from PIL import Image
from rembg import new_session, remove
input_path = 'input.png'
output_path = 'output.png'
input = Image.open(input_path)
This defaults to the u2net
model.
output = remove(input)
output.save(output_path)
You can use the new_session
function to create a session with a specific model.
model_name = "isnet-general-use"
session = new_session(model_name)
output = remove(input, session=session)
Alpha metting is a post processing step that can be used to improve the quality of the output.
output = remove(input, alpha_matting=True, alpha_matting_foreground_threshold=270,alpha_matting_background_threshold=20, alpha_matting_erode_size=11)
If you only want the mask, you can use the only_mask
argument.
output = remove(input, only_mask=True)
You can use the post_process_mask
argument to post process the mask to get better results.
output = remove(input, post_process_mask=True)
You can use the bgcolor
argument to replace the background color.
output = remove(input, bgcolor=(255, 255, 255, 255))
You can use the input_points
and input_labels
arguments to specify the points that should be used for the masks. This only works with the sam
model.
import numpy as np
# Define the points and labels
# The points are defined as [y, x]
input_points = np.array([[400, 350], [700, 400], [200, 400]])
input_labels = np.array([1, 1, 2])
image = remove(image,session=session, input_points=input_points, input_labels=input_labels)
output.save(output_path)