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Aspose.Imaging  Python
ICO

使用 Python 进行 ICO 图像背景删除

创建 Python 应用程序以通过服务器 API 删除 ICO 图像和照片的背景

如何使用 Python 删除 ICO 图像和照片的背景

要从图像或照片中去除背景,需要精确识别突出的物体。对于ICO图像,有多种方法可用于对象定义。在简单的场景中,自动化方法可以有效地处理具有统一背景的图像。然而,在处理具有多个人物或物体与背景融合的照片时,建议进行初步的物体指定。这需要手动勾画矩形区域并指定要突出显示的对象类型。在更复杂的自动对象分配情况下,云 API 可以作为替代方案。这款基于云的应用程序可识别照片中的对象,并利用生成的轮廓来消除背景。背景去除后,增强剩余物体的边缘可以显着提高整体图像质量。要删除 ICO 文件中的背景,建议使用 Aspose.Imaging for Python via .NET API 是一个功能丰富、功能强大且易于使用的图像处理和转换 API,适用于 Python 平台。您可以使用系统命令中的以下命令安装它。

系统命令行

>> pip install aspose-imaging-python-net

通过 Python 从 ICO 中删除背景的步骤

您需要 aspose-imaging-python-net 在您自己的环境中尝试以下工作流程。

  • 使用 Image.Load 方法加载 ICO 文件
  • 移除背景;
  • 以 Aspose.Imaging 支持的格式将图像保存到光盘

系统要求

所有主要操作系统都支持 Python 的 Aspose.Imaging。只需确保您具有以下先决条件。

  • 带有 .NET Core 运行时的 Microsoft Windows / Linux。
  • Python 和 PyPi 包管理器。
 

删除 ICO 图像中的背景 - Python

from aspose.imaging import Image, RasterImage, Point, Rectangle, Color
from aspose.imaging.fileformats.png import PngColorType
from aspose.imaging.imageoptions import PngOptions
from aspose.imaging.masking import *
from aspose.imaging.masking.options import *
from aspose.imaging.masking.result import *
from aspose.imaging.sources import FileCreateSource
from aspose.pycore import as_of
import os
if 'TEMPLATE_DIR' in os.environ:
templates_folder = os.environ['TEMPLATE_DIR']
else:
templates_folder = r"C:\Users\USER\Downloads\templates"
delete_output = 'SAVE_OUTPUT' not in os.environ
def remove_background_processing_with_manual_rectangles():
raster_formats = [
"jpg",
"png",
"bmp",
"apng",
"dicom",
"jp2",
"j2k",
"tga",
"webp",
"tif",
"gif",
"ico"
]
vector_formats = [
"svg",
"otg",
"odg",
"wmf",
"emf",
"wmz",
"emz",
"cmx",
"cdr"
]
all_formats: list = []
all_formats.extend(raster_formats)
all_formats.extend(vector_formats)
for format_ext in all_formats:
input_file = os.path.join(templates_folder, f"couple.{format_ext}")
if not os.path.exists(input_file):
continue
is_vector_format = format_ext in vector_formats
# Need to rasterize vector formats before background remove
if is_vector_format:
input_file = rasterize_vector_image(format_ext, input_file)
output_file = os.path.join(templates_folder, f"remove_background_manual_rectangles.{format_ext}.png")
print(f"Processing {format_ext}")
with as_of(Image.load(input_file), RasterImage) as image:
obj_init3 = AutoMaskingArgs()
obj_init3.objects_rectangles = [Rectangle(87, 47, 123, 308), Rectangle(180, 24, 126, 224)]
obj_init4 = PngOptions()
obj_init4.color_type = PngColorType.TRUECOLOR_WITH_ALPHA
obj_init4.source = FileCreateSource(output_file, False)
obj_init5 = AutoMaskingGraphCutOptions()
obj_init5.feathering_radius = 2
obj_init5.method = SegmentationMethod.GRAPH_CUT
obj_init5.args = obj_init3
obj_init5.export_options = obj_init4
masking_options = obj_init5
with ImageMasking(image).create_session(masking_options) as masking_session:
# first run of segmentation
with masking_session.decompose() as _:
pass
args_with_user_markers = AutoMaskingArgs()
obj_init_list = [
# background markers
None,
# foreground markers
UserMarker()
# boy's head
.add_point(218, 48, 10)
# girl's head
.add_point(399, 66, 10)
# girs's body
.add_point(158, 141, 10)
.add_point(158, 209, 20)
.add_point(115, 225, 5)
.get_points()]
args_with_user_markers.objects_points = obj_init_list
with masking_session.improve_decomposition(args_with_user_markers) as masking_result:
with masking_result[1].get_image() as result_image:
result_image.save()
if delete_output:
os.remove(output_file)
# Remove rasterized vector image
if is_vector_format and delete_output:
os.remove(input_file)
def remove_background_auto_processing_with_assumed_objects():
raster_formats = [
"jpg",
"png",
"bmp",
"apng",
"dicom",
"jp2",
"j2k",
"tga",
"webp",
"tif",
"gif"]
vector_formats = [
"svg",
"otg",
"odg",
"eps",
"wmf",
"emf",
"wmz",
"emz",
"cmx",
"cdr"]
all_formats = []
all_formats.extend(raster_formats)
all_formats.extend(vector_formats)
for format_ext in all_formats:
input_file = os.path.join(templates_folder, f"couple.{format_ext}")
if not os.path.exists(input_file):
continue
is_vector_format = format_ext in vector_formats
# Need to rasterize vector formats before background remove
if is_vector_format:
input_file = rasterize_vector_image(format_ext, input_file)
output_file = os.path.join(templates_folder,
f"remove_background_auto_assumed_objects.{format_ext}.png")
print(f"Processing {format_ext}")
with as_of(Image.load(input_file), RasterImage) as image:
obj_init9 = list()
obj_init9.append(AssumedObjectData(DetectedObjectType.HUMAN, Rectangle(87, 47, 123, 308)))
obj_init9.append(AssumedObjectData(DetectedObjectType.HUMAN, Rectangle(180, 24, 126, 224)))
obj_init10 = PngOptions()
obj_init10.color_type = PngColorType.TRUECOLOR_WITH_ALPHA
obj_init10.source = FileCreateSource(output_file, False)
obj_init11 = AutoMaskingGraphCutOptions()
obj_init11.assumed_objects = obj_init9
obj_init11.calculate_default_strokes = True
obj_init11.feathering_radius = 1
obj_init11.method = SegmentationMethod.GRAPH_CUT
obj_init11.export_options = obj_init10
obj_init11.background_replacement_color = Color.green
masking_options = obj_init11
with ImageMasking(image).decompose(masking_options) as masking_result:
with masking_result[1].get_image() as result_image:
result_image.save()
# Remove rasterized vector image
if is_vector_format and delete_output:
os.remove(input_file)
if delete_output:
os.remove(output_file)
def remove_background_auto_processing():
raster_formats = [
"jpg",
"png",
"bmp",
"apng",
"dicom",
"jp2",
"j2k",
"tga",
"webp",
"tif",
"gif"]
vector_formats = [
"svg",
"otg",
"odg",
"eps",
"wmf",
"emf",
"wmz",
"emz",
"cmx",
"cdr"]
all_formats: list = []
all_formats.extend(raster_formats)
all_formats.extend(vector_formats)
for format_ext in all_formats:
input_file = os.path.join(templates_folder, f"couple.{format_ext}")
if not os.path.exists(input_file):
continue
is_vector_format = format_ext in vector_formats
# Need to rasterize vector formats before background remove
if is_vector_format:
input_file = rasterize_vector_image(format_ext, input_file)
output_file = os.path.join(templates_folder, f"remove_background_auto.{format_ext}.png")
print(f"Processing {format_ext}")
with as_of(Image.load(input_file), RasterImage) as image:
obj_init14 = PngOptions()
obj_init14.color_type = PngColorType.TRUECOLOR_WITH_ALPHA
obj_init14.source = FileCreateSource(output_file, False)
obj_init15 = AutoMaskingGraphCutOptions()
obj_init15.feathering_radius = 1
obj_init15.method = SegmentationMethod.GRAPH_CUT
obj_init15.export_options = obj_init14
obj_init15.background_replacement_color = Color.green
masking_options = obj_init15
with ImageMasking(image).decompose(masking_options) as masking_result:
with masking_result[1].get_image() as result_image:
result_image.save()
# Remove rasterized vector image
if is_vector_format and delete_output:
os.remove(input_file)
if delete_output:
os.remove(output_file)
def remove_background_generic_example():
raster_formats = [
"jpg",
"png",
"bmp",
"apng",
"dicom",
"jp2",
"j2k",
"tga",
"webp",
"tif",
"gif"]
vector_formats = [
"svg",
"otg",
"odg",
"wmf",
"emf",
"wmz",
"emz",
"cmx",
"cdr"]
all_formats: list = []
all_formats.extend(raster_formats)
all_formats.extend(vector_formats)
for format_ext in all_formats:
input_file = os.path.join(templates_folder, f"couple.{format_ext}")
if not os.path.exists(input_file):
continue
is_vector_format: bool = format_ext in vector_formats
# Need to rasterize vector formats before background remove
if is_vector_format:
input_file = rasterize_vector_image(format_ext, input_file)
output_file = os.path.join(templates_folder, f"remove_background.{format_ext}.png")
print(f"Processing {format_ext}")
with as_of(Image.load(input_file), RasterImage) as image:
obj_init18 = PngOptions()
obj_init18.color_type = PngColorType.TRUECOLOR_WITH_ALPHA
obj_init18.source = FileCreateSource(output_file, False)
obj_init19 = AutoMaskingGraphCutOptions()
obj_init19.calculate_default_strokes = True
obj_init19.feathering_radius = 1
obj_init19.method = SegmentationMethod.GRAPH_CUT
obj_init19.export_options = obj_init18
obj_init19.background_replacement_color = Color.green
masking_options = obj_init19
with ImageMasking(image).decompose(masking_options) as masking_result:
with masking_result[1].get_image() as result_image:
result_image.save()
# Remove rasterized vector image
if is_vector_format and delete_output:
os.remove(input_file)
if delete_output:
os.remove(output_file)
def rasterize_vector_image(format_ext, input_file):
output_file: str = os.path.join(templates_folder, f"rasterized.{format_ext}.png")
with Image.load(input_file) as image:
image.save(output_file, PngOptions())
return output_file
class UserMarker:
def __init__(self):
self._list: list = []
def add_point(self, left, top, radius):
for y in range(top - radius, top + radius + 1):
for x in range(left - radius, left + radius + 1):
self._list.append(Point(x, y))
return self
def get_points(self):
return self._list
# Run examples
remove_background_auto_processing_with_assumed_objects()
remove_background_processing_with_manual_rectangles()
remove_background_auto_processing()
remove_background_generic_example()
 
  • 关于 Python API 的 Aspose.Imaging

    Aspose.Imaging API 是一种图像处理解决方案,用于在应用程序中创建、修改、绘制或转换图像(照片)。它提供:跨平台的图像处理,包括但不限于各种图像格式之间的转换(包括统一的多页或多帧图像处理)、绘图等修改、使用图形基元、转换(调整大小、裁剪、翻转和旋转) 、二值化、灰度、调整)、高级图像处理功能(过滤、抖动、遮罩、去偏斜)和内存优化策略。它是一个独立的库,不依赖任何软件进行图像操作。可以在项目中使用原生 API 轻松添加高性能图像转换功能。这些是 100% 私有的本地 API,图像在您的服务器上处理。

    通过在线应用删除 ICO 中的背景

    通过访问我们的 Live Demos 网站 移除 ICO 文档中的背景。 现场演示有以下好处

      无需下载或设置任何东西
      无需编写任何代码
      只需上传您的 ICO 文件并点击“立即删除背景”按钮
      立即获取生成文件的下载链接

    ICO 什么是 ICO 文件格式

    ICO 文件格式是 Microsoft Windows 中计算机图标的图像文件格式。 ICO 文件包含一个或多个具有多种尺寸和颜色深度的小图像,以便它们可以适当地缩放。在 Windows 中,在桌面、开始菜单或 Windows 资源管理器中向用户显示图标的所有可执行文件都必须带有 ICO 格式的图标。

    阅读更多

    其他支持的删除背景格式

    使用 Python,可以轻松地从不同格式中删除背景,包括。

    APNG (动画便携式网络图形)
    BMP (位图图片)
    JPG (联合摄影专家组)
    DIB (设备无关位图)
    DICOM (数码影像与通讯)
    DJVU (图形格式)
    DNG (数码相机图像)
    EMF (增强的元文件格式)
    EMZ (Windows 压缩增强元文件)
    GIF (图形交换格式)
    JP2 (JPEG 2000)
    J2K (小波压缩图像)
    PNG (便携式网络图形)
    TIFF (标记图像格式)
    WEBP (光栅 Web 图像)
    WMF (微软视窗元文件)
    WMZ (压缩的 Windows Media Player 皮肤)
    TGA (塔加图形)
    SVG (可缩放矢量图形)
    EPS (封装的 PostScript 语言)
    CDR (矢量绘图图像)
    CMX (Corel 交换图像)
    OTG (开放文档标准)
    ODG (Apache OpenOffice 绘图格式)