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ee.data.computePixels (Python only)
使用集合让一切井井有条
根据您的偏好保存内容并对其进行分类。
通过对图片数据执行任意计算来计算图块。
返回：
以原始图片数据形式返回的像素。
| 用法 | 返回 |
|---|
ee.data.computePixels(params) | 对象|值 |
| 参数 | 类型 | 详细信息 |
|---|
params | 对象 | 一个包含参数的对象，参数可具有以下可能的值：
expression - 要计算的表达式。
fileFormat - 生成的文件格式。默认值为 png。如需了解可用的格式，请参阅 ImageFileFormat。还有其他格式可将下载的对象转换为 Python 数据对象。其中包括：
NUMPY_NDARRAY，用于转换为结构化 NumPy 数组。
grid - 用于描述要从中提取数据的像素网格的参数。
默认为数据的原生像素网格。
bandIds - 如果存在，则指定要从中获取像素的一组特定波段。
visualizationOptions - 如果存在，则为一组可视化选项，用于生成数据的 8 位 RGB 可视化效果，而不是返回原始数据。
workloadTag - 用户提供的用于跟踪相应计算的标记。 |
示例
Python 设置
如需了解 Python API 和如何使用 geemap 进行交互式开发，请参阅
Python 环境页面。
import ee
import geemap.core as geemap
Colab (Python)
# Region of interest.
coords = [
-121.58626826832939,
38.059141484827485,
]
region = ee.Geometry.Point(coords)
# Sentinel-2 median composite.
image = (ee.ImageCollection('COPERNICUS/S2')
.filterBounds(region)
.filterDate('2020-04-01', '2020-09-01')
.median())
# Make a projection to discover the scale in degrees.
proj = ee.Projection('EPSG:4326').atScale(10).getInfo()
# Get scales out of the transform.
scale_x = proj['transform'][0]
scale_y = -proj['transform'][4]
# Make a request object.
request = {
'expression': image,
'fileFormat': 'PNG',
'bandIds': ['B4', 'B3', 'B2'],
'grid': {
'dimensions': {
'width': 640,
'height': 640
},
'affineTransform': {
'scaleX': scale_x,
'shearX': 0,
'translateX': coords[0],
'shearY': 0,
'scaleY': scale_y,
'translateY': coords[1]
},
'crsCode': proj['crs'],
},
'visualizationOptions': {'ranges': [{'min': 0, 'max': 3000}]},
}
image_png = ee.data.computePixels(request)
# Do something with the image...
如未另行说明，那么本页面中的内容已根据知识共享署名 4.0 许可获得了许可，并且代码示例已根据 Apache 2.0 许可获得了许可。有关详情，请参阅 Google 开发者网站政策。Java 是 Oracle 和/或其关联公司的注册商标。
最后更新时间 (UTC)：2025-07-26。
[null,null,["最后更新时间 (UTC)：2025-07-26。"],[[["\u003cp\u003e\u003ccode\u003eee.data.computePixels\u003c/code\u003e computes a tile by performing an arbitrary computation on image data and returns the pixels as raw image data.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eparams\u003c/code\u003e argument to \u003ccode\u003eee.data.computePixels\u003c/code\u003e allows for customizing the computation through an expression, file format, pixel grid, band selection, visualization options, and workload tag.\u003c/p\u003e\n"],["\u003cp\u003eThe provided Python example demonstrates using \u003ccode\u003eee.data.computePixels\u003c/code\u003e to retrieve a PNG image tile from a Sentinel-2 median composite with specified visualization and grid parameters.\u003c/p\u003e\n"]]],[],null,["# ee.data.computePixels (Python only)\n\n\u003cbr /\u003e\n\nComputes a tile by performing an arbitrary computation on image data.\n\n\u003cbr /\u003e\n\nReturns:\nThe pixels as raw image data.\n\n| Usage | Returns |\n|---------------------------------|---------------|\n| `ee.data.computePixels(params)` | Object\\|Value |\n\n| Argument | Type | Details |\n|----------|--------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `params` | Object | An object containing parameters with the following possible values: `expression` - The expression to compute. `fileFormat` - The resulting file format. Defaults to png. See [ImageFileFormat](https://developers.google.com/earth-engine/reference/rest/v1/ImageFileFormat) for the available formats. There are additional formats that convert the downloaded object to a Python data object. These include: `NUMPY_NDARRAY`, which converts to a structured NumPy array. `grid` - Parameters describing the pixel grid in which to fetch data. Defaults to the native pixel grid of the data. `bandIds` - If present, specifies a specific set of bands from which to get pixels. `visualizationOptions` - If present, a set of visualization options to apply to produce an 8-bit RGB visualization of the data, rather than returning the raw data. `workloadTag` - User supplied tag to track this computation. |\n\nExamples\n--------\n\nPython setup\n\nSee the [Python Environment](/earth-engine/guides/python_install) page for information on the Python API and using\n`geemap` for interactive development. \n\n```python\nimport ee\nimport geemap.core as geemap\n```\n\n### Colab (Python)\n\n```python\n# Region of interest.\ncoords = [\n -121.58626826832939,\n 38.059141484827485,\n]\nregion = ee.Geometry.Point(coords)\n\n# Sentinel-2 median composite.\nimage = (ee.ImageCollection('COPERNICUS/S2')\n .filterBounds(region)\n .filterDate('2020-04-01', '2020-09-01')\n .median())\n\n# Make a projection to discover the scale in degrees.\nproj = ee.Projection('EPSG:4326').atScale(10).getInfo()\n\n# Get scales out of the transform.\nscale_x = proj['transform'][0]\nscale_y = -proj['transform'][4]\n\n# Make a request object.\nrequest = {\n 'expression': image,\n 'fileFormat': 'PNG',\n 'bandIds': ['B4', 'B3', 'B2'],\n 'grid': {\n 'dimensions': {\n 'width': 640,\n 'height': 640\n },\n 'affineTransform': {\n 'scaleX': scale_x,\n 'shearX': 0,\n 'translateX': coords[0],\n 'shearY': 0,\n 'scaleY': scale_y,\n 'translateY': coords[1]\n },\n 'crsCode': proj['crs'],\n },\n 'visualizationOptions': {'ranges': [{'min': 0, 'max': 3000}]},\n}\n\nimage_png = ee.data.computePixels(request)\n# Do something with the image...\n```"]]
