Remove Background Competitors Benchmark (Remove.bg, Clipdrop, SAM, Azure)

Original Image

Photoroom API (response time: ~450 milliseconds)

Remove.bg API (response time: ~600 milliseconds)

Clipdrop API (response time: ~2 seconds, doesn't support cropping to the bounds of the subject)

Segment Anything Model (SAM) (response time: depends on the machine running the model)

Azure Background Removal API (response time: ~2 seconds)

Original Image

Photoroom API (response time: ~450 milliseconds)

Remove.bg API (response time: ~600 milliseconds)

Clipdrop API (response time: ~2 seconds, doesn't support cropping to the bounds of the subject)

Segment Anything Model (SAM) (response time: depends on the machine running the model)

Azure Background Removal API (response time: ~2 seconds)

Original Image

Photoroom API (response time: ~450 milliseconds)

Remove.bg API (response time: ~600 milliseconds)

Clipdrop API (response time: ~2 seconds, doesn't support cropping to the bounds of the subject)

Segment Anything Model (SAM) (response time: depends on the machine running the model)

Azure Background Removal API (response time: ~2 seconds)

Original Image

Photoroom API (response time: ~450 milliseconds)

Remove.bg API (response time: ~600 milliseconds)

Clipdrop API (response time: ~2 seconds, doesn't support cropping to the bounds of the subject)

Segment Anything Model (SAM) (response time: depends on the machine running the model)

Azure Background Removal API (response time: ~2 seconds)

Original Image

Photoroom API (response time: ~450 milliseconds)

Remove.bg API (response time: ~600 milliseconds)

Clipdrop API (response time: ~2 seconds, doesn't support cropping to the bounds of the subject)

Segment Anything Model (SAM) (response time: depends on the machine running the model)

Azure Background Removal API (response time: ~2 seconds)

Original Image

Photoroom API (response time: ~450 milliseconds)

Remove.bg API (response time: ~600 milliseconds)

Clipdrop API (response time: ~2 seconds, doesn't support cropping to the bounds of the subject)

Segment Anything Model (SAM) (response time: depends on the machine running the model)

Azure Background Removal API (response time: ~2 seconds)

Original Image

Photoroom API (response time: ~450 milliseconds)

Remove.bg API (response time: ~600 milliseconds)

Clipdrop API (response time: ~2 seconds, doesn't support cropping to the bounds of the subject)

Segment Anything Model (SAM) (response time: depends on the machine running the model)

Azure Background Removal API (response time: ~2 seconds)

Original Image

Photoroom API (response time: ~450 milliseconds)

Remove.bg API (response time: ~600 milliseconds)

Clipdrop API (response time: ~2 seconds, doesn't support cropping to the bounds of the subject)

Segment Anything Model (SAM) (response time: depends on the machine running the model)

Azure Background Removal API (response time: ~2 seconds)

Before running this code, please download the original images that you want to re-process, and place them in a directory called original-images.

import os
import requests
import concurrent.futures

API_KEY = "YOUR_PHOTOROOM_API_KEY"

def process_image(input_image_path, output_image_path):
    try:
        url = "https://sdk.photoroom.com/v1/segment"

        with open(input_image_path, 'rb') as image_file:
            files = { "image_file": image_file }

            headers = {
                "Accept": "image/png, application/json",
                "pr-background-removal-model-version": "2024-09-26",
                "x-api-key": API_KEY
            }

            response = requests.post(url, files=files, headers=headers)
            response.raise_for_status()

            with open(output_image_path, 'wb') as f:
                f.write(response.content)
                print(f"Image downloaded and saved to {output_image_path}")

    except requests.RequestException as e:
        print(f"Error: {str(e)} ({input_image_path})")
        return str(e)
    
def iterate_over_directory(directory_path, result_directory):
    with concurrent.futures.ThreadPoolExecutor(max_workers=16) as executor:
        for root, _, files in os.walk(directory_path):
            for file in files:
                if file.lower().endswith(('.png', '.jpg', '.jpeg', '.webp', '.heic')):
                    file_path = os.path.join(root, file)

                    result_file_name = os.path.splitext(os.path.basename(file_path))[0] + '.png'
                    result_file_directory = os.path.join(result_directory, os.path.basename(root))

                    if not os.path.exists(result_file_directory):
                        os.makedirs(result_file_directory)

                    result_path = os.path.join(result_file_directory, result_file_name)

                    if not os.path.exists(result_path): # don't re-process images 
                        executor.submit(process_image, file_path, result_path)    

if __name__ == "__main__":
    INPUT_DIRECTORY = "./original-images/"
    OUTPUT_DIRECTORY = "./result-photoroom/"

    if not os.path.exists(OUTPUT_DIRECTORY):
        os.makedirs(OUTPUT_DIRECTORY)

    iterate_over_directory(directory_path=INPUT_DIRECTORY, result_directory=OUTPUT_DIRECTORY)

Before running this code, please download the original images that you want to re-process, and place them in a directory called original-images.

import os
import requests

API_KEY = "YOUR_REMOVE_BG_API_KEY"

def process_image(input_image_path, output_image_path):
    try:
        url = "https://api.remove.bg/v1.0/removebg"

        with open(input_image_path, 'rb') as image_file:
            files = { "image_file": image_file }

            payload = {
                "size": "auto"
            }
            headers = {
                "Accept": "image/png, application/json",
                "x-api-key": API_KEY
            }

            response = requests.post(url, data=payload, files=files, headers=headers)
            response.raise_for_status()

            with open(output_image_path, 'wb') as f:
                f.write(response.content)
                print(f"Image downloaded and saved to {output_image_path}")

    except requests.RequestException as e:
        print(f"Error: {str(e)} ({input_image_path})")
        return str(e)
    
def iterate_over_directory(directory_path, result_directory):
    for root, _, files in os.walk(directory_path):
        for file in files:
            if file.lower().endswith(('.png', '.jpg', '.jpeg', '.webp', '.heic')):
                file_path = os.path.join(root, file)

                result_file_name = os.path.splitext(os.path.basename(file_path))[0] + '.png'
                result_file_directory = os.path.join(result_directory, os.path.basename(root))

                if not os.path.exists(result_file_directory):
                    os.makedirs(result_file_directory)

                result_path = os.path.join(result_file_directory, result_file_name)

                if not os.path.exists(result_path): # don't re-process images 
                    process_image(file_path, result_path)    

if __name__ == "__main__":
    INPUT_DIRECTORY = "./original-images/"
    OUTPUT_DIRECTORY = "./result-remove-bg/"

    if not os.path.exists(OUTPUT_DIRECTORY):
        os.makedirs(OUTPUT_DIRECTORY)

    iterate_over_directory(directory_path=INPUT_DIRECTORY, result_directory=OUTPUT_DIRECTORY)

Before running this code, please download the original images that you want to re-process, and place them in a directory called original-images.

import os
import requests

API_KEY = "YOUR_CLIPDROP_API_KEY"

def process_image(input_image_path, output_image_path):
    try:
        url = "https://clipdrop-api.co/remove-background/v1"

        with open(input_image_path, 'rb') as image_file:
            files = { "image_file": image_file }

            payload = {
                "transparency_handling": "discard_alpha_layer"
            }
            headers = {
                "Accept": "image/png",
                "x-api-key": API_KEY
            }

            response = requests.post(url, data=payload, files=files, headers=headers)
            response.raise_for_status()

            with open(output_image_path, 'wb') as f:
                f.write(response.content)
                print(f"Image downloaded and saved to {output_image_path}")

    except requests.RequestException as e:
        print(f"Error: {str(e)} ({input_image_path})")
        return str(e)
    
def iterate_over_directory(directory_path, result_directory):
    for root, _, files in os.walk(directory_path):
        for file in files:
            if file.lower().endswith(('.png', '.jpg', '.jpeg', '.webp', '.heic')):
                file_path = os.path.join(root, file)

                result_file_name = os.path.splitext(os.path.basename(file_path))[0] + '.png'
                result_file_directory = os.path.join(result_directory, os.path.basename(root))

                if not os.path.exists(result_file_directory):
                    os.makedirs(result_file_directory)

                result_path = os.path.join(result_file_directory, result_file_name)

                if not os.path.exists(result_path): # don't re-process images 
                    process_image(file_path, result_path)    

if __name__ == "__main__":
    INPUT_DIRECTORY = "./original-images/"
    OUTPUT_DIRECTORY = "./result-clipdrop/"

    if not os.path.exists(OUTPUT_DIRECTORY):
        os.makedirs(OUTPUT_DIRECTORY)

    iterate_over_directory(directory_path=INPUT_DIRECTORY, result_directory=OUTPUT_DIRECTORY)

Before running this code please:

download the original images that you want to re-process, and place them in a directory called original-images
run the command: pip install pillow rembg

from PIL import Image
from rembg import new_session, remove
import os

MODEL_NAME = "sam"
SESSION = new_session(MODEL_NAME)

def process_image(input_image_path, output_image_path):
    input = Image.open(input_image_path)
    output = remove(input)
    output.save(output_image_path)
    print(f"Image saved to {output_image_path}")
    
def iterate_over_directory(directory_path, result_directory):
    for root, _, files in os.walk(directory_path):
        for file in files:
            if file.lower().endswith(('.png', '.jpg', '.jpeg', '.webp', '.heic')):
                file_path = os.path.join(root, file)

                result_file_name = os.path.splitext(os.path.basename(file_path))[0] + '-sam.png'
                result_file_directory = os.path.join(result_directory, os.path.basename(root))

                if not os.path.exists(result_file_directory):
                    os.makedirs(result_file_directory)

                result_path = os.path.join(result_file_directory, result_file_name)

                if not os.path.exists(result_path): # don't re-process images 
                    process_image(file_path, result_path)

if __name__ == "__main__":
    INPUT_DIRECTORY = "./original-images/"
    OUTPUT_DIRECTORY = "./result-sam/"

    if not os.path.exists(OUTPUT_DIRECTORY):
        os.makedirs(OUTPUT_DIRECTORY)

    iterate_over_directory(directory_path=INPUT_DIRECTORY, result_directory=OUTPUT_DIRECTORY)

Before running this code, please download the original images that you want to re-process, and place them in a directory called original-images.

import os
import requests

API_ENDPOINT = "YOUR_AZURE_ENDPOINT"
API_KEY = "YOUR_AZURE_API_KEY"

def process_image(input_image_path, output_image_path):
    try:
        url = API_ENDPOINT + "computervision/imageanalysis:segment?api-version=2023-02-01-preview&mode=backgroundRemoval"

        with open(input_image_path, 'rb') as image_file:
            headers = {
                "Content-Type": "application/octet-stream",
                "Ocp-Apim-Subscription-Key": API_KEY
            }

            response = requests.post(url, data=image_file, headers=headers)
            response.raise_for_status()

            with open(output_image_path, 'wb') as f:
                f.write(response.content)
                print(f"Image downloaded and saved to {output_image_path}")

    except requests.RequestException as e:
        print(f"Error: {str(e)} ({input_image_path})")
        return str(e)
    
def iterate_over_directory(directory_path, result_directory):
    for root, _, files in os.walk(directory_path):
        for file in files:
            if file.lower().endswith(('.png', '.jpg', '.jpeg', '.webp', '.heic')):
                file_path = os.path.join(root, file)

                result_file_name = os.path.splitext(os.path.basename(file_path))[0] + '-azure.png'
                result_file_directory = os.path.join(result_directory, os.path.basename(root))

                if not os.path.exists(result_file_directory):
                    os.makedirs(result_file_directory)

                result_path = os.path.join(result_file_directory, result_file_name)

                if not os.path.exists(result_path): # don't re-process images 
                    process_image(file_path, result_path)    

if __name__ == "__main__":
    INPUT_DIRECTORY = "./original-images/"
    OUTPUT_DIRECTORY = "./result-azure/"

    if not os.path.exists(OUTPUT_DIRECTORY):
        os.makedirs(OUTPUT_DIRECTORY)

    iterate_over_directory(directory_path=INPUT_DIRECTORY, result_directory=OUTPUT_DIRECTORY)

Remove Background Competitors Benchmark (Remove.bg, Clipdrop, SAM, Azure)

Result Comparison

Home Decoration Images

Furniture Images

Apparel Images

Food Images

Cosmetic Images

Jewelry Images

People Images

Industry Images

Reproducing the results