omero-integration

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

OMERO Integration

OMERO 集成

Overview

概述

OMERO is an open-source platform for managing, visualizing, and analyzing microscopy images and metadata. Access images via Python API, retrieve datasets, analyze pixels, manage ROIs and annotations, for high-content screening and microscopy workflows.

OMERO是一个用于管理、可视化和分析显微图像及元数据的开源平台。可通过Python API访问图像、检索数据集、分析像素、管理ROI和标注，适用于高内涵筛选和显微工作流。

When to Use This Skill

何时使用此技能

This skill should be used when:

Working with OMERO Python API (omero-py) to access microscopy data
Retrieving images, datasets, projects, or screening data programmatically
Analyzing pixel data and creating derived images
Creating or managing ROIs (regions of interest) on microscopy images
Adding annotations, tags, or metadata to OMERO objects
Storing measurement results in OMERO tables
Creating server-side scripts for batch processing
Performing high-content screening analysis

在以下场景中应使用此技能：

使用OMERO Python API（omero-py）访问显微数据
以编程方式检索图像、数据集、项目或筛选数据
分析像素数据并创建衍生图像
在显微图像上创建或管理ROI（感兴趣区域）
为OMERO对象添加标注、标签或元数据
将测量结果存储在OMERO表格中
创建用于批量处理的服务器端脚本
执行高内涵筛选分析

Core Capabilities

核心功能

This skill covers eight major capability areas. Each is documented in detail in the references/ directory:

此技能涵盖八大核心功能领域，每个领域的详细文档都在references/目录中：

1. Connection & Session Management

1. 连接与会话管理

File:

references/connection.md

Establish secure connections to OMERO servers, manage sessions, handle authentication, and work with group contexts. Use this for initial setup and connection patterns.

Common scenarios:

Connect to OMERO server with credentials
Use existing session IDs
Switch between group contexts
Manage connection lifecycle with context managers

文件：

references/connection.md

建立与OMERO服务器的安全连接，管理会话，处理身份验证，并在组上下文下工作。用于初始设置和连接模式配置。

常见场景：

使用凭据连接OMERO服务器
使用现有会话ID
在不同组上下文间切换
使用上下文管理器管理连接生命周期

2. Data Access & Retrieval

2. 数据访问与检索

File:

references/data_access.md

Navigate OMERO's hierarchical data structure (Projects → Datasets → Images) and screening data (Screens → Plates → Wells). Retrieve objects, query by attributes, and access metadata.

Common scenarios:

List all projects and datasets for a user
Retrieve images by ID or dataset
Access screening plate data
Query objects with filters

文件：

references/data_access.md

浏览OMERO的层级数据结构（项目→数据集→图像）和筛选数据（筛选集→培养板→孔）。检索对象、按属性查询并访问元数据。

常见场景：

列出用户的所有项目和数据集
通过ID或数据集检索图像
访问筛选培养板数据
使用过滤器查询对象

3. Metadata & Annotations

3. 元数据与标注

File:

references/metadata.md

Create and manage annotations including tags, key-value pairs, file attachments, and comments. Link annotations to images, datasets, or other objects.

Common scenarios:

Add tags to images
Attach analysis results as files
Create custom key-value metadata
Query annotations by namespace

文件：

references/metadata.md

创建和管理标注，包括标签、键值对、文件附件和注释。将标注关联到图像、数据集或其他对象。

常见场景：

为图像添加标签
将分析结果作为文件附加
创建自定义键值元数据
按命名空间查询标注

4. Image Processing & Rendering

4. 图像处理与渲染

File:

references/image_processing.md

Access raw pixel data as NumPy arrays, manipulate rendering settings, create derived images, and manage physical dimensions.

Common scenarios:

Extract pixel data for computational analysis
Generate thumbnail images
Create maximum intensity projections
Modify channel rendering settings

文件：

references/image_processing.md

以NumPy数组形式访问原始像素数据，操作渲染设置，创建衍生图像，并管理物理尺寸。

常见场景：

提取像素数据用于计算分析
生成缩略图
创建最大强度投影
修改通道渲染设置

5. Regions of Interest (ROIs)

5. 感兴趣区域（ROIs）

File:

references/rois.md

Create, retrieve, and analyze ROIs with various shapes (rectangles, ellipses, polygons, masks, points, lines). Extract intensity statistics from ROI regions.

Common scenarios:

Draw rectangular ROIs on images
Create polygon masks for segmentation
Analyze pixel intensities within ROIs
Export ROI coordinates

文件：

references/rois.md

创建、检索和分析不同形状的ROI（矩形、椭圆、多边形、掩码、点、线）。提取ROI区域内的强度统计数据。

常见场景：

在图像上绘制矩形ROI
创建用于分割的多边形掩码
分析ROI内的像素强度
导出ROI坐标

6. OMERO Tables

6. OMERO表格

File:

references/tables.md

Store and query structured tabular data associated with OMERO objects. Useful for analysis results, measurements, and metadata.

Common scenarios:

Store quantitative measurements for images
Create tables with multiple column types
Query table data with conditions
Link tables to specific images or datasets

文件：

references/tables.md

存储和查询与OMERO对象关联的结构化表格数据，适用于分析结果、测量数据和元数据。

常见场景：

存储图像的定量测量结果
创建包含多种列类型的表格
按条件查询表格数据
将表格关联到特定图像或数据集

7. Scripts & Batch Operations

7. 脚本与批量操作

File:

references/scripts.md

Create OMERO.scripts that run server-side for batch processing, automated workflows, and integration with OMERO clients.

Common scenarios:

Process multiple images in batch
Create automated analysis pipelines
Generate summary statistics across datasets
Export data in custom formats

文件：

references/scripts.md

创建在服务器端运行的OMERO.scripts，用于批量处理、自动化工作流以及与OMERO客户端集成。

常见场景：

批量处理多张图像
创建自动化分析流水线
生成跨数据集的汇总统计数据
以自定义格式导出数据

8. Advanced Features

8. 高级功能

File:

references/advanced.md

Covers permissions, filesets, cross-group queries, delete operations, and other advanced functionality.

Common scenarios:

Handle group permissions
Access original imported files
Perform cross-group queries
Delete objects with callbacks

文件：

references/advanced.md

涵盖权限管理、文件集、跨组查询、删除操作及其他高级功能。

常见场景：

处理组权限
访问原始导入文件
执行跨组查询
通过回调删除对象

Installation

安装

bash

uv pip install omero-py

Requirements:

Python 3.7+
Zeroc Ice 3.6+
Access to an OMERO server (host, port, credentials)

bash

uv pip install omero-py

要求：

Python 3.7+
Zeroc Ice 3.6+
可访问OMERO服务器（主机、端口、凭据）

Quick Start

快速开始

Basic connection pattern:

python

from omero.gateway import BlitzGateway

基础连接模式：

python

from omero.gateway import BlitzGateway

Connect to OMERO server

conn = BlitzGateway(username, password, host=host, port=port) connected = conn.connect()

if connected: # Perform operations for project in conn.listProjects(): print(project.getName())

# Always close connection
conn.close()

else: print("Connection failed")


**Recommended pattern with context manager:**

```python
from omero.gateway import BlitzGateway

with BlitzGateway(username, password, host=host, port=port) as conn:
    # Connection automatically managed
    for project in conn.listProjects():
        print(project.getName())
    # Automatically closed on exit

conn = BlitzGateway(username, password, host=host, port=port) connected = conn.connect()

if connected: # Perform operations for project in conn.listProjects(): print(project.getName())

# Always close connection
conn.close()

else: print("Connection failed")


**推荐的上下文管理器模式**：

```python
from omero.gateway import BlitzGateway

with BlitzGateway(username, password, host=host, port=port) as conn:
    # Connection automatically managed
    for project in conn.listProjects():
        print(project.getName())
    # Automatically closed on exit

Selecting the Right Capability

选择合适的功能

For data exploration:

Start with
```
references/connection.md
```
to establish connection
Use
```
references/data_access.md
```
to navigate hierarchy
Check
```
references/metadata.md
```
for annotation details

For image analysis:

Use
```
references/image_processing.md
```
for pixel data access
Use
```
references/rois.md
```
for region-based analysis
Use
```
references/tables.md
```
to store results

For automation:

Use
```
references/scripts.md
```
for server-side processing
Use
```
references/data_access.md
```
for batch data retrieval

For advanced operations:

Use
```
references/advanced.md
```
for permissions and deletion
Check
```
references/connection.md
```
for cross-group queries

用于数据探索：

从
```
references/connection.md
```
开始建立连接
使用
```
references/data_access.md
```
浏览层级结构
查看
```
references/metadata.md
```
了解标注详情

用于图像分析：

使用
```
references/image_processing.md
```
访问像素数据
使用
```
references/rois.md
```
进行基于区域的分析
使用
```
references/tables.md
```
存储结果

用于自动化：

使用
```
references/scripts.md
```
进行服务器端处理
使用
```
references/data_access.md
```
进行批量数据检索

用于高级操作：

使用
```
references/advanced.md
```
处理权限和删除操作
查看
```
references/connection.md
```
了解跨组查询

Common Workflows

常见工作流

Workflow 1: Retrieve and Analyze Images

工作流1：检索并分析图像

Connect to OMERO server (
```
references/connection.md
```
)
Navigate to dataset (
```
references/data_access.md
```
)
Retrieve images from dataset (
```
references/data_access.md
```
)
Access pixel data as NumPy array (
```
references/image_processing.md
```
)
Perform analysis
Store results as table or file annotation (
```
references/tables.md
```
or
```
references/metadata.md
```
)

连接到OMERO服务器（
```
references/connection.md
```
）
导航到数据集（
```
references/data_access.md
```
）
从数据集检索图像（
```
references/data_access.md
```
）
以NumPy数组形式访问像素数据（
```
references/image_processing.md
```
）
执行分析
将结果存储为表格或文件标注（
```
references/tables.md
```
或
```
references/metadata.md
```
）

Workflow 2: Batch ROI Analysis

工作流2：批量ROI分析

Connect to OMERO server
Retrieve images with existing ROIs (
```
references/rois.md
```
)
For each image, get ROI shapes
Extract pixel intensities within ROIs (
```
references/rois.md
```
)
Store measurements in OMERO table (
```
references/tables.md
```
)

连接到OMERO服务器
检索带有现有ROI的图像（
```
references/rois.md
```
）
针对每张图像，获取ROI形状
提取ROI内的像素强度（
```
references/rois.md
```
）
将测量结果存储在OMERO表格中（
```
references/tables.md
```
）

Workflow 3: Create Analysis Script

工作流3：创建分析脚本

Design analysis workflow
Use OMERO.scripts framework (
```
references/scripts.md
```
)
Access data through script parameters
Process images in batch
Generate outputs (new images, tables, files)

设计分析工作流
使用OMERO.scripts框架（
```
references/scripts.md
```
）
通过脚本参数访问数据
批量处理图像
生成输出（新图像、表格、文件）

Error Handling

错误处理

Always wrap OMERO operations in try-except blocks and ensure connections are properly closed:

python

from omero.gateway import BlitzGateway
import traceback

try:
    conn = BlitzGateway(username, password, host=host, port=port)
    if not conn.connect():
        raise Exception("Connection failed")

    # Perform operations

except Exception as e:
    print(f"Error: {e}")
    traceback.print_exc()
finally:
    if conn:
        conn.close()

始终将OMERO操作包裹在try-except块中，并确保连接被正确关闭：

python

from omero.gateway import BlitzGateway
import traceback

try:
    conn = BlitzGateway(username, password, host=host, port=port)
    if not conn.connect():
        raise Exception("Connection failed")

    # Perform operations

except Exception as e:
    print(f"Error: {e}")
    traceback.print_exc()
finally:
    if conn:
        conn.close()

Additional Resources

额外资源

Official Documentation: https://omero.readthedocs.io/en/stable/developers/Python.html
BlitzGateway API: https://omero.readthedocs.io/en/stable/developers/Python.html#omero-blitzgateway
OMERO Model: https://omero.readthedocs.io/en/stable/developers/Model.html
Community Forum: https://forum.image.sc/tag/omero

官方文档：https://omero.readthedocs.io/en/stable/developers/Python.html
BlitzGateway API：https://omero.readthedocs.io/en/stable/developers/Python.html#omero-blitzgateway
OMERO 模型：https://omero.readthedocs.io/en/stable/developers/Model.html
社区论坛：https://forum.image.sc/tag/omero

Notes

注意事项

OMERO uses group-based permissions (READ-ONLY, READ-ANNOTATE, READ-WRITE)
Images in OMERO are organized hierarchically: Project > Dataset > Image
Screening data uses: Screen > Plate > Well > WellSample > Image
Always close connections to free server resources
Use context managers for automatic resource management
Pixel data is returned as NumPy arrays for analysis

OMERO使用基于组的权限（只读、可读可标注、可读可写）
OMERO中的图像按层级组织：项目 > 数据集 > 图像
筛选数据的层级为：筛选集 > 培养板 > 孔 > 孔样本 > 图像
始终关闭连接以释放服务器资源
使用上下文管理器实现自动资源管理
像素数据以NumPy数组形式返回，便于分析