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import streamlit as st
import requests
from PIL import Image
from io import BytesIO
from streamlit_drawable_canvas import st_canvas
# API information (your actual token)
url = "https://api.magicstudio.com/magiceraser/erase"
access_token = 'eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJjbGllbnRfaWQiOiIyRGZQSm1sY1BLalBuaGh4ajBxSVpmQktfbS12RFhTc1NMRFNOX1gtZlVVIiwiZXhwIjoxNzI3MTY0MTcyLCJhcHBfbmFtZSI6IjE3NTMwODQiLCJtZXRhZGF0YSI6bnVsbCwiZ3JhbnRfdHlwZSI6ImNyZWQifQ.24oHGH9ial_gqeYrpUbYP68MwYly2ArzXbhbE1hGzQo' # Your token
# Helper function for downloading the processed image
def image_download_button(pil_image, filename: str, fmt: str, label="Download"):
pil_format = "JPEG" if fmt == "jpg" else "PNG"
file_format = "jpg" if fmt == "jpg" else "png"
mime = "image/jpeg" if fmt == "jpg" else "image/png"
buf = BytesIO()
pil_image.save(buf, format=pil_format)
return st.download_button(
label=label,
data=buf.getvalue(),
file_name=f'{filename}.{file_format}',
mime=mime,
)
# Set the title of the app
st.title("AI Photo Object Removal")
# Upload the image
uploaded_file = st.file_uploader("Upload an image to remove objects from", type=["png", "jpg", "jpeg"])
if uploaded_file is not None:
# Load the uploaded image
img_input = Image.open(uploaded_file).convert("RGBA")
# Resize image if too large
max_size = 2000
img_width, img_height = img_input.size
if img_width > max_size or img_height > max_size:
if img_width > img_height:
new_width = max_size
new_height = int((max_size / img_width) * img_height)
else:
new_height = max_size
new_width = int((max_size / img_height) * img_width)
img_input = img_input.resize((new_width, new_height))
# Display the image and let the user draw the mask
stroke_width = st.slider("Brush size", 1, 100, 50)
st.write("**Draw over the parts of the image you want to remove.**")
# Create a drawing canvas for the mask
canvas_result = st_canvas(
stroke_color="rgba(255, 0, 255, 1)", # Pink color for the brush
stroke_width=stroke_width,
background_image=img_input,
update_streamlit=True,
height=img_input.height,
width=img_input.width,
drawing_mode="freedraw",
key="canvas",
)
if canvas_result.image_data is not None:
# Convert the drawing into a mask
mask_image = Image.fromarray((canvas_result.image_data[:, :, 3] > 0).astype(int) * 255)
mask_image = mask_image.resize(img_input.size).convert("L") # Convert to grayscale
# Display the mask for the user to review
st.write("**Generated Mask:**")
st.image(mask_image)
if st.button('Submit'):
with st.spinner("AI is processing..."):
try:
# Convert both image and mask to binary format for API upload
img_buffer = BytesIO()
mask_buffer = BytesIO()
img_input.save(img_buffer, format='PNG')
mask_image.save(mask_buffer, format='PNG')
# Prepare the files for the API
files = [
('image_file', ('image.png', img_buffer.getvalue(), 'image/png')),
('mask_file', ('mask.png', mask_buffer.getvalue(), 'image/png')),
]
headers = {
'accessToken': access_token
}
# Send POST request to MagicEraser API
response = requests.post(url, headers=headers, files=files)
if response.status_code == 200:
# Process and display the result
result_image = Image.open(BytesIO(response.content)).convert("RGB")
st.write("AI has finished the job!")
st.image(result_image)
# Download button for the output image
uploaded_name = uploaded_file.name.split('.')[0]
image_download_button(
pil_image=result_image,
filename=f"{uploaded_name}_output",
fmt="jpg",
label="Download Image"
)
else:
st.error(f"Error: {response.status_code} - {response.text}")
except Exception as e:
st.error(f"Error processing the image: {e}")
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