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Remove backgrounds from images using segmentation. Support for color-based, edge detection, and AI-assisted removal methods. Batch processing available.
npx skill4agent add dkyazzentwatwa/chatgpt-skills background-removerfrom background_remover import BackgroundRemover
remover = BackgroundRemover()
# Simple removal
remover.load("photo.jpg")
remover.remove_background()
remover.save("photo_transparent.png")
# Remove specific color
remover.load("product.jpg")
remover.remove_color((255, 255, 255), tolerance=30) # Remove white
remover.save("product_clean.png")
# Replace background
remover.load("portrait.jpg")
remover.remove_background()
remover.replace_background(color=(0, 120, 255)) # Blue background
remover.save("portrait_blue.png")# Remove background (auto-detect)
python background_remover.py --input photo.jpg --output result.png
# Remove specific color
python background_remover.py --input image.jpg --color "255,255,255" --tolerance 30 -o clean.png
# Use GrabCut method
python background_remover.py --input photo.jpg --method grabcut -o result.png
# Replace background with color
python background_remover.py --input photo.jpg --replace-color "0,120,255" -o result.png
# Replace background with image
python background_remover.py --input photo.jpg --replace-image bg.jpg -o result.png
# Batch process
python background_remover.py --batch input_folder/ --output-dir output/ --method edgeclass BackgroundRemover:
def __init__(self)
# Loading
def load(self, filepath: str) -> 'BackgroundRemover'
def load_array(self, array: np.ndarray) -> 'BackgroundRemover'
# Removal Methods
def remove_background(self, method: str = "auto") -> 'BackgroundRemover'
def remove_color(self, color: Tuple, tolerance: int = 20) -> 'BackgroundRemover'
def remove_edges(self, threshold: int = 50) -> 'BackgroundRemover'
def grabcut(self, rect: Tuple = None, iterations: int = 5) -> 'BackgroundRemover'
# Background Operations
def replace_background(self, color: Tuple = None, image: str = None) -> 'BackgroundRemover'
def add_shadow(self, offset: Tuple = (5, 5), blur: int = 10) -> 'BackgroundRemover'
# Refinement
def refine_edges(self, feather: int = 2) -> 'BackgroundRemover'
def expand_mask(self, pixels: int = 2) -> 'BackgroundRemover'
def contract_mask(self, pixels: int = 2) -> 'BackgroundRemover'
# Output
def save(self, filepath: str, quality: int = 95) -> str
def get_image(self) -> Image
def get_mask(self) -> Image
# Batch Processing
def batch_process(self, input_dir: str, output_dir: str,
method: str = "auto") -> List[str]# Automatically choose best method
remover.remove_background(method="auto")# Remove white background
remover.remove_color((255, 255, 255), tolerance=30)
# Remove green screen
remover.remove_color((0, 255, 0), tolerance=50)
# Remove any solid color
remover.remove_color((200, 200, 200), tolerance=40)# Use edge detection to find subject
remover.remove_edges(threshold=50)# Full image GrabCut
remover.grabcut(iterations=5)
# With bounding rectangle hint
remover.grabcut(rect=(50, 50, 400, 300), iterations=10)remover.remove_background()
remover.replace_background(color=(255, 255, 255)) # White
remover.replace_background(color=(0, 0, 0)) # Black
remover.replace_background(color=(135, 206, 235)) # Sky blueremover.remove_background()
remover.replace_background(image="office_bg.jpg")remover.remove_background()
remover.save("transparent.png") # PNG preserves alpha# Soften edges with feathering
remover.refine_edges(feather=3)
# Expand mask to include more area
remover.expand_mask(pixels=2)
# Contract mask for tighter crop
remover.contract_mask(pixels=2)remover = BackgroundRemover()
# Remove white studio background
remover.load("product_photo.jpg")
remover.remove_color((255, 255, 255), tolerance=25)
remover.refine_edges(feather=2)
remover.save("product_transparent.png")remover = BackgroundRemover()
# Remove background from portrait
remover.load("portrait.jpg")
remover.grabcut(iterations=8)
remover.refine_edges(feather=3)
# Add professional background
remover.replace_background(color=(220, 220, 220))
remover.add_shadow(offset=(5, 5), blur=15)
remover.save("portrait_professional.jpg")remover = BackgroundRemover()
remover.load("greenscreen_video_frame.jpg")
remover.remove_color((0, 255, 0), tolerance=60)
remover.replace_background(image="virtual_bg.jpg")
remover.save("composited.jpg")remover = BackgroundRemover()
processed = remover.batch_process(
input_dir="product_photos/",
output_dir="processed/",
method="color",
color=(255, 255, 255),
tolerance=30
)
print(f"Processed {len(processed)} images")remove_color()grabcut()