app.py

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)