![\"\"](\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260119131815-696e2f17629ac.png\")
<\/p>\n\u00a0<\/p>\n
\u4f60\u662f\u5426\u8fd8\u62a0\u56fe\u9700\u8981\u7cbe\u7ec6\u8c03\u6574\u8fb9\u7f18，\u4e00\u5f20\u56fe\u81f3\u5c11\u8017\u65f610\u5206\u949f；\u5728\u7ebf\u62a0\u56fe\u5de5\u5177\u8981\u4e48\u6536\u8d39，\u8981\u4e48\u6709\u6c34\u5370\u9650\u5236\u3002\u4eca\u5929\u7ed9\u5927\u5bb6\u5e26\u6765\u4e00\u6b3eGitHub 19K\u661f\u7684AI\u62a0\u56fe\u795e\u5668\u2014\u2014Rembg！<\/p>\n
Rembg\u7684\u6838\u5fc3\u4f18\u52bf：<\/p>\n
\u2705 \u5b8c\u5168\u514d\u8d39\u5f00\u6e90，\u57fa\u4e8e\u5148\u8fdb\u7684U\u00b2-Net\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b<\/p>\n<\/li>\n
\u2705 \u79bb\u7ebf\u8fd0\u884c，\u4fdd\u62a4\u9690\u79c1\u6570\u636e\u5b89\u5168<\/p>\n<\/li>\n
\u2705 \u4e00\u952e\u53bb\u80cc\u666f，5\u884c\u4ee3\u7801\u641e\u5b9a\u4e13\u4e1a\u62a0\u56fe<\/p>\n<\/li>\n
\u2705 \u652f\u6301\u6279\u91cf\u5904\u7406，\u7535\u5546\u8fd0\u8425\u6548\u7387\u63d0\u534710\u500d<\/p>\n<\/li>\n<\/ul>\n
\u8bdd\u4e0d\u591a\u8bf4，\u9a6c\u4e0a\u5f00\u59cb\u5b9e\u6218！<\/p>\n
\u7cfb\u7edf\u8981\u6c42：<\/p>\n
Python 3.8 \u6216\u66f4\u9ad8\u7248\u672c<\/p>\n<\/li>\n
\u63a8\u8350\u4f7f\u7528\u865a\u62df\u73af\u5883（\u907f\u514d\u4f9d\u8d56\u51b2\u7a81）<\/p>\n<\/li>\n<\/ul>\n
\u5feb\u901f\u68c0\u67e5Python\u7248\u672c：<\/p>\n
python –version
\n# \u8f93\u51fa\u5e94\u663e\u793a：Python 3.8.x \u6216\u66f4\u9ad8<\/p>\n
\u6253\u5f00\u7ec8\u7aef，\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4（\u8d85\u7ea7\u7b80\u5355）：<\/p>\n
# \u57fa\u7840\u7248\u672c（CPU\u8fd0\u884c）
\npip install rembg<\/p>\n
# GPU\u52a0\u901f\u7248\u672c（\u63a8\u8350，\u901f\u5ea6\u5feb3\u500d）
\npip install rembg[gpu]<\/p>\n
\u5b89\u88c5\u65f6\u95f4： \u7ea62-5\u5206\u949f（\u53d6\u51b3\u4e8e\u7f51\u901f）<\/p>\n
\u5e38\u89c1\u95ee\u9898： \u5982\u679c\u9047\u5230\u4e0b\u8f7d\u6162，\u4f7f\u7528\u56fd\u5185\u955c\u50cf\u6e90：<\/p>\n
pip install rembg -i https:\/\/pypi.tuna.tsinghua.edu.cn\/simple<\/p>\n
\u521b\u5efa\u6587\u4ef6 quick_start.py，\u590d\u5236\u4ee5\u4e0b\u4ee3\u7801：<\/p>\n
from rembg import remove
\nfrom PIL import Image<\/p>\n
# \u8bfb\u53d6\u539f\u59cb\u56fe\u7247
\ninput_image = Image.open('input.jpg')<\/p>\n
# AI\u4e00\u952e\u53bb\u80cc\u666f（\u5c31\u8fd9\u4e48\u7b80\u5355！）
\noutput_image = remove(input_image)<\/p>\n
# \u4fdd\u5b58\u4e3aPNG\u900f\u660e\u80cc\u666f\u56fe
\noutput_image.save('output.png')<\/p>\n
print("\u62a0\u56fe\u5b8c\u6210！\u67e5\u770b output.png")<\/p>\n
\u8fd0\u884c\u547d\u4ee4：<\/p>\n
python quick_start.py<\/p>\n
\u6548\u679c\u5bf9\u6bd4：<\/p>\n
\u539f\u56fe：\u666e\u901aJPG，\u5e26\u590d\u6742\u80cc\u666f<\/p>\n<\/li>\n
\u8f93\u51fa：PNG\u900f\u660e\u80cc\u666f，\u4e3b\u4f53\u5b8c\u7f8e\u4fdd\u7559<\/p>\n<\/li>\n<\/ul>\n
\u662f\u4e0d\u662f\u8d85\u7ea7\u7b80\u5355？AI\u81ea\u52a8\u8bc6\u522b\u4e3b\u4f53，\u8fde\u5934\u53d1\u4e1d\u90fd\u80fd\u7cbe\u51c6\u5904\u7406！<\/p>\n
\u7535\u5546\u8fd0\u8425\u5fc5\u5907！\u81ea\u52a8\u5904\u7406\u6574\u4e2a\u6587\u4ef6\u5939\u7684\u5546\u54c1\u56fe：<\/p>\n
import os
\nfrom rembg import remove
\nfrom PIL import Image<\/p>\n
def batch_remove_bg(input_folder, output_folder):
\n """
\n \u6279\u91cf\u62a0\u56fe\u51fd\u6570<\/p>\n
\u53c2\u6570:
\n input_folder: \u539f\u59cb\u56fe\u7247\u6587\u4ef6\u5939\u8def\u5f84
\n output_folder: \u8f93\u51fa\u6587\u4ef6\u5939\u8def\u5f84
\n """
\n # \u521b\u5efa\u8f93\u51fa\u6587\u4ef6\u5939
\n if not os.path.exists(output_folder):
\n os.makedirs(output_folder)<\/p>\n
# \u652f\u6301\u7684\u56fe\u7247\u683c\u5f0f
\n supported_formats = ('.jpg', '.jpeg', '.png', '.bmp')<\/p>\n
# \u904d\u5386\u6240\u6709\u56fe\u7247
\n for filename in os.listdir(input_folder):
\n if filename.lower().endswith(supported_formats):
\n # \u5b8c\u6574\u8def\u5f84
\n input_path = os.path.join(input_folder, filename)
\n output_path = os.path.join(output_folder,
\n f"{os.path.splitext(filename)[0]}.png")<\/p>\n
# \u5904\u7406\u56fe\u7247
\n with Image.open(input_path) as img:
\n output = remove(img)
\n output.save(output_path)
\n print(f"\u5df2\u5904\u7406: {filename}")<\/p>\n
# \u4f7f\u7528\u793a\u4f8b
\nbatch_remove_bg('products', 'products_output')
\nprint("🎉 \u6279\u91cf\u5904\u7406\u5b8c\u6210！")<\/p>\n
\u5b9e\u6d4b\u6548\u679c： 100\u5f20\u56fe\u7247\u7ea65\u5206\u949f\u5904\u7406\u5b8c\u6210（GPU\u6a21\u5f0f）<\/p>\n
\u6709\u65f6\u5019\u9700\u8981\u767d\u8272\u80cc\u666f\u6216\u7eaf\u8272\u80cc\u666f，\u8fd9\u6837\u505a：<\/p>\n
from rembg import remove
\nfrom PIL import Image
\nimport numpy as np<\/p>\n
def add_custom_background(input_path, output_path, bg_color=(255, 255, 255)):
\n """
\n \u6dfb\u52a0\u81ea\u5b9a\u4e49\u80cc\u666f\u8272<\/p>\n
\u53c2\u6570:
\n input_path: \u8f93\u5165\u56fe\u7247\u8def\u5f84
\n output_path: \u8f93\u51fa\u56fe\u7247\u8def\u5f84
\n bg_color: \u80cc\u666f\u989c\u8272RGB\u5143\u7ec4，\u9ed8\u8ba4\u767d\u8272
\n """
\n # \u62a0\u56fe\u5f97\u5230\u900f\u660e\u80cc\u666f
\n with Image.open(input_path) as img:
\n output = remove(img)<\/p>\n
# \u521b\u5efa\u7eaf\u8272\u80cc\u666f
\n background = Image.new('RGB', output.size, bg_color)<\/p>\n
# \u5c06\u62a0\u56fe\u7ed3\u679c\u7c98\u8d34\u5230\u80cc\u666f\u4e0a
\n background.paste(output, (0, 0), output)<\/p>\n
# \u4fdd\u5b58
\n background.save(output_path)
\n print(f"\u5df2\u6dfb\u52a0\u80cc\u666f\u8272: RGB{bg_color}")<\/p>\n
# \u4f7f\u7528\u793a\u4f8b
\nadd_custom_background('input.jpg', 'white_bg.jpg', (255, 255, 255)) # \u767d\u8272\u80cc\u666f
\nadd_custom_background('input.jpg', 'blue_bg.jpg', (0, 120, 255)) # \u84dd\u8272\u80cc\u666f<\/p>\n
Rembg\u652f\u6301\u591a\u79cdAI\u6a21\u578b，\u9488\u5bf9\u4e0d\u540c\u573a\u666f\u4f18\u5316：<\/p>\n
from rembg import remove, new_session<\/p>\n
# \u6a21\u578b\u5bf9\u6bd4\u8868
\nmodels = {
\n 'u2net': '\u901a\u7528\u573a\u666f，\u901f\u5ea6\u5feb',
\n 'u2netp': '\u8f7b\u91cf\u7248，\u79fb\u52a8\u7aef\u53cb\u597d',
\n 'u2net_human_seg': '\u4eba\u50cf\u4e13\u7528，\u7cbe\u5ea6\u66f4\u9ad8',
\n 'isnet-general-use': '2023\u5e74\u65b0\u6a21\u578b，\u8fb9\u7f18\u66f4\u81ea\u7136'
\n}<\/p>\n
def compare_models(input_path):
\n """\u5bf9\u6bd4\u4e0d\u540c\u6a21\u578b\u6548\u679c"""
\n for model_name, description in models.items():
\n print(f"\u6b63\u5728\u4f7f\u7528\u6a21\u578b: {model_name} ({description})")<\/p>\n
# \u521b\u5efa\u6a21\u578b\u4f1a\u8bdd
\n session = new_session(model_name)<\/p>\n
# \u5904\u7406\u56fe\u7247
\n with Image.open(input_path) as img:
\n output = remove(img, session=output_{model_name}.png')<\/p>\n
# \u4f7f\u7528\u793a\u4f8b
\ncompare_models('portrait.jpg')<\/p>\n
\u6a21\u578b\u63a8\u8350：<\/p>\n
\u4eba\u50cf\u62a0\u56fe \u2192 u2net_human_seg<\/p>\n<\/li>\n
\u52a8\u7269\/\u5ba0\u7269 \u2192 u2net<\/p>\n<\/li>\n
\u4ea7\u54c1\u56fe \u2192 isnet-general-use<\/p>\n<\/li>\n<\/ul>\n
\u8ba9\u4e0d\u61c2\u7f16\u7a0b\u7684\u540c\u4e8b\u4e5f\u80fd\u7528\u4e0aAI\u62a0\u56fe！\u5b8c\u6574\u4ee3\u7801\u5982\u4e0b：<\/p>\n
import streamlit as st
\nfrom rembg import remove
\nfrom PIL import Image
\nimport io<\/p>\n
# \u9875\u9762\u914d\u7f6e
\nst.set_page_config(
\n page_title="AI\u62a0\u56fe\u795e\u5668",
\n page_icon="\u2702\ufe0f",
\n layout="wide"
\n)<\/p>\n
# \u6807\u9898
\nst.title("\u2702\ufe0f AI\u667a\u80fd\u62a0\u56fe\u5de5\u5177")
\nst.markdown("### \u57fa\u4e8eRembg\u5f00\u6e90\u9879\u76ee | \u4e00\u952e\u53bb\u9664\u56fe\u7247\u80cc\u666f")<\/p>\n
# \u4fa7\u8fb9\u680f\u914d\u7f6e
\nwith st.sidebar:
\n st.header("\u2699\ufe0f \u8bbe\u7f6e\u9009\u9879")<\/p>\n
# \u80cc\u666f\u989c\u8272\u9009\u62e9
\n bg_option = st.radio(
\n "\u9009\u62e9\u8f93\u51fa\u80cc\u666f",
\n ["\u900f\u660e\u80cc\u666f", "\u767d\u8272\u80cc\u666f", "\u81ea\u5b9a\u4e49\u989c\u8272"]
\n )<\/p>\n
# \u81ea\u5b9a\u4e49\u989c\u8272\u9009\u62e9\u5668
\n if bg_option == "\u81ea\u5b9a\u4e49\u989c\u8272":
\n custom_color = st.color_picker("\u9009\u62e9\u80cc\u666f\u989c\u8272", "#FFFFFF")<\/p>\n
# \u6a21\u578b\u9009\u62e9
\n model_choice = st.selectbox(
\n "\u9009\u62e9AI\u6a21\u578b",
\n ["u2net", "u2net_human_seg", "isnet-general-use"],
\n help="\u4e0d\u540c\u6a21\u578b\u9002\u7528\u4e8e\u4e0d\u540c\u573a\u666f"
\n )<\/p>\n
# \u4e3b\u754c\u9762 – \u6587\u4ef6\u4e0a\u4f20
\nuploaded_file = st.file_uploader(
\n "\u62d6\u62fd\u6216\u70b9\u51fb\u4e0a\u4f20\u56fe\u7247",
\n type=['png', 'jpg', 'jpeg', 'bmp'],
\n help="\u652f\u6301\u5e38\u89c1\u56fe\u7247\u683c\u5f0f"
\n)<\/p>\n
if uploaded_file is not None:
\n # \u521b\u5efa\u4e24\u5217\u5e03\u5c40
\n col1, col2 = st.columns(2)<\/p>\n
# \u663e\u793a\u539f\u56fe
\n with col1:
\n st.subheader("📷 \u539f\u59cb\u56fe\u7247")
\n input_image = Image.open(uploaded_file)
\n st.image(input_image, use_container_width=True)<\/p>\n
# \u5904\u7406\u6309\u94ae
\n if st.button("🚀 \u5f00\u59cb\u62a0\u56fe", type="primary"):
\n with st.spinner("AI\u6b63\u5728\u5904\u7406\u4e2d…"):
\n # \u53bb\u9664\u80cc\u666f
\n output_image = remove(input_image)<\/p>\n
# \u6839\u636e\u9009\u9879\u5904\u7406\u80cc\u666f
\n if bg_option == "\u767d\u8272\u80cc\u666f":
\n background = Image.new('RGB', output_image.size, (255, 255, 255))
\n background.paste(output_image, (0, 0), output_image)
\n output_image = background
\n elif bg_option == "\u81ea\u5b9a\u4e49\u989c\u8272":
\n # \u5c06hex\u8f6cRGB
\n rgb = tuple(int(custom_color.lstrip('#')[i:i+2], 16) for i in (0, 2, 4))
\n background = Image.new('RGB', output_image.size, rgb)
\n background.paste(output_image, (0, 0), output_image)
\n output_image = background<\/p>\n
# \u663e\u793a\u7ed3\u679c
\n with col2:
\n st.subheader("\u2728 \u62a0\u56fe\u7ed3\u679c")
\n st.image(output_image, use_container_width=True)<\/p>\n
# \u4e0b\u8f7d\u6309\u94ae
\n buf = io.BytesIO()
\n output_image.save(buf, format='PNG')<\/p>\n
st.download_button(
\n label="📥 \u4e0b\u8f7d\u7ed3\u679c\u56fe\u7247",
\n data=buf.getvalue(),
\n file_name="rembg_output.png",
\n mime="image\/png"
\n )<\/p>\n
st.success("\u2705 \u5904
\n <div style='text-align: center'>
\n <p>💡 \u6280\u672f\u652f\u6301：Rembg\u5f00\u6e90\u9879\u76ee | \u2b50 GitHub 19K+ Stars<\/p>
\n <\/div>
\n """,
\n unsafe_allow_html=True
\n)<\/p>\n
\u8fd0\u884c\u754c\u9762：<\/p>\n
streamlit run app.py<\/p>\n
\u6d4f\u89c8\u5668\u81ea\u52a8\u6253\u5f00 http:\/\/localhost:8501，\u8d85\u6f02\u4eae\u7684\u754c\u9762！<\/p>\n
\u514d\u8d39\u90e8\u7f72\u5230Streamlit Cloud：<\/p>\n
\u5c06\u4ee3\u7801\u4e0a\u4f20\u5230GitHub\u4ed3\u5e93<\/p>\n<\/li>\n
\u521b\u5efa requirements.txt：<\/p>\n<\/li>\n
rembg==2.0.50
\nstreamlit==1.29.0
\nPillow==10.1.0<\/p>\n
\u8bbf\u95ee streamlit.io\/cloud<\/span> \u767b\u5f55<\/p>\n<\/li>\n \u70b9\u51fb "New app" \u2192 \u9009\u62e9\u4f60\u7684\u4ed3\u5e93 \u2192 Deploy<\/p>\n<\/li>\n 5\u5206\u949f\u540e，\u4f60\u5c31\u6709\u4e86\u4e00\u4e2a\u5728\u7ebfAI\u62a0\u56fe\u7f51\u7ad9！\u00a0<\/p>\n Windows\u7cfb\u7edf：<\/p>\n # \u5b89\u88c5CUDA\u7248\u672c\u7684PyTorch # \u9a8c\u8bc1GPU\u53ef\u7528 \u901f\u5ea6\u5bf9\u6bd4：<\/p>\n CPU\u6a21\u5f0f：1\u5f20\u56fe\u7ea63-5\u79d2<\/p>\n<\/li>\n GPU\u6a21\u5f0f：1\u5f20\u56fe\u7ea60.5-1\u79d2（\u63d0\u53475\u500d！）<\/p>\n<\/li>\n<\/ul>\n \u5904\u7406\u9ad8\u5206\u8fa8\u7387\u56fe\u7247\u65f6，\u907f\u514d\u5185\u5b58\u6ea2\u51fa：<\/p>\n from rembg import remove def process_large_image(input_path, output_path, max_size=2000): \u53c2\u6570: # \u5982\u679c\u56fe\u7247\u8fc7\u5927，\u5148\u7f29\u653e # \u62a0\u56fe # \u4f7f\u7528\u793a\u4f8b \u95ee\u98981：\u6a21\u578b\u4e0b\u8f7d\u5931\u8d25<\/p>\n # \u75c7\u72b6：ModuleNotFoundError \u6216\u4e0b\u8f7d\u8d85\u65f6<\/p>\n # \u89e3\u51b3\u65b9\u6848：\u624b\u52a8\u6307\u5b9a\u6a21\u578b\u7f13\u5b58\u8def\u5f84 \u95ee\u98982：CUDA out of memory<\/p>\n # \u75c7\u72b6：RuntimeError: CUDA out of memory<\/p>\n # \u89e3\u51b3\u65b9\u6848：\u964d\u4f4e\u56fe\u7247\u5206\u8fa8\u7387\u6216\u5207\u6362CPU\u6a21\u5f0f \u95ee\u98983：\u900f\u660e\u901a\u9053\u4e22\u5931<\/p>\n # \u786e\u4fdd\u4fdd\u5b58\u4e3aPNG\u683c\u5f0f # \u81ea\u52a8\u5904\u7406\u5e97\u94fa\u6240\u6709\u5546\u54c1\u56fe # \u4eba\u50cf\u62a0\u56fe + \u6dfb\u52a0\u8bc1\u4ef6\u7167\u80cc\u666f # \u4ece\u590d\u6742\u80cc\u666f\u63d0\u53d6Logo\/\u56fe\u6807 Rembg\u6838\u5fc3\u4f18\u52bf\u56de\u987e：<\/p>\n \u96f6\u95e8\u69db：5\u884c\u4ee3\u7801\u5b8c\u6210\u4e13\u4e1a\u62a0\u56fe<\/p>\n<\/li>\n \u5b8c\u5168\u514d\u8d39：\u5f00\u6e90\u65e0\u9650\u5236\u4f7f\u7528<\/p>\n<\/li>\n \u7cbe\u51c6\u9ad8\u6548：AI\u6a21\u578b\u8bc6\u522b\u51c6\u786e\u738795%+<\/p>\n<\/li>\n \u6269\u5c55\u6027\u5f3a：\u652f\u6301\u6279\u91cf\u3001Web\u754c\u9762\u3001API\u96c6\u6210<\/p>\n<\/li>\n<\/ul>\n \u9002\u7528\u4eba\u7fa4：<\/p>\n \u7535\u5546\u8fd0\u8425：\u6279\u91cf\u5904\u7406\u5546\u54c1\u56fe<\/p>\n<\/li>\n \u5e73\u9762\u8bbe\u8ba1\u5e08：\u5feb\u901f\u63d0\u53d6\u7d20\u6750<\/p>\n<\/li>\n \u81ea\u5a92\u4f53\u521b\u4f5c\u8005：\u5236\u4f5c\u5c01\u9762\u56fe<\/p>\n<\/li>\n \u5f00\u53d1\u8005：\u96c6\u6210\u5230\u81ea\u5df1\u7684\u5e94\u7528<\/p>\n<\/li>\n<\/ul>\n \u5982\u679c\u8fd9\u7bc7\u6559\u7a0b\u5e2e\u5230\u4e86\u4f60，\u522b\u5fd8\u4e86\u70b9\u8d5e👍\u6536\u85cf\u2b50\u4e09\u8fde\u652f\u6301！\u6709\u95ee\u9898\u6b22\u8fce\u8bc4\u8bba\u533a\u4ea4\u6d41，\u6211\u4f1a\u7b2c\u4e00\u65f6\u95f4\u56de\u590d\u3002<\/p>\n \u76f8\u5173\u94fe\u63a5：<\/p>\n Rembg GitHub：https:\/\/github.com\/danielgatis\/rembg<\/span><\/p>\n<\/li>\n Streamlit\u5b98\u65b9\u6587\u6863：https:\/\/docs.streamlit.io<\/span><\/p>\n<\/li>\n<\/ul>\n \u672c\u6587\u539f\u521b\u9996\u53d1\u4e8eCSDN，\u8f6c\u8f7d\u8bf7\u6ce8\u660e\u51fa\u5904 | \u6700\u540e\u66f4\u65b0：2026\u5e741\u6708<\/p>\n","protected":false},"excerpt":{"rendered":" \u544a\u522bPS\u62a0\u56fe\u5669\u68a6
\n\u7b2c\u56db\u90e8\u5206：\u6027\u80fd\u4f18\u5316\u4e0e\u8e29\u5751\u6307\u5357<\/h3>\n
4.1 GPU\u52a0\u901f\u914d\u7f6e<\/h4>\n
\npip install torch torchvision –index-url https:\/\/download.pytorch.org\/whl\/cu118<\/p>\n
\npython -c "import torch; print(torch.cuda.is_available())"<\/p>\n\n
4.2 \u5927\u56fe\u5904\u7406\u5185\u5b58\u4f18\u5316<\/h4>\n
\nfrom PIL import Image<\/p>\n
\n """
\n \u5904\u7406\u5927\u5c3a\u5bf8\u56fe\u7247<\/p>\n
\n max_size: \u6700\u5927\u8fb9\u957f\u9650\u5236（\u50cf\u7d20）
\n """
\n with Image.open(input_path) as img:
\n # \u83b7\u53d6\u539f\u59cb\u5c3a\u5bf8
\n width, height = img.size<\/p>\n
\n if max(width, height) > max_size:
\n ratio = max_size \/ max(width, height)
\n new_size = (int(width * ratio), int(height * ratio))
\n img = img.resize(new_size, Image.Resampling.LANCZOS)
\n print(f"\u56fe\u7247\u5df2\u7f29\u653e\u81f3: {new_size}")<\/p>\n
\n output = remove(img)
\n output.save(output_path)
\n print("\u5904\u7406\u5b8c\u6210！")<\/p>\n
\nprocess_large_image('huge_photo.jpg', 'output.png')<\/p>\n4.3 \u5e38\u89c1\u62a5\u9519\u89e3\u51b3\u65b9\u6848<\/h4>\n
\nimport os
\nos.environ['U2NET_HOME'] = '.\/models' # \u81ea\u5b9a\u4e49\u6a21\u578b\u5b58\u653e\u4f4d\u7f6e<\/p>\n
\nimport torch
\ntorch.cuda.empty_cache() # \u6e05\u7a7aGPU\u7f13\u5b58<\/p>\n
\noutput.save('result.png', 'PNG') # \u660e\u786e\u6307\u5b9a\u683c\u5f0f<\/p>\n
\n\u5b9e\u6218\u5e94\u7528\u573a\u666f<\/h3>\n
\u573a\u666f1：\u7535\u5546\u4ea7\u54c1\u56fe\u6279\u91cf\u5904\u7406<\/h4>\n
\nbatch_remove_bg('products', 'products_clean')
\n# \u7ed3\u679c：\u7edf\u4e00\u767d\u5e95\u56fe，\u4e0a\u67b6\u901f\u5ea6\u63d0\u534710\u500d<\/p>\n\u573a\u666f2：\u8bc1\u4ef6\u7167\u5feb\u901f\u5236\u4f5c<\/h4>\n
\nadd_custom_background('portrait.jpg', 'id_photo.jpg', (0, 120, 215)) # \u84dd\u8272\u80cc\u666f<\/p>\n\u573a\u666f3：\u8bbe\u8ba1\u7d20\u6750\u63d0\u53d6<\/h4>\n
\nremove(Image.open('screenshot.png')).save('logo.png')<\/p>\n
\n\u603b\u7ed3\u4e0e\u5c55\u671b<\/h3>\n
\n
\n
\n💬\u7ed3\u8bed<\/h3>\n
\n\n
\n
\n\u4f60\u662f\u5426\u8fd8\u62a0\u56fe\u9700\u8981\u7cbe\u7ec6\u8c03\u6574\u8fb9\u7f18，\u4e00\u5f20\u56fe\u81f3\u5c11\u8017\u65f610\u5206\u949f；\u5728\u7ebf\u62a0\u56fe\u5de5\u5177\u8981\u4e48\u6536\u8d39，\u8981\u4e48\u6709\u6c34\u5370\u9650\u5236\u3002\u4eca\u5929\u7ed9\u5927\u5bb6\u5e26\u6765\u4e00\u6b3eGitHub 19K\u661f\u7684AI\u62a0\u56fe\u795e\u5668\u2014\u2014Rembg！
\nRembg\u7684\u6838\u5fc3\u4f18\u52bf： \u2705 \u5b8c\u5168\u514d\u8d39\u5f00\u6e90，\u57fa\u4e8e\u5148\u8fdb\u7684U\u00b2-Net\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b \u2705 \u79bb\u7ebf\u8fd0\u884c，\u4fdd\u62a4\u9690\u79c1\u6570\u636e\u5b89\u5168 \u2705 \u4e00\u952e\u53bb\u80cc\u666f，5\u884c\u4ee3\u7801\u641e\u5b9a\u4e13\u4e1a\u62a0\u56fe \u2705 \u652f\u6301\u6279\u91cf\u5904\u7406࿰<\/p>\n","protected":false},"author":2,"featured_media":62333,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[50],"topic":[],"class_list":["post-62334","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server","tag-50"],"yoast_head":"\n