at the bottom) to mark the areas you want to remove. Click on the "Run" button to process the image and remove the marked areas. """) with gr.Row(): with gr.Column(): # The image overflow, fix image_and_mask = gr.ImageMask( label="Input Image and Mask", layers=False, show_fullscreen_button=False, sources=["upload"], show_download_button=False, interactive=True, height="full", width="full", ) with gr.Column(): image_slider = ImageSlider( label="Compare Original and Processed", interactive=False, ) process_btn = gr.ClearButton( value="Run", variant="primary", size="lg", components=[image_slider], ) process_btn.click( fn=run_sync, inputs=[ image_and_mask, ], outputs=[image_slider], api_name=False, ) # Build examples images_examples = glob.glob("examples/*") mask_examples = [img.replace("inputs", "masks") for img in images_examples] output_examples = [img.replace("inputs", "outputs") for img in images_examples] # examples = [ # [ # img, # mask, # (img, out), # ] # for img, mask, out in zip(images_examples, mask_examples, output_examples) # ] examples = [ [ { "background": "./examples/ex1.jpg", "layers": [], "composite": "./examples/ex1_mask.png", }, # ("./examples/ex1.jpg", "./examples/ex1_result.png"), ( "https://dropshare.blanchon.xyz/public/dropshare/ex1.jpg", "https://dropshare.blanchon.xyz/public/dropshare/ex1_results.png", ), ], [ { "background": "./examples/ex2.jpg", "layers": [], "composite": "./examples/ex2_mask.png", }, # ("./examples/ex2.jpg", "./examples/ex2_result.png"), ( "https://dropshare.blanchon.xyz/public/dropshare/ex2.jpg", "https://dropshare.blanchon.xyz/public/dropshare/ex2_result.png", ), ], [ { "background": "./examples/ex3.jpg", "layers": [], "composite": "./examples/ex3_mask.png", }, # ("./examples/ex3.jpg", "./examples/ex3_result.png"), ( "https://dropshare.blanchon.xyz/public/dropshare/ex3.jpg", "https://dropshare.blanchon.xyz/public/dropshare/ex3_result.png", ), ], [ { "background": "./examples/ex4.jpg", "layers": [], "composite": "./examples/ex4_mask.png", }, # ("./examples/ex4.jpg", "./examples/ex4_result.png"), ( "https://dropshare.blanchon.xyz/public/dropshare/ex4.jpg", "https://dropshare.blanchon.xyz/public/dropshare/ex4_result.png", ), ], ] # Update the gr.Examples call gr.Examples( examples=examples, inputs=[ image_and_mask, image_slider, ], api_name=False, ) if __name__ == "__main__": demo.launch(debug=True, share=True)