room_cleaner / app.py
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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_result.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)