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# Directory Structure
```
├── .cursorrules
├── .env.example
├── .github
│ └── workflows
│ ├── build.yml
│ ├── ci-cd.yml
│ ├── ci.yml
│ ├── deploy.yml
│ ├── ecosystem-monitor.yml
│ ├── fan-out-orchestrator.yml
│ └── release.yml
├── .gitignore
├── .pre-commit-config.yaml
├── AUTOMOTIVE_CAMERA_SYSTEM_SUMMARY.md
├── automotive-camera-system
│ ├── docs
│ │ └── IMPLEMENTACE_CS.md
│ └── README.md
├── AWS_MCP_IMPLEMENTATION_SUMMARY.md
├── AWS_MCP_QUICKSTART.md
├── AWS_SIP_TRUNK_DEPLOYMENT_COMPLETE.md
├── aws-sip-trunk
│ ├── .gitignore
│ ├── config
│ │ ├── extensions.conf.j2
│ │ └── pjsip.conf.j2
│ ├── DEPLOYMENT_SUMMARY.md
│ ├── docs
│ │ ├── DEPLOYMENT.md
│ │ └── TROUBLESHOOTING.md
│ ├── PROJECT_INDEX.md
│ ├── pyproject.toml
│ ├── QUICKSTART.md
│ ├── README.md
│ ├── scripts
│ │ ├── deploy-asterisk-aws.sh
│ │ └── user-data.sh
│ ├── terraform
│ │ ├── ec2.tf
│ │ ├── main.tf
│ │ ├── monitoring.tf
│ │ ├── networking.tf
│ │ ├── outputs.tf
│ │ ├── storage.tf
│ │ ├── terraform.tfvars.example
│ │ └── variables.tf
│ ├── tests
│ │ └── test_sip_connectivity.py
│ └── VERIFICATION_CHECKLIST.md
├── CLAUDE.md
├── component_templates.json
├── conanfile.py
├── config
│ ├── default.json
│ └── project_orchestration.json
├── Containerfile
├── cursor-templates
│ └── openssl
│ ├── linux-dev.mdc.jinja2
│ └── shared.mdc.jinja2
├── data
│ └── prompts
│ └── templates
│ ├── advanced-multi-server-template.json
│ ├── analysis-assistant.json
│ ├── analyze-mermaid-diagram.json
│ ├── architecture-design-assistant.json
│ ├── code-diagram-documentation-creator.json
│ ├── code-refactoring-assistant.json
│ ├── code-review-assistant.json
│ ├── collaborative-development.json
│ ├── consolidated-interfaces-template.json
│ ├── could-you-interpret-the-assumed-applicat.json
│ ├── data-analysis-template.json
│ ├── database-query-assistant.json
│ ├── debugging-assistant.json
│ ├── development-system-prompt-zcna0.json
│ ├── development-system-prompt.json
│ ├── development-workflow.json
│ ├── docker-compose-prompt-combiner.json
│ ├── docker-containerization-guide.json
│ ├── docker-mcp-servers-orchestration.json
│ ├── foresight-assistant.json
│ ├── generate-different-types-of-questions-ab.json
│ ├── generate-mermaid-diagram.json
│ ├── image-1-describe-the-icon-in-one-sen.json
│ ├── initialize-project-setup-for-a-new-micro.json
│ ├── install-dependencies-build-run-test.json
│ ├── mcp-code-generator.json
│ ├── mcp-integration-assistant.json
│ ├── mcp-resources-explorer.json
│ ├── mcp-resources-integration.json
│ ├── mcp-server-configurator.json
│ ├── mcp-server-dev-prompt-combiner.json
│ ├── mcp-server-integration-template.json
│ ├── mcp-template-system.json
│ ├── mermaid-analysis-expert.json
│ ├── mermaid-class-diagram-generator.json
│ ├── mermaid-diagram-generator.json
│ ├── mermaid-diagram-modifier.json
│ ├── modify-mermaid-diagram.json
│ ├── monorepo-migration-guide.json
│ ├── multi-resource-context.json
│ ├── project-analysis-assistant.json
│ ├── prompt-combiner-interface.json
│ ├── prompt-templates.json
│ ├── repository-explorer.json
│ ├── research-assistant.json
│ ├── sequential-data-analysis.json
│ ├── solid-code-analysis-visualizer.json
│ ├── task-list-helper-8ithy.json
│ ├── template-based-mcp-integration.json
│ ├── templates.json
│ ├── test-prompt.json
│ └── you-are-limited-to-respond-yes-or-no-onl.json
├── docs
│ ├── AWS_MCP.md
│ ├── AWS.md
│ ├── CONAN.md
│ └── integration.md
├── elevenlabs-agents
│ ├── agent-prompts.json
│ └── README.md
├── IMPLEMENTATION_STATUS.md
├── integration_plan.md
├── LICENSE
├── MANIFEST.in
├── mcp-project-orchestrator
│ └── openssl
│ ├── .github
│ │ └── workflows
│ │ └── validate-cursor-config.yml
│ ├── conanfile.py
│ ├── CURSOR_DEPLOYMENT_POLISH.md
│ ├── cursor-rules
│ │ ├── mcp.json.jinja2
│ │ ├── prompts
│ │ │ ├── fips-compliance.md.jinja2
│ │ │ ├── openssl-coding-standards.md.jinja2
│ │ │ └── pr-review.md.jinja2
│ │ └── rules
│ │ ├── ci-linux.mdc.jinja2
│ │ ├── linux-dev.mdc.jinja2
│ │ ├── macos-dev.mdc.jinja2
│ │ ├── shared.mdc.jinja2
│ │ └── windows-dev.mdc.jinja2
│ ├── docs
│ │ └── cursor-configuration-management.md
│ ├── examples
│ │ └── example-workspace
│ │ ├── .cursor
│ │ │ ├── mcp.json
│ │ │ └── rules
│ │ │ ├── linux-dev.mdc
│ │ │ └── shared.mdc
│ │ ├── .gitignore
│ │ ├── CMakeLists.txt
│ │ ├── conanfile.py
│ │ ├── profiles
│ │ │ ├── linux-gcc-debug.profile
│ │ │ └── linux-gcc-release.profile
│ │ ├── README.md
│ │ └── src
│ │ ├── crypto_utils.cpp
│ │ ├── crypto_utils.h
│ │ └── main.cpp
│ ├── IMPLEMENTATION_SUMMARY.md
│ ├── mcp_orchestrator
│ │ ├── __init__.py
│ │ ├── cli.py
│ │ ├── conan_integration.py
│ │ ├── cursor_config.py
│ │ ├── cursor_deployer.py
│ │ ├── deploy_cursor.py
│ │ ├── env_config.py
│ │ ├── platform_detector.py
│ │ └── yaml_validator.py
│ ├── openssl-cursor-example-workspace-20251014_121133.zip
│ ├── pyproject.toml
│ ├── README.md
│ ├── requirements.txt
│ ├── scripts
│ │ └── create_example_workspace.py
│ ├── setup.py
│ ├── test_deployment.py
│ └── tests
│ ├── __init__.py
│ ├── test_cursor_deployer.py
│ └── test_template_validation.py
├── printcast-agent
│ ├── .env.example
│ ├── config
│ │ └── asterisk
│ │ └── extensions.conf
│ ├── Containerfile
│ ├── docker-compose.yml
│ ├── pyproject.toml
│ ├── README.md
│ ├── scripts
│ │ └── docker-entrypoint.sh
│ ├── src
│ │ ├── integrations
│ │ │ ├── __init__.py
│ │ │ ├── asterisk.py
│ │ │ ├── content.py
│ │ │ ├── delivery.py
│ │ │ ├── elevenlabs.py
│ │ │ └── printing.py
│ │ ├── mcp_server
│ │ │ ├── __init__.py
│ │ │ ├── main.py
│ │ │ └── server.py
│ │ └── orchestration
│ │ ├── __init__.py
│ │ └── workflow.py
│ └── tests
│ └── test_mcp_server.py
├── project_orchestration.json
├── project_templates.json
├── pyproject.toml
├── README.md
├── REFACTORING_COMPLETED.md
├── REFACTORING_RECOMMENDATIONS.md
├── requirements.txt
├── scripts
│ ├── archive
│ │ ├── init_claude_test.sh
│ │ ├── init_postgres.sh
│ │ ├── start_mcp_servers.sh
│ │ └── test_claude_desktop.sh
│ ├── consolidate_mermaid.py
│ ├── consolidate_prompts.py
│ ├── consolidate_resources.py
│ ├── consolidate_templates.py
│ ├── INSTRUCTIONS.md
│ ├── README.md
│ ├── setup_aws_mcp.sh
│ ├── setup_mcp.sh
│ ├── setup_orchestrator.sh
│ ├── setup_project.py
│ └── test_mcp.sh
├── src
│ └── mcp_project_orchestrator
│ ├── __init__.py
│ ├── __main__.py
│ ├── aws_mcp.py
│ ├── cli
│ │ └── __init__.py
│ ├── cli.py
│ ├── commands
│ │ └── openssl_cli.py
│ ├── core
│ │ ├── __init__.py
│ │ ├── base.py
│ │ ├── config.py
│ │ ├── exceptions.py
│ │ ├── fastmcp.py
│ │ ├── logging.py
│ │ └── managers.py
│ ├── cursor_deployer.py
│ ├── ecosystem_monitor.py
│ ├── fan_out_orchestrator.py
│ ├── fastmcp.py
│ ├── mcp-py
│ │ ├── AggregateVersions.py
│ │ ├── CustomBashTool.py
│ │ ├── FileAnnotator.py
│ │ ├── mcp-client.py
│ │ ├── mcp-server.py
│ │ ├── MermaidDiagramGenerator.py
│ │ ├── NamingAgent.py
│ │ └── solid-analyzer-agent.py
│ ├── mermaid
│ │ ├── __init__.py
│ │ ├── generator.py
│ │ ├── mermaid_orchestrator.py
│ │ ├── renderer.py
│ │ ├── templates
│ │ │ ├── AbstractFactory-diagram.json
│ │ │ ├── Adapter-diagram.json
│ │ │ ├── Analyze_Mermaid_Diagram.json
│ │ │ ├── Builder-diagram.json
│ │ │ ├── Chain-diagram.json
│ │ │ ├── Code_Diagram_Documentation_Creator.json
│ │ │ ├── Command-diagram.json
│ │ │ ├── Decorator-diagram.json
│ │ │ ├── Facade-diagram.json
│ │ │ ├── Factory-diagram.json
│ │ │ ├── flowchart
│ │ │ │ ├── AbstractFactory-diagram.json
│ │ │ │ ├── Adapter-diagram.json
│ │ │ │ ├── Analyze_Mermaid_Diagram.json
│ │ │ │ ├── Builder-diagram.json
│ │ │ │ ├── Chain-diagram.json
│ │ │ │ ├── Code_Diagram_Documentation_Creator.json
│ │ │ │ ├── Command-diagram.json
│ │ │ │ ├── Decorator-diagram.json
│ │ │ │ ├── Facade-diagram.json
│ │ │ │ ├── Factory-diagram.json
│ │ │ │ ├── Generate_Mermaid_Diagram.json
│ │ │ │ ├── generated_diagram.json
│ │ │ │ ├── integration.json
│ │ │ │ ├── Iterator-diagram.json
│ │ │ │ ├── Mediator-diagram.json
│ │ │ │ ├── Memento-diagram.json
│ │ │ │ ├── Mermaid_Analysis_Expert.json
│ │ │ │ ├── Mermaid_Class_Diagram_Generator.json
│ │ │ │ ├── Mermaid_Diagram_Generator.json
│ │ │ │ ├── Mermaid_Diagram_Modifier.json
│ │ │ │ ├── Modify_Mermaid_Diagram.json
│ │ │ │ ├── Observer-diagram.json
│ │ │ │ ├── Prototype-diagram.json
│ │ │ │ ├── Proxy-diagram.json
│ │ │ │ ├── README.json
│ │ │ │ ├── Singleton-diagram.json
│ │ │ │ ├── State-diagram.json
│ │ │ │ ├── Strategy-diagram.json
│ │ │ │ ├── TemplateMethod-diagram.json
│ │ │ │ ├── theme_dark.json
│ │ │ │ ├── theme_default.json
│ │ │ │ ├── theme_pastel.json
│ │ │ │ ├── theme_vibrant.json
│ │ │ │ └── Visitor-diagram.json
│ │ │ ├── Generate_Mermaid_Diagram.json
│ │ │ ├── generated_diagram.json
│ │ │ ├── index.json
│ │ │ ├── integration.json
│ │ │ ├── Iterator-diagram.json
│ │ │ ├── Mediator-diagram.json
│ │ │ ├── Memento-diagram.json
│ │ │ ├── Mermaid_Analysis_Expert.json
│ │ │ ├── Mermaid_Class_Diagram_Generator.json
│ │ │ ├── Mermaid_Diagram_Generator.json
│ │ │ ├── Mermaid_Diagram_Modifier.json
│ │ │ ├── Modify_Mermaid_Diagram.json
│ │ │ ├── Observer-diagram.json
│ │ │ ├── Prototype-diagram.json
│ │ │ ├── Proxy-diagram.json
│ │ │ ├── README.json
│ │ │ ├── Singleton-diagram.json
│ │ │ ├── State-diagram.json
│ │ │ ├── Strategy-diagram.json
│ │ │ ├── TemplateMethod-diagram.json
│ │ │ ├── theme_dark.json
│ │ │ ├── theme_default.json
│ │ │ ├── theme_pastel.json
│ │ │ ├── theme_vibrant.json
│ │ │ └── Visitor-diagram.json
│ │ └── types.py
│ ├── project_orchestration.py
│ ├── prompt_manager
│ │ ├── __init__.py
│ │ ├── loader.py
│ │ ├── manager.py
│ │ └── template.py
│ ├── prompts
│ │ ├── __dirname.json
│ │ ├── __image_1___describe_the_icon_in_one_sen___.json
│ │ ├── __init__.py
│ │ ├── __type.json
│ │ ├── _.json
│ │ ├── _DEFAULT_OPEN_DELIMITER.json
│ │ ├── _emojiRegex.json
│ │ ├── _UUID_CHARS.json
│ │ ├── a.json
│ │ ├── A.json
│ │ ├── Aa.json
│ │ ├── aAnnotationPadding.json
│ │ ├── absoluteThresholdGroup.json
│ │ ├── add.json
│ │ ├── ADDITIONAL_PROPERTY_FLAG.json
│ │ ├── Advanced_Multi-Server_Integration_Template.json
│ │ ├── allOptionsList.json
│ │ ├── analysis
│ │ │ ├── Data_Analysis_Template.json
│ │ │ ├── index.json
│ │ │ ├── Mermaid_Analysis_Expert.json
│ │ │ ├── Sequential_Data_Analysis_with_MCP_Integration.json
│ │ │ └── SOLID_Code_Analysis_Visualizer.json
│ │ ├── Analysis_Assistant.json
│ │ ├── Analyze_Mermaid_Diagram.json
│ │ ├── ANDROID_EVERGREEN_FIRST.json
│ │ ├── ANSI_ESCAPE_BELL.json
│ │ ├── architecture
│ │ │ ├── index.json
│ │ │ └── PromptCombiner_Interface.json
│ │ ├── Architecture_Design_Assistant.json
│ │ ├── argsTag.json
│ │ ├── ARROW.json
│ │ ├── assistant
│ │ │ ├── Analysis_Assistant.json
│ │ │ ├── Architecture_Design_Assistant.json
│ │ │ ├── Code_Refactoring_Assistant.json
│ │ │ ├── Code_Review_Assistant.json
│ │ │ ├── Database_Query_Assistant.json
│ │ │ ├── Debugging_Assistant.json
│ │ │ ├── Foresight_Assistant.json
│ │ │ ├── index.json
│ │ │ ├── MCP_Integration_Assistant.json
│ │ │ ├── Project_Analysis_Assistant.json
│ │ │ └── Research_Assistant.json
│ │ ├── astralRange.json
│ │ ├── at.json
│ │ ├── authorization_endpoint.json
│ │ ├── b.json
│ │ ├── BABELIGNORE_FILENAME.json
│ │ ├── BACKSLASH.json
│ │ ├── backupId.json
│ │ ├── BANG.json
│ │ ├── BASE64_MAP.json
│ │ ├── baseFlags.json
│ │ ├── Basic_Template.json
│ │ ├── bgModel.json
│ │ ├── bignum.json
│ │ ├── blockKeywordsStr.json
│ │ ├── BOMChar.json
│ │ ├── boundary.json
│ │ ├── brackets.json
│ │ ├── BROWSER_VAR.json
│ │ ├── bt.json
│ │ ├── BUILTIN.json
│ │ ├── BULLET.json
│ │ ├── c.json
│ │ ├── C.json
│ │ ├── CACHE_VERSION.json
│ │ ├── cacheControl.json
│ │ ├── cacheProp.json
│ │ ├── category.py
│ │ ├── CHANGE_EVENT.json
│ │ ├── CHAR_CODE_0.json
│ │ ├── chars.json
│ │ ├── cjsPattern.json
│ │ ├── cKeywords.json
│ │ ├── classForPercent.json
│ │ ├── classStr.json
│ │ ├── clientFirstMessageBare.json
│ │ ├── cmd.json
│ │ ├── Code_Diagram_Documentation_Creator.json
│ │ ├── Code_Refactoring_Assistant.json
│ │ ├── Code_Review_Assistant.json
│ │ ├── code.json
│ │ ├── coding
│ │ │ ├── __dirname.json
│ │ │ ├── _.json
│ │ │ ├── _DEFAULT_OPEN_DELIMITER.json
│ │ │ ├── _emojiRegex.json
│ │ │ ├── _UUID_CHARS.json
│ │ │ ├── a.json
│ │ │ ├── A.json
│ │ │ ├── aAnnotationPadding.json
│ │ │ ├── absoluteThresholdGroup.json
│ │ │ ├── add.json
│ │ │ ├── ADDITIONAL_PROPERTY_FLAG.json
│ │ │ ├── allOptionsList.json
│ │ │ ├── ANDROID_EVERGREEN_FIRST.json
│ │ │ ├── ANSI_ESCAPE_BELL.json
│ │ │ ├── argsTag.json
│ │ │ ├── ARROW.json
│ │ │ ├── astralRange.json
│ │ │ ├── at.json
│ │ │ ├── authorization_endpoint.json
│ │ │ ├── BABELIGNORE_FILENAME.json
│ │ │ ├── BACKSLASH.json
│ │ │ ├── BANG.json
│ │ │ ├── BASE64_MAP.json
│ │ │ ├── baseFlags.json
│ │ │ ├── bgModel.json
│ │ │ ├── bignum.json
│ │ │ ├── blockKeywordsStr.json
│ │ │ ├── BOMChar.json
│ │ │ ├── boundary.json
│ │ │ ├── brackets.json
│ │ │ ├── BROWSER_VAR.json
│ │ │ ├── bt.json
│ │ │ ├── BUILTIN.json
│ │ │ ├── BULLET.json
│ │ │ ├── c.json
│ │ │ ├── C.json
│ │ │ ├── CACHE_VERSION.json
│ │ │ ├── cacheControl.json
│ │ │ ├── cacheProp.json
│ │ │ ├── CHANGE_EVENT.json
│ │ │ ├── CHAR_CODE_0.json
│ │ │ ├── chars.json
│ │ │ ├── cjsPattern.json
│ │ │ ├── cKeywords.json
│ │ │ ├── classForPercent.json
│ │ │ ├── classStr.json
│ │ │ ├── clientFirstMessageBare.json
│ │ │ ├── cmd.json
│ │ │ ├── code.json
│ │ │ ├── colorCode.json
│ │ │ ├── comma.json
│ │ │ ├── command.json
│ │ │ ├── configJsContent.json
│ │ │ ├── connectionString.json
│ │ │ ├── cssClassStr.json
│ │ │ ├── currentBoundaryParse.json
│ │ │ ├── d.json
│ │ │ ├── data.json
│ │ │ ├── DATA.json
│ │ │ ├── dataWebpackPrefix.json
│ │ │ ├── debug.json
│ │ │ ├── decodeStateVectorV2.json
│ │ │ ├── DEFAULT_DELIMITER.json
│ │ │ ├── DEFAULT_DIAGRAM_DIRECTION.json
│ │ │ ├── DEFAULT_JS_PATTERN.json
│ │ │ ├── DEFAULT_LOG_TARGET.json
│ │ │ ├── defaultHelpOpt.json
│ │ │ ├── defaultHost.json
│ │ │ ├── deferY18nLookupPrefix.json
│ │ │ ├── DELIM.json
│ │ │ ├── delimiter.json
│ │ │ ├── DEPRECATION.json
│ │ │ ├── destMain.json
│ │ │ ├── DID_NOT_THROW.json
│ │ │ ├── direction.json
│ │ │ ├── displayValue.json
│ │ │ ├── DNS.json
│ │ │ ├── doc.json
│ │ │ ├── DOCUMENTATION_NOTE.json
│ │ │ ├── DOT.json
│ │ │ ├── DOTS.json
│ │ │ ├── dummyCompoundId.json
│ │ │ ├── e.json
│ │ │ ├── E.json
│ │ │ ├── earlyHintsLink.json
│ │ │ ├── elide.json
│ │ │ ├── EMPTY.json
│ │ │ ├── end.json
│ │ │ ├── endpoint.json
│ │ │ ├── environment.json
│ │ │ ├── ERR_CODE.json
│ │ │ ├── errMessage.json
│ │ │ ├── errMsg.json
│ │ │ ├── ERROR_MESSAGE.json
│ │ │ ├── error.json
│ │ │ ├── ERROR.json
│ │ │ ├── ERRORCLASS.json
│ │ │ ├── errorMessage.json
│ │ │ ├── es6Default.json
│ │ │ ├── ESC.json
│ │ │ ├── Escapable.json
│ │ │ ├── escapedChar.json
│ │ │ ├── escapeFuncStr.json
│ │ │ ├── escSlash.json
│ │ │ ├── ev.json
│ │ │ ├── event.json
│ │ │ ├── execaMessage.json
│ │ │ ├── EXPECTED_LABEL.json
│ │ │ ├── expected.json
│ │ │ ├── expectedString.json
│ │ │ ├── expression1.json
│ │ │ ├── EXTENSION.json
│ │ │ ├── f.json
│ │ │ ├── FAIL_TEXT.json
│ │ │ ├── FILE_BROWSER_FACTORY.json
│ │ │ ├── fill.json
│ │ │ ├── findPackageJson.json
│ │ │ ├── fnKey.json
│ │ │ ├── FORMAT.json
│ │ │ ├── formatted.json
│ │ │ ├── from.json
│ │ │ ├── fullpaths.json
│ │ │ ├── FUNC_ERROR_TEXT.json
│ │ │ ├── GenStateSuspendedStart.json
│ │ │ ├── GENSYNC_EXPECTED_START.json
│ │ │ ├── gutter.json
│ │ │ ├── h.json
│ │ │ ├── handlerFuncName.json
│ │ │ ├── HASH_UNDEFINED.json
│ │ │ ├── head.json
│ │ │ ├── helpMessage.json
│ │ │ ├── HINT_ARG.json
│ │ │ ├── HOOK_RETURNED_NOTHING_ERROR_MESSAGE.json
│ │ │ ├── i.json
│ │ │ ├── id.json
│ │ │ ├── identifier.json
│ │ │ ├── Identifier.json
│ │ │ ├── INDENT.json
│ │ │ ├── indentation.json
│ │ │ ├── index.json
│ │ │ ├── INDIRECTION_FRAGMENT.json
│ │ │ ├── input.json
│ │ │ ├── inputText.json
│ │ │ ├── insert.json
│ │ │ ├── insertPromptQuery.json
│ │ │ ├── INSPECT_MAX_BYTES.json
│ │ │ ├── intToCharMap.json
│ │ │ ├── IS_ITERABLE_SENTINEL.json
│ │ │ ├── IS_KEYED_SENTINEL.json
│ │ │ ├── isConfigType.json
│ │ │ ├── isoSentinel.json
│ │ │ ├── isSourceNode.json
│ │ │ ├── j.json
│ │ │ ├── JAKE_CMD.json
│ │ │ ├── JEST_GLOBAL_NAME.json
│ │ │ ├── JEST_GLOBALS_MODULE_NAME.json
│ │ │ ├── JSON_SYNTAX_CHAR.json
│ │ │ ├── json.json
│ │ │ ├── jsonType.json
│ │ │ ├── jupyter_namespaceObject.json
│ │ │ ├── JUPYTERLAB_DOCMANAGER_PLUGIN_ID.json
│ │ │ ├── k.json
│ │ │ ├── KERNEL_STATUS_ERROR_CLASS.json
│ │ │ ├── key.json
│ │ │ ├── l.json
│ │ │ ├── labelId.json
│ │ │ ├── LATEST_PROTOCOL_VERSION.json
│ │ │ ├── LETTERDASHNUMBER.json
│ │ │ ├── LF.json
│ │ │ ├── LIMIT_REPLACE_NODE.json
│ │ │ ├── logTime.json
│ │ │ ├── lstatkey.json
│ │ │ ├── lt.json
│ │ │ ├── m.json
│ │ │ ├── maliciousPayload.json
│ │ │ ├── mask.json
│ │ │ ├── match.json
│ │ │ ├── matchingDelim.json
│ │ │ ├── MAXIMUM_MESSAGE_SIZE.json
│ │ │ ├── mdcContent.json
│ │ │ ├── MERMAID_DOM_ID_PREFIX.json
│ │ │ ├── message.json
│ │ │ ├── messages.json
│ │ │ ├── meth.json
│ │ │ ├── minimatch.json
│ │ │ ├── MOCK_CONSTRUCTOR_NAME.json
│ │ │ ├── MOCKS_PATTERN.json
│ │ │ ├── moduleDirectory.json
│ │ │ ├── msg.json
│ │ │ ├── mtr.json
│ │ │ ├── multipartType.json
│ │ │ ├── n.json
│ │ │ ├── N.json
│ │ │ ├── name.json
│ │ │ ├── NATIVE_PLATFORM.json
│ │ │ ├── newUrl.json
│ │ │ ├── NM.json
│ │ │ ├── NO_ARGUMENTS.json
│ │ │ ├── NO_DIFF_MESSAGE.json
│ │ │ ├── NODE_MODULES.json
│ │ │ ├── nodeInternalPrefix.json
│ │ │ ├── nonASCIIidentifierStartChars.json
│ │ │ ├── nonKey.json
│ │ │ ├── NOT_A_DOT.json
│ │ │ ├── notCharacterOrDash.json
│ │ │ ├── notebookURL.json
│ │ │ ├── notSelector.json
│ │ │ ├── nullTag.json
│ │ │ ├── num.json
│ │ │ ├── NUMBER.json
│ │ │ ├── o.json
│ │ │ ├── O.json
│ │ │ ├── octChar.json
│ │ │ ├── octetStreamType.json
│ │ │ ├── operators.json
│ │ │ ├── out.json
│ │ │ ├── OUTSIDE_JEST_VM_PROTOCOL.json
│ │ │ ├── override.json
│ │ │ ├── p.json
│ │ │ ├── PACKAGE_FILENAME.json
│ │ │ ├── PACKAGE_JSON.json
│ │ │ ├── packageVersion.json
│ │ │ ├── paddedNumber.json
│ │ │ ├── page.json
│ │ │ ├── parseClass.json
│ │ │ ├── path.json
│ │ │ ├── pathExt.json
│ │ │ ├── pattern.json
│ │ │ ├── PatternBoolean.json
│ │ │ ├── pBuiltins.json
│ │ │ ├── pFloatForm.json
│ │ │ ├── pkg.json
│ │ │ ├── PLUGIN_ID_DOC_MANAGER.json
│ │ │ ├── plusChar.json
│ │ │ ├── PN_CHARS.json
│ │ │ ├── point.json
│ │ │ ├── prefix.json
│ │ │ ├── PRETTY_PLACEHOLDER.json
│ │ │ ├── property_prefix.json
│ │ │ ├── pubkey256.json
│ │ │ ├── Q.json
│ │ │ ├── qmark.json
│ │ │ ├── QO.json
│ │ │ ├── query.json
│ │ │ ├── querystringType.json
│ │ │ ├── queryText.json
│ │ │ ├── r.json
│ │ │ ├── R.json
│ │ │ ├── rangeStart.json
│ │ │ ├── re.json
│ │ │ ├── reI.json
│ │ │ ├── REQUIRED_FIELD_SYMBOL.json
│ │ │ ├── reserve.json
│ │ │ ├── resolvedDestination.json
│ │ │ ├── resolverDir.json
│ │ │ ├── responseType.json
│ │ │ ├── result.json
│ │ │ ├── ROOT_DESCRIBE_BLOCK_NAME.json
│ │ │ ├── ROOT_NAMESPACE_NAME.json
│ │ │ ├── ROOT_TASK_NAME.json
│ │ │ ├── route.json
│ │ │ ├── RUNNING_TEXT.json
│ │ │ ├── s.json
│ │ │ ├── SCHEMA_PATH.json
│ │ │ ├── se.json
│ │ │ ├── SEARCHABLE_CLASS.json
│ │ │ ├── secret.json
│ │ │ ├── selector.json
│ │ │ ├── SEMVER_SPEC_VERSION.json
│ │ │ ├── sensitiveHeaders.json
│ │ │ ├── sep.json
│ │ │ ├── separator.json
│ │ │ ├── SHAPE_STATE.json
│ │ │ ├── shape.json
│ │ │ ├── SHARED.json
│ │ │ ├── short.json
│ │ │ ├── side.json
│ │ │ ├── SNAPSHOT_VERSION.json
│ │ │ ├── SOURCE_MAPPING_PREFIX.json
│ │ │ ├── source.json
│ │ │ ├── sourceMapContent.json
│ │ │ ├── SPACE_SYMBOL.json
│ │ │ ├── SPACE.json
│ │ │ ├── sqlKeywords.json
│ │ │ ├── sranges.json
│ │ │ ├── st.json
│ │ │ ├── ST.json
│ │ │ ├── stack.json
│ │ │ ├── START_HIDING.json
│ │ │ ├── START_OF_LINE.json
│ │ │ ├── startNoTraversal.json
│ │ │ ├── STATES.json
│ │ │ ├── stats.json
│ │ │ ├── statSync.json
│ │ │ ├── storageStatus.json
│ │ │ ├── storageType.json
│ │ │ ├── str.json
│ │ │ ├── stringifiedObject.json
│ │ │ ├── stringPath.json
│ │ │ ├── stringResult.json
│ │ │ ├── stringTag.json
│ │ │ ├── strValue.json
│ │ │ ├── style.json
│ │ │ ├── SUB_NAME.json
│ │ │ ├── subkey.json
│ │ │ ├── SUBPROTOCOL.json
│ │ │ ├── SUITE_NAME.json
│ │ │ ├── symbolPattern.json
│ │ │ ├── symbolTag.json
│ │ │ ├── t.json
│ │ │ ├── T.json
│ │ │ ├── templateDir.json
│ │ │ ├── tempName.json
│ │ │ ├── text.json
│ │ │ ├── time.json
│ │ │ ├── titleSeparator.json
│ │ │ ├── tmpl.json
│ │ │ ├── tn.json
│ │ │ ├── toValue.json
│ │ │ ├── transform.json
│ │ │ ├── trustProxyDefaultSymbol.json
│ │ │ ├── typeArgumentsKey.json
│ │ │ ├── typeKey.json
│ │ │ ├── typeMessage.json
│ │ │ ├── typesRegistryPackageName.json
│ │ │ ├── u.json
│ │ │ ├── UNDEFINED.json
│ │ │ ├── unit.json
│ │ │ ├── UNMATCHED_SURROGATE_PAIR_REPLACE.json
│ │ │ ├── ur.json
│ │ │ ├── USAGE.json
│ │ │ ├── value.json
│ │ │ ├── Vr.json
│ │ │ ├── watchmanURL.json
│ │ │ ├── webkit.json
│ │ │ ├── xhtml.json
│ │ │ ├── XP_DEFAULT_PATHEXT.json
│ │ │ └── y.json
│ │ ├── Collaborative_Development_with_MCP_Integration.json
│ │ ├── colorCode.json
│ │ ├── comma.json
│ │ ├── command.json
│ │ ├── completionShTemplate.json
│ │ ├── configJsContent.json
│ │ ├── connectionString.json
│ │ ├── Consolidated_TypeScript_Interfaces_Template.json
│ │ ├── Could_you_interpret_the_assumed_applicat___.json
│ │ ├── cssClassStr.json
│ │ ├── currentBoundaryParse.json
│ │ ├── d.json
│ │ ├── Data_Analysis_Template.json
│ │ ├── data.json
│ │ ├── DATA.json
│ │ ├── Database_Query_Assistant.json
│ │ ├── dataWebpackPrefix.json
│ │ ├── debug.json
│ │ ├── Debugging_Assistant.json
│ │ ├── decodeStateVectorV2.json
│ │ ├── DEFAULT_DELIMITER.json
│ │ ├── DEFAULT_DIAGRAM_DIRECTION.json
│ │ ├── DEFAULT_INDENT.json
│ │ ├── DEFAULT_JS_PATTERN.json
│ │ ├── DEFAULT_LOG_TARGET.json
│ │ ├── defaultHelpOpt.json
│ │ ├── defaultHost.json
│ │ ├── deferY18nLookupPrefix.json
│ │ ├── DELIM.json
│ │ ├── delimiter.json
│ │ ├── DEPRECATION.json
│ │ ├── DESCENDING.json
│ │ ├── destMain.json
│ │ ├── development
│ │ │ ├── Collaborative_Development_with_MCP_Integration.json
│ │ │ ├── Consolidated_TypeScript_Interfaces_Template.json
│ │ │ ├── Development_Workflow.json
│ │ │ ├── index.json
│ │ │ ├── MCP_Server_Development_Prompt_Combiner.json
│ │ │ └── Monorepo_Migration_and_Code_Organization_Guide.json
│ │ ├── Development_System_Prompt.json
│ │ ├── Development_Workflow.json
│ │ ├── devops
│ │ │ ├── Docker_Compose_Prompt_Combiner.json
│ │ │ ├── Docker_Containerization_Guide.json
│ │ │ └── index.json
│ │ ├── DID_NOT_THROW.json
│ │ ├── direction.json
│ │ ├── displayValue.json
│ │ ├── DNS.json
│ │ ├── doc.json
│ │ ├── Docker_Compose_Prompt_Combiner.json
│ │ ├── Docker_Containerization_Guide.json
│ │ ├── Docker_MCP_Servers_Orchestration_Guide.json
│ │ ├── DOCUMENTATION_NOTE.json
│ │ ├── DOT.json
│ │ ├── DOTS.json
│ │ ├── dummyCompoundId.json
│ │ ├── e.json
│ │ ├── E.json
│ │ ├── earlyHintsLink.json
│ │ ├── elide.json
│ │ ├── EMPTY.json
│ │ ├── encoded.json
│ │ ├── end.json
│ │ ├── endpoint.json
│ │ ├── environment.json
│ │ ├── ERR_CODE.json
│ │ ├── errMessage.json
│ │ ├── errMsg.json
│ │ ├── ERROR_MESSAGE.json
│ │ ├── error.json
│ │ ├── ERROR.json
│ │ ├── ERRORCLASS.json
│ │ ├── errorMessage.json
│ │ ├── es6Default.json
│ │ ├── ESC.json
│ │ ├── Escapable.json
│ │ ├── escapedChar.json
│ │ ├── escapeFuncStr.json
│ │ ├── escSlash.json
│ │ ├── ev.json
│ │ ├── event.json
│ │ ├── execaMessage.json
│ │ ├── EXPECTED_LABEL.json
│ │ ├── expected.json
│ │ ├── expectedString.json
│ │ ├── expression1.json
│ │ ├── EXTENSION.json
│ │ ├── f.json
│ │ ├── FAIL_TEXT.json
│ │ ├── FILE_BROWSER_FACTORY.json
│ │ ├── fill.json
│ │ ├── findPackageJson.json
│ │ ├── fnKey.json
│ │ ├── Foresight_Assistant.json
│ │ ├── FORMAT.json
│ │ ├── formatted.json
│ │ ├── from.json
│ │ ├── fullpaths.json
│ │ ├── FUNC_ERROR_TEXT.json
│ │ ├── general
│ │ │ └── index.json
│ │ ├── Generate_different_types_of_questions_ab___.json
│ │ ├── Generate_Mermaid_Diagram.json
│ │ ├── GenStateSuspendedStart.json
│ │ ├── GENSYNC_EXPECTED_START.json
│ │ ├── GitHub_Repository_Explorer.json
│ │ ├── gutter.json
│ │ ├── h.json
│ │ ├── handlerFuncName.json
│ │ ├── HASH_UNDEFINED.json
│ │ ├── head.json
│ │ ├── helpMessage.json
│ │ ├── HINT_ARG.json
│ │ ├── HOOK_RETURNED_NOTHING_ERROR_MESSAGE.json
│ │ ├── i.json
│ │ ├── id.json
│ │ ├── identifier.json
│ │ ├── Identifier.json
│ │ ├── INDENT.json
│ │ ├── indentation.json
│ │ ├── index.json
│ │ ├── INDIRECTION_FRAGMENT.json
│ │ ├── Initialize_project_setup_for_a_new_micro___.json
│ │ ├── input.json
│ │ ├── inputText.json
│ │ ├── insert.json
│ │ ├── insertPromptQuery.json
│ │ ├── INSPECT_MAX_BYTES.json
│ │ ├── install_dependencies__build__run__test____.json
│ │ ├── intToCharMap.json
│ │ ├── IS_ITERABLE_SENTINEL.json
│ │ ├── IS_KEYED_SENTINEL.json
│ │ ├── isConfigType.json
│ │ ├── isoSentinel.json
│ │ ├── isSourceNode.json
│ │ ├── j.json
│ │ ├── J.json
│ │ ├── JAKE_CMD.json
│ │ ├── JEST_GLOBAL_NAME.json
│ │ ├── JEST_GLOBALS_MODULE_NAME.json
│ │ ├── JSON_SYNTAX_CHAR.json
│ │ ├── json.json
│ │ ├── jsonType.json
│ │ ├── jupyter_namespaceObject.json
│ │ ├── JUPYTERLAB_DOCMANAGER_PLUGIN_ID.json
│ │ ├── k.json
│ │ ├── KERNEL_STATUS_ERROR_CLASS.json
│ │ ├── key.json
│ │ ├── l.json
│ │ ├── labelId.json
│ │ ├── LATEST_PROTOCOL_VERSION.json
│ │ ├── LETTERDASHNUMBER.json
│ │ ├── LF.json
│ │ ├── LIMIT_REPLACE_NODE.json
│ │ ├── LINE_FEED.json
│ │ ├── logTime.json
│ │ ├── lstatkey.json
│ │ ├── lt.json
│ │ ├── m.json
│ │ ├── maliciousPayload.json
│ │ ├── manager.py
│ │ ├── marker.json
│ │ ├── mask.json
│ │ ├── match.json
│ │ ├── matchingDelim.json
│ │ ├── MAXIMUM_MESSAGE_SIZE.json
│ │ ├── MCP_Integration_Assistant.json
│ │ ├── MCP_Resources_Explorer.json
│ │ ├── MCP_Resources_Integration_Guide.json
│ │ ├── MCP_Server_Development_Prompt_Combiner.json
│ │ ├── MCP_Server_Integration_Guide.json
│ │ ├── mcp-code-generator.json
│ │ ├── mdcContent.json
│ │ ├── Mermaid_Analysis_Expert.json
│ │ ├── Mermaid_Class_Diagram_Generator.json
│ │ ├── Mermaid_Diagram_Generator.json
│ │ ├── Mermaid_Diagram_Modifier.json
│ │ ├── MERMAID_DOM_ID_PREFIX.json
│ │ ├── message.json
│ │ ├── messages.json
│ │ ├── meth.json
│ │ ├── minimatch.json
│ │ ├── MOBILE_QUERY.json
│ │ ├── MOCK_CONSTRUCTOR_NAME.json
│ │ ├── MOCKS_PATTERN.json
│ │ ├── Modify_Mermaid_Diagram.json
│ │ ├── moduleDirectory.json
│ │ ├── Monorepo_Migration_and_Code_Organization_Guide.json
│ │ ├── msg.json
│ │ ├── mtr.json
│ │ ├── Multi-Resource_Context_Assistant.json
│ │ ├── multipartType.json
│ │ ├── n.json
│ │ ├── N.json
│ │ ├── name.json
│ │ ├── NATIVE_PLATFORM.json
│ │ ├── newUrl.json
│ │ ├── NM.json
│ │ ├── NO_ARGUMENTS.json
│ │ ├── NO_DIFF_MESSAGE.json
│ │ ├── NODE_MODULES.json
│ │ ├── nodeInternalPrefix.json
│ │ ├── nonASCIIidentifierStartChars.json
│ │ ├── nonKey.json
│ │ ├── NOT_A_DOT.json
│ │ ├── notCharacterOrDash.json
│ │ ├── notebookURL.json
│ │ ├── notSelector.json
│ │ ├── nullTag.json
│ │ ├── num.json
│ │ ├── NUMBER.json
│ │ ├── o.json
│ │ ├── O.json
│ │ ├── octChar.json
│ │ ├── octetStreamType.json
│ │ ├── operators.json
│ │ ├── other
│ │ │ ├── __image_1___describe_the_icon_in_one_sen___.json
│ │ │ ├── __type.json
│ │ │ ├── Advanced_Multi-Server_Integration_Template.json
│ │ │ ├── Analyze_Mermaid_Diagram.json
│ │ │ ├── Basic_Template.json
│ │ │ ├── Code_Diagram_Documentation_Creator.json
│ │ │ ├── Collaborative_Development_with_MCP_Integration.json
│ │ │ ├── completionShTemplate.json
│ │ │ ├── Could_you_interpret_the_assumed_applicat___.json
│ │ │ ├── DEFAULT_INDENT.json
│ │ │ ├── Docker_MCP_Servers_Orchestration_Guide.json
│ │ │ ├── Generate_different_types_of_questions_ab___.json
│ │ │ ├── Generate_Mermaid_Diagram.json
│ │ │ ├── GitHub_Repository_Explorer.json
│ │ │ ├── index.json
│ │ │ ├── Initialize_project_setup_for_a_new_micro___.json
│ │ │ ├── install_dependencies__build__run__test____.json
│ │ │ ├── LINE_FEED.json
│ │ │ ├── MCP_Resources_Explorer.json
│ │ │ ├── MCP_Resources_Integration_Guide.json
│ │ │ ├── MCP_Server_Integration_Guide.json
│ │ │ ├── mcp-code-generator.json
│ │ │ ├── Mermaid_Class_Diagram_Generator.json
│ │ │ ├── Mermaid_Diagram_Generator.json
│ │ │ ├── Mermaid_Diagram_Modifier.json
│ │ │ ├── Modify_Mermaid_Diagram.json
│ │ │ ├── Multi-Resource_Context_Assistant.json
│ │ │ ├── output.json
│ │ │ ├── sseUrl.json
│ │ │ ├── string.json
│ │ │ ├── Task_List_Helper.json
│ │ │ ├── Template-Based_MCP_Integration.json
│ │ │ ├── Test_Prompt.json
│ │ │ ├── type.json
│ │ │ ├── VERSION.json
│ │ │ ├── WIN_SLASH.json
│ │ │ └── You_are_limited_to_respond_Yes_or_No_onl___.json
│ │ ├── out.json
│ │ ├── output.json
│ │ ├── OUTSIDE_JEST_VM_PROTOCOL.json
│ │ ├── override.json
│ │ ├── p.json
│ │ ├── PACKAGE_FILENAME.json
│ │ ├── PACKAGE_JSON.json
│ │ ├── packageVersion.json
│ │ ├── paddedNumber.json
│ │ ├── page.json
│ │ ├── parseClass.json
│ │ ├── PATH_NODE_MODULES.json
│ │ ├── path.json
│ │ ├── pathExt.json
│ │ ├── pattern.json
│ │ ├── PatternBoolean.json
│ │ ├── pBuiltins.json
│ │ ├── pFloatForm.json
│ │ ├── pkg.json
│ │ ├── PLUGIN_ID_DOC_MANAGER.json
│ │ ├── plusChar.json
│ │ ├── PN_CHARS.json
│ │ ├── point.json
│ │ ├── prefix.json
│ │ ├── PRETTY_PLACEHOLDER.json
│ │ ├── Project_Analysis_Assistant.json
│ │ ├── ProjectsUpdatedInBackgroundEvent.json
│ │ ├── PromptCombiner_Interface.json
│ │ ├── promptId.json
│ │ ├── property_prefix.json
│ │ ├── pubkey256.json
│ │ ├── Q.json
│ │ ├── qmark.json
│ │ ├── QO.json
│ │ ├── query.json
│ │ ├── querystringType.json
│ │ ├── queryText.json
│ │ ├── r.json
│ │ ├── R.json
│ │ ├── rangeStart.json
│ │ ├── re.json
│ │ ├── reI.json
│ │ ├── REQUIRED_FIELD_SYMBOL.json
│ │ ├── Research_Assistant.json
│ │ ├── reserve.json
│ │ ├── resolvedDestination.json
│ │ ├── resolverDir.json
│ │ ├── responseType.json
│ │ ├── result.json
│ │ ├── ROOT_DESCRIBE_BLOCK_NAME.json
│ │ ├── ROOT_NAMESPACE_NAME.json
│ │ ├── ROOT_TASK_NAME.json
│ │ ├── route.json
│ │ ├── RUNNING_TEXT.json
│ │ ├── RXstyle.json
│ │ ├── s.json
│ │ ├── SCHEMA_PATH.json
│ │ ├── schemaQuery.json
│ │ ├── se.json
│ │ ├── SEARCHABLE_CLASS.json
│ │ ├── secret.json
│ │ ├── selector.json
│ │ ├── SEMVER_SPEC_VERSION.json
│ │ ├── sensitiveHeaders.json
│ │ ├── sep.json
│ │ ├── separator.json
│ │ ├── Sequential_Data_Analysis_with_MCP_Integration.json
│ │ ├── SHAPE_STATE.json
│ │ ├── shape.json
│ │ ├── SHARED.json
│ │ ├── short.json
│ │ ├── side.json
│ │ ├── SNAPSHOT_VERSION.json
│ │ ├── SOLID_Code_Analysis_Visualizer.json
│ │ ├── SOURCE_MAPPING_PREFIX.json
│ │ ├── source.json
│ │ ├── sourceMapContent.json
│ │ ├── SPACE_SYMBOL.json
│ │ ├── SPACE.json
│ │ ├── sqlKeywords.json
│ │ ├── sranges.json
│ │ ├── sseUrl.json
│ │ ├── st.json
│ │ ├── ST.json
│ │ ├── stack.json
│ │ ├── START_HIDING.json
│ │ ├── START_OF_LINE.json
│ │ ├── startNoTraversal.json
│ │ ├── STATES.json
│ │ ├── stats.json
│ │ ├── statSync.json
│ │ ├── status.json
│ │ ├── storageStatus.json
│ │ ├── storageType.json
│ │ ├── str.json
│ │ ├── string.json
│ │ ├── stringifiedObject.json
│ │ ├── stringPath.json
│ │ ├── stringResult.json
│ │ ├── stringTag.json
│ │ ├── strValue.json
│ │ ├── style.json
│ │ ├── SUB_NAME.json
│ │ ├── subkey.json
│ │ ├── SUBPROTOCOL.json
│ │ ├── SUITE_NAME.json
│ │ ├── symbolPattern.json
│ │ ├── symbolTag.json
│ │ ├── system
│ │ │ ├── Aa.json
│ │ │ ├── b.json
│ │ │ ├── Development_System_Prompt.json
│ │ │ ├── index.json
│ │ │ ├── marker.json
│ │ │ ├── PATH_NODE_MODULES.json
│ │ │ ├── ProjectsUpdatedInBackgroundEvent.json
│ │ │ ├── RXstyle.json
│ │ │ ├── status.json
│ │ │ └── versionMajorMinor.json
│ │ ├── t.json
│ │ ├── T.json
│ │ ├── Task_List_Helper.json
│ │ ├── Template-Based_MCP_Integration.json
│ │ ├── template.py
│ │ ├── templateDir.json
│ │ ├── tempName.json
│ │ ├── Test_Prompt.json
│ │ ├── text.json
│ │ ├── time.json
│ │ ├── titleSeparator.json
│ │ ├── tmpl.json
│ │ ├── tn.json
│ │ ├── TOPBAR_FACTORY.json
│ │ ├── toValue.json
│ │ ├── transform.json
│ │ ├── trustProxyDefaultSymbol.json
│ │ ├── txt.json
│ │ ├── type.json
│ │ ├── typeArgumentsKey.json
│ │ ├── typeKey.json
│ │ ├── typeMessage.json
│ │ ├── typesRegistryPackageName.json
│ │ ├── u.json
│ │ ├── UNDEFINED.json
│ │ ├── unit.json
│ │ ├── UNMATCHED_SURROGATE_PAIR_REPLACE.json
│ │ ├── ur.json
│ │ ├── usage.json
│ │ ├── USAGE.json
│ │ ├── user
│ │ │ ├── backupId.json
│ │ │ ├── DESCENDING.json
│ │ │ ├── encoded.json
│ │ │ ├── index.json
│ │ │ ├── J.json
│ │ │ ├── MOBILE_QUERY.json
│ │ │ ├── promptId.json
│ │ │ ├── schemaQuery.json
│ │ │ ├── TOPBAR_FACTORY.json
│ │ │ ├── txt.json
│ │ │ └── usage.json
│ │ ├── value.json
│ │ ├── VERSION.json
│ │ ├── version.py
│ │ ├── versionMajorMinor.json
│ │ ├── Vr.json
│ │ ├── watchmanURL.json
│ │ ├── webkit.json
│ │ ├── WIN_SLASH.json
│ │ ├── xhtml.json
│ │ ├── XP_DEFAULT_PATHEXT.json
│ │ ├── y.json
│ │ └── You_are_limited_to_respond_Yes_or_No_onl___.json
│ ├── resources
│ │ ├── __init__.py
│ │ ├── code_examples
│ │ │ └── index.json
│ │ ├── config
│ │ │ └── index.json
│ │ ├── documentation
│ │ │ └── index.json
│ │ ├── images
│ │ │ └── index.json
│ │ ├── index.json
│ │ └── other
│ │ └── index.json
│ ├── server.py
│ ├── templates
│ │ ├── __init__.py
│ │ ├── AbstractFactory.json
│ │ ├── Adapter.json
│ │ ├── base.py
│ │ ├── Builder.json
│ │ ├── Chain.json
│ │ ├── Command.json
│ │ ├── component
│ │ │ ├── AbstractFactory.json
│ │ │ ├── Adapter.json
│ │ │ ├── Builder.json
│ │ │ ├── Chain.json
│ │ │ ├── Command.json
│ │ │ ├── Decorator.json
│ │ │ ├── Facade.json
│ │ │ ├── Factory.json
│ │ │ ├── Iterator.json
│ │ │ ├── Mediator.json
│ │ │ ├── Memento.json
│ │ │ ├── Observer.json
│ │ │ ├── Prototype.json
│ │ │ ├── Proxy.json
│ │ │ ├── Singleton.json
│ │ │ ├── State.json
│ │ │ ├── Strategy.json
│ │ │ ├── TemplateMethod.json
│ │ │ └── Visitor.json
│ │ ├── component.py
│ │ ├── Decorator.json
│ │ ├── Facade.json
│ │ ├── Factory.json
│ │ ├── index.json
│ │ ├── Iterator.json
│ │ ├── manager.py
│ │ ├── Mediator.json
│ │ ├── Memento.json
│ │ ├── Observer.json
│ │ ├── project.py
│ │ ├── Prototype.json
│ │ ├── Proxy.json
│ │ ├── renderer.py
│ │ ├── Singleton.json
│ │ ├── State.json
│ │ ├── Strategy.json
│ │ ├── template_manager.py
│ │ ├── TemplateMethod.json
│ │ ├── types.py
│ │ └── Visitor.json
│ └── utils
│ └── __init__.py
├── SUMMARY.md
├── TASK_COMPLETION_SUMMARY.md
├── templates
│ └── openssl
│ ├── files
│ │ ├── CMakeLists.txt.jinja2
│ │ ├── conanfile.py.jinja2
│ │ ├── main.cpp.jinja2
│ │ └── README.md.jinja2
│ ├── openssl-consumer.json
│ └── template.json
├── test_openssl_integration.sh
├── test_package
│ └── conanfile.py
└── tests
├── __init__.py
├── conftest.py
├── integration
│ ├── test_core_integration.py
│ ├── test_mermaid_integration.py
│ ├── test_prompt_manager_integration.py
│ └── test_server_integration.py
├── test_aws_mcp.py
├── test_base_classes.py
├── test_config.py
├── test_exceptions.py
├── test_mermaid.py
├── test_prompts.py
└── test_templates.py
```
# Files
--------------------------------------------------------------------------------
/src/mcp_project_orchestrator/prompts/coding/A.json:
--------------------------------------------------------------------------------
```json
{
"name": "A",
"description": "Prompt template extracted from lexer.js",
"type": "prompt",
"category": "coding",
"content": "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"variables": {},
"metadata": {
"source": "/home/sparrow/projects/mcp-prompts/node_modules/cjs-module-lexer/dist/lexer.js",
"imported": true
}
}
```
--------------------------------------------------------------------------------
/automotive-camera-system/docs/IMPLEMENTACE_CS.md:
--------------------------------------------------------------------------------
```markdown
# Implementační Plán - Automobilový Kamerový Systém
## 🇨🇿 Kompletní Průvodce Implementací v Češtině
### Úvod
Tento dokument poskytuje kompletní návod pro implementaci pokročilého kamerového systému do automobilů s využitím AWS cloudových služeb a edge computing technologií.
## 1. Typy Kamerových Systémů pro Automobily
### 1.1 Základní Zadní Kamera
**Účel**: Asistence při couvání
**Kamery**: 1x zadní kamera
**Funkce**:
- Zobrazení zadního prostoru na displeji
- Vodicí linie pro parkování
- Detekce vzdálenosti od překážek
- Aktivace při zařazení zpátečky
**Implementace**:
```python
class RearViewCamera:
"""
Základní zadní kamera s vodicími liniemi.
Poskytuje real-time zobrazení prostoru za vozidlem s překryvem
vodicích linií založených na úhlu natočení volantu.
"""
def __init__(self, camera_index: int = 0):
self.camera = cv2.VideoCapture(camera_index)
self.camera.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
self.camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
def draw_parking_lines(self, frame: np.ndarray, steering_angle: float) -> np.ndarray:
"""
Vykreslí vodicí linie pro parkování.
Args:
frame: Vstupní video snímek
steering_angle: Úhel natočení volantu v stupních
Returns:
Snímek s vykreslenými vodicími liniemi
"""
height, width = frame.shape[:2]
# Vypočítat trajektorii na základě úhlu natočení
trajectory = self._calculate_trajectory(steering_angle, width, height)
# Vykreslit linie
cv2.polylines(frame, [trajectory], False, (0, 255, 0), 3)
# Zóny vzdálenosti (zelená, žlutá, červená)
self._draw_distance_zones(frame, width, height)
return frame
```
### 1.2 Surround View System (360°)
**Účel**: Kompletní pohled okolo vozidla
**Kamery**: 4-8 kamer (přední, zadní, 2-6x boční)
**Funkce**:
- Bird's eye view (pohled shora)
- 2D/3D zobrazení okolí
- Detekce překážek ve všech směrech
- Asistence při parkování v těsných prostorech
**Implementace**:
```python
class SurroundViewSystem:
"""
360° surround view systém s kalibrací a image stitchingem.
Kombinuje obrazy z více kamer do jednoho seamless bird's eye view.
Používá kalibra
ní parametry pro korekci zkreslení a perspektivní transformaci.
"""
def __init__(self, camera_configs: List[CameraConfig]):
self.cameras = []
self.calibration_data = {}
for config in camera_configs:
camera = self._init_camera(config)
self.cameras.append(camera)
self.calibration_data[config.position] = self._load_calibration(config)
def generate_surround_view(self) -> np.ndarray:
"""
Vygeneruje 360° surround view snímek.
Returns:
np.ndarray: Bird's eye view obraz 1280x720px
"""
frames = []
# Načíst snímky ze všech kamer
for camera in self.cameras:
ret, frame = camera.read()
if ret:
# Korigovat zkreslení
frame = self._undistort(frame, camera.position)
# Aplikovat perspektivní transformaci
frame = self._perspective_transform(frame, camera.position)
frames.append(frame)
# Stitching všech snímků
surround_view = self._stitch_images(frames)
# Overlay s 3D modelem vozidla
surround_view = self._overlay_vehicle_model(surround_view)
return surround_view
def _undistort(self, frame: np.ndarray, position: str) -> np.ndarray:
"""Koriguje zkreslení objektivu pomocí kalibračních parametrů."""
calib = self.calibration_data[position]
return cv2.undistort(frame, calib['camera_matrix'], calib['dist_coeffs'])
def _perspective_transform(self, frame: np.ndarray, position: str) -> np.ndarray:
"""Transformuje perspektivu pro bird's eye view."""
M = self.calibration_data[position]['homography_matrix']
height, width = 720, 1280
return cv2.warpPerspective(frame, M, (width, height))
```
### 1.3 ADAS Kamerový Systém
**Účel**: Pokročilé asistenční systémy
**Kamery**: 1-3 kamery (především přední)
**Funkce**:
- Lane Keep Assist (udržování v pruhu)
- Adaptive Cruise Control (ACC)
- Forward Collision Warning
- Pedestrian Detection
- Traffic Sign Recognition
- Automatic Emergency Braking
**Implementace**:
```python
class ADASCameraSystem:
"""
Pokročilý ADAS systém s detekcí jízdních pruhů a objektů.
Využívá YOLOv8 pro detekci objektů a SCNN pro detekci pruhů.
Optimalizováno pro real-time inference na NVIDIA Jetson.
"""
def __init__(self, model_path: str):
# Načíst optimalizovaný TensorRT model
self.object_detector = YOLO(f"{model_path}/yolov8n.engine")
self.lane_detector = LaneDetectionModel(f"{model_path}/lane_scnn.engine")
# Inicializovat tracking
self.tracker = DeepSORT()
# Inicializovat kalman filtr pro smoothing
self.kalman = cv2.KalmanFilter(4, 2)
def process_frame(self, frame: np.ndarray, vehicle_speed: float) -> Dict:
"""
Zpracuje video snímek a detekuje objekty a pruhy.
Args:
frame: Vstupní RGB snímek 1920x1080
vehicle_speed: Rychlost vozidla v km/h
Returns:
dict: Detekované objekty, pruhy, varování
"""
results = {}
# Detekce objektů (chodci, vozidla, cyklisté)
objects = self.object_detector(frame, conf=0.5, iou=0.4)
results['objects'] = self._process_detections(objects)
# Detekce jízdních pruhů
lanes = self.lane_detector(frame)
results['lanes'] = self._process_lanes(lanes)
# Analýza scény
results['warnings'] = self._analyze_scene(results, vehicle_speed)
# TTC (Time To Collision) výpočet
results['ttc'] = self._calculate_ttc(results['objects'], vehicle_speed)
return results
def _analyze_scene(self, detections: Dict, speed: float) -> List[Warning]:
"""Analyzuje scénu a generuje varování."""
warnings = []
# Lane Departure Warning
if self._is_departing_lane(detections['lanes']):
warnings.append(Warning(type='LDW', severity='HIGH'))
# Forward Collision Warning
for obj in detections['objects']:
if obj['class'] in ['car', 'pedestrian', 'bicycle']:
ttc = obj.get('ttc')
if ttc and ttc < 2.0: # méně než 2 sekundy do kolize
warnings.append(Warning(
type='FCW',
severity='CRITICAL',
object=obj,
ttc=ttc
))
return warnings
```
## 2. Hardware Komponenty
### 2.1 Kamery
#### Wide-Angle Kamery
```yaml
Specifikace:
Rozlišení: 1920x1080 @ 30 FPS minimum
Field of View: 120-170°
Low Light Performance: < 0.1 lux
Interface: USB 3.0 nebo MIPI-CSI
Lens: M12 mount, IR-cut filter
Doporučené modely:
- Arducam IMX219: $30-40, 8MP, 160° FOV
- See3CAM_CU135: $100, 13MP, 100° FOV
- Leopard Imaging LI-IMX390: $150, HDR, 120° FOV (automotive grade)
```
#### Fish-Eye Kamery (pro surround view)
```yaml
Specifikace:
Rozlišení: 1920x1080 @ 30 FPS
Field of View: 185-220°
Distortion: Vysoké zkreslení (vyžaduje calibraci)
Interface: MIPI-CSI preferováno
IP Rating: IP67 pro vnější montáž
Doporučené modely:
- Arducam OV9281: $80, 1MP, 200° FOV
- DFOV (Fisheye): $120, 2MP, 220° FOV
```
### 2.2 Computing Platform
#### NVIDIA Jetson Xavier NX (Doporučeno)
```yaml
Specifikace:
GPU: 384-core NVIDIA Volta
CPU: 6-core ARMv8.2 @ 1.4GHz
Memory: 8GB LPDDR4x
Storage: microSD + NVMe SSD
Power: 10-15W
AI Performance: 21 TOPS
Cena: $400-500
Výhody:
- Nativní CUDA support
- TensorRT optimalizace
- Nízká spotřeba
- Industrial temperature range
```
#### Raspberry Pi 4 (Budget varianta)
```yaml
Specifikace:
CPU: 4-core ARM Cortex-A72 @ 1.5GHz
GPU: VideoCore VI
Memory: 4-8GB LPDDR4
Storage: microSD
Power: 5-8W
Cena: $50-80
Omezení:
- Slabší AI inference (potřeba Coral TPU)
- Max 2-3 kamery současně
- Omezený na základní funkce
```
### 2.3 Další Hardware
```yaml
GPS Module:
Model: u-blox NEO-M9N
Cena: $40
Přesnost: 2m CEP
Update rate: 25 Hz
CAN Bus Interface:
Model: CANable USB adapter
Cena: $30
Protocol: CAN 2.0A/B
Speed: Up to 1 Mbps
Storage:
microSD: Samsung EVO Plus 128GB ($20)
NVMe SSD: 256GB NVMe ($50) pro recordings
Power Supply:
12V DC-DC converter: 5V/5A output
Battery backup: UPS for safe shutdown
Display:
7-10" touchscreen LCD
Resolution: 1024x600 minimum
Cena: $50-100
```
## 3. AWS Cloud Infrastructure
### 3.1 IoT Greengrass Deployment
```python
# greengrass_components/camera_processing/recipe.yaml
---
RecipeFormatVersion: '2020-01-25'
ComponentName: com.automotive.camera.processing
ComponentVersion: '1.0.0'
ComponentDescription: 'Automotive camera processing with object detection'
ComponentPublisher: 'Automotive Systems'
ComponentConfiguration:
DefaultConfiguration:
cameras:
count: 4
resolution: '1920x1080'
fps: 30
models:
object_detection: 'yolov8n.engine'
lane_detection: 'scnn_lane.engine'
processing:
enable_gpu: true
batch_size: 1
max_latency_ms: 100
Manifests:
- Platform:
os: linux
architecture: arm64
Lifecycle:
Install:
Script: |
apt-get update
apt-get install -y python3-opencv
pip3 install ultralytics tensorrt
Run:
Script: python3 {artifacts:path}/camera_processor.py
Artifacts:
- Uri: s3://automotive-camera-artifacts/camera_processor.py
- Uri: s3://automotive-camera-models/yolov8n.engine
- Uri: s3://automotive-camera-models/scnn_lane.engine
```
### 3.2 CloudFormation Stack
```yaml
# infrastructure/cloudformation/camera-system-stack.yaml
AWSTemplateFormatVersion: '2010-09-09'
Description: 'Automotive Camera System Infrastructure'
Parameters:
FleetSize:
Type: Number
Default: 1
Description: 'Number of vehicles in fleet'
VideoRetentionDays:
Type: Number
Default: 30
Description: 'Days to retain video recordings'
Resources:
# IoT Thing Group for vehicle fleet
VehicleFleetThingGroup:
Type: AWS::IoT::ThingGroup
Properties:
ThingGroupName: !Sub '${AWS::StackName}-vehicle-fleet'
ThingGroupProperties:
ThingGroupDescription: 'Fleet of vehicles with camera systems'
AttributePayload:
Attributes:
fleet_size: !Ref FleetSize
# S3 Bucket for video recordings
VideoRecordingsBucket:
Type: AWS::S3::Bucket
Properties:
BucketName: !Sub '${AWS::StackName}-recordings-${AWS::AccountId}'
VersioningConfiguration:
Status: Enabled
LifecycleConfiguration:
Rules:
- Id: ArchiveOldRecordings
Status: Enabled
Transitions:
- TransitionInDays: !Ref VideoRetentionDays
StorageClass: GLACIER
- TransitionInDays: 90
StorageClass: DEEP_ARCHIVE
ExpirationInDays: 365
PublicAccessBlockConfiguration:
BlockPublicAcls: true
BlockPublicPolicy: true
IgnorePublicAcls: true
RestrictPublicBuckets: true
# Kinesis Video Stream for live streaming
CameraLiveStream:
Type: AWS::KinesisVideo::Stream
Properties:
Name: !Sub '${AWS::StackName}-live-stream'
DataRetentionInHours: 24
MediaType: 'video/h264'
# DynamoDB Table for metadata
VideoMetadataTable:
Type: AWS::DynamoDB::Table
Properties:
TableName: !Sub '${AWS::StackName}-video-metadata'
BillingMode: PAY_PER_REQUEST
AttributeDefinitions:
- AttributeName: vehicle_id
AttributeType: S
- AttributeName: timestamp
AttributeType: N
- AttributeName: event_type
AttributeType: S
KeySchema:
- AttributeName: vehicle_id
KeyType: HASH
- AttributeName: timestamp
KeyType: RANGE
GlobalSecondaryIndexes:
- IndexName: event-type-index
KeySchema:
- AttributeName: event_type
KeyType: HASH
- AttributeName: timestamp
KeyType: RANGE
Projection:
ProjectionType: ALL
# Lambda for video processing
VideoProcessingFunction:
Type: AWS::Lambda::Function
Properties:
FunctionName: !Sub '${AWS::StackName}-video-processor'
Runtime: python3.11
Handler: index.lambda_handler
Role: !GetAtt VideoProcessingRole.Arn
Timeout: 300
MemorySize: 3008
Code:
ZipFile: |
import boto3
import json
from datetime import datetime
s3 = boto3.client('s3')
dynamodb = boto3.resource('dynamodb')
rekognition = boto3.client('rekognition')
def lambda_handler(event, context):
"""
Zpracuje nahraný video soubor a extrahuje metadata.
"""
bucket = event['Records'][0]['s3']['bucket']['name']
key = event['Records'][0]['s3']['object']['key']
# Extrahovat metadata z názvu souboru
# Format: vehicle_id/YYYY-MM-DD/HH-MM-SS_event.mp4
parts = key.split('/')
vehicle_id = parts[0]
timestamp = datetime.strptime(parts[2].split('_')[0], '%H-%M-%S')
event_type = parts[2].split('_')[1].replace('.mp4', '')
# Uložit metadata do DynamoDB
table = dynamodb.Table(os.environ['METADATA_TABLE'])
table.put_item(Item={
'vehicle_id': vehicle_id,
'timestamp': int(timestamp.timestamp()),
'event_type': event_type,
's3_key': key,
'processed': False
})
# Spustit video analýzu (async)
rekognition.start_label_detection(
Video={'S3Object': {'Bucket': bucket, 'Name': key}},
NotificationChannel={
'SNSTopicArn': os.environ['SNS_TOPIC_ARN'],
'RoleArn': os.environ['REKOGNITION_ROLE_ARN']
}
)
return {'statusCode': 200}
Environment:
Variables:
METADATA_TABLE: !Ref VideoMetadataTable
SNS_TOPIC_ARN: !Ref AlertTopic
REKOGNITION_ROLE_ARN: !GetAtt RekognitionRole.Arn
# SNS Topic for alerts
AlertTopic:
Type: AWS::SNS::Topic
Properties:
TopicName: !Sub '${AWS::StackName}-alerts'
Subscription:
- Endpoint: !Ref AlertEmail
Protocol: email
# CloudWatch Dashboard
CameraSystemDashboard:
Type: AWS::CloudWatch::Dashboard
Properties:
DashboardName: !Sub '${AWS::StackName}-dashboard'
DashboardBody: !Sub |
{
"widgets": [
{
"type": "metric",
"properties": {
"metrics": [
["AWS/IoT", "PublishIn.Success", {"stat": "Sum"}],
[".", "PublishIn.Failure", {"stat": "Sum"}]
],
"period": 300,
"stat": "Sum",
"region": "${AWS::Region}",
"title": "IoT Messages"
}
},
{
"type": "metric",
"properties": {
"metrics": [
["CameraSystem", "ObjectDetections", {"stat": "Sum"}],
[".", "LaneDetections", {"stat": "Sum"}]
],
"period": 60,
"stat": "Sum",
"region": "${AWS::Region}",
"title": "Detection Metrics"
}
}
]
}
Outputs:
RecordingsBucketName:
Value: !Ref VideoRecordingsBucket
Export:
Name: !Sub '${AWS::StackName}-recordings-bucket'
LiveStreamName:
Value: !GetAtt CameraLiveStream.Name
Export:
Name: !Sub '${AWS::StackName}-live-stream'
```
## 4. Deployment Procedure
### 4.1 Příprava Hardware
```bash
#!/bin/bash
# scripts/setup-jetson.sh
set -euo pipefail
echo "=== Automotive Camera System - Jetson Setup ==="
# 1. Update system
sudo apt-get update
sudo apt-get upgrade -y
# 2. Install JetPack SDK components
sudo apt-get install -y \
nvidia-jetpack \
python3-pip \
python3-opencv \
v4l-utils \
can-utils
# 3. Install Python dependencies
pip3 install --upgrade pip
pip3 install \
boto3 \
awsiotsdk \
ultralytics \
torch \
torchvision \
numpy \
scipy
# 4. Install TensorRT
pip3 install nvidia-tensorrt
# 5. Configure cameras
echo "Detecting cameras..."
v4l2-ctl --list-devices
# 6. Install AWS IoT Greengrass
curl -s https://d2s8p88vqu9w66.cloudfront.net/releases/greengrass-nucleus-latest.zip > greengrass-nucleus-latest.zip
unzip greengrass-nucleus-latest.zip -d GreengrassInstaller
sudo -E java -Droot="/greengrass/v2" -Dlog.store=FILE \
-jar ./GreengrassInstaller/lib/Greengrass.jar \
--aws-region eu-central-1 \
--thing-name VehicleCameraSystem \
--thing-group-name vehicle-fleet \
--tes-role-name GreengrassV2TokenExchangeRole \
--tes-role-alias-name GreengrassCoreTokenExchangeRoleAlias \
--component-default-user ggc_user:ggc_group \
--provision true \
--setup-system-service true
# 7. Configure CAN interface
sudo ip link set can0 up type can bitrate 500000
sudo ifconfig can0 txqueuelen 1000
# 8. Create systemd service
cat > /tmp/automotive-camera.service <<EOF
[Unit]
Description=Automotive Camera System
After=network.target greengrass.service
[Service]
Type=simple
User=ggc_user
WorkingDirectory=/home/ggc_user/automotive-camera
ExecStart=/usr/bin/python3 /home/ggc_user/automotive-camera/src/main.py
Restart=always
RestartSec=10
[Install]
WantedBy=multi-user.target
EOF
sudo mv /tmp/automotive-camera.service /etc/systemd/system/
sudo systemctl daemon-reload
sudo systemctl enable automotive-camera.service
echo "Setup complete!"
echo "Next steps:"
echo "1. Calibrate cameras: python3 tools/calibrate_cameras.py"
echo "2. Deploy Greengrass components: aws greengrassv2 create-deployment"
echo "3. Start system: sudo systemctl start automotive-camera"
```
### 4.2 Camera Calibration
```python
# tools/calibrate_cameras.py
"""
Nástroj pro kalibraci kamer surround view systému.
Použití:
python calibrate_cameras.py --cameras 4 --pattern chessboard --size 9x6
"""
import cv2
import numpy as np
import argparse
import json
from pathlib import Path
class CameraCalibrator:
"""
Kalibrace kamer pomocí šachovnicového vzoru.
Proces:
1. Zachytí série snímků šachovnice z různých úhlů
2. Detekuje rohy šachovnice
3. Vypočítá intrinsic parametry kamery (focal length, principal point)
4. Vypočítá distortion koeficienty
5. Uloží kalibrační data pro každou kameru
"""
def __init__(self, pattern_size: tuple = (9, 6), square_size: float = 25.0):
"""
Args:
pattern_size: Počet vnitřních rohů (columns, rows)
square_size: Velikost čtverce v mm
"""
self.pattern_size = pattern_size
self.square_size = square_size
# Připravit object points
self.objp = np.zeros((pattern_size[0] * pattern_size[1], 3), np.float32)
self.objp[:, :2] = np.mgrid[0:pattern_size[0], 0:pattern_size[1]].T.reshape(-1, 2)
self.objp *= square_size
def calibrate(self, camera_index: int, num_images: int = 20) -> dict:
"""
Kalibruje kameru zachycením série snímků.
Args:
camera_index: Index kamery (0-3 pro 4 kamery)
num_images: Počet snímků pro kalibraci
Returns:
dict: Kalibrační parametry (camera_matrix, dist_coeffs, rvecs, tvecs)
"""
cap = cv2.VideoCapture(camera_index)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
obj_points = [] # 3D body v reálném světě
img_points = [] # 2D body v obraze
captured = 0
print(f"Calibrating camera {camera_index}...")
print(f"Position the chessboard pattern in view and press SPACE to capture")
print(f"Need {num_images} images. Press 'q' to quit.")
while captured < num_images:
ret, frame = cap.read()
if not ret:
continue
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Najít rohy šachovnice
ret, corners = cv2.findChessboardCorners(gray, self.pattern_size, None)
# Vykresl it náhled
display = frame.copy()
if ret:
cv2.drawChessboardCorners(display, self.pattern_size, corners, ret)
cv2.putText(display, "Pattern found! Press SPACE", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
else:
cv2.putText(display, "Move pattern into view", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
cv2.putText(display, f"Captured: {captured}/{num_images}", (10, 70),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
cv2.imshow(f'Camera {camera_index} Calibration', display)
key = cv2.waitKey(1) & 0xFF
if key == ord('q'):
break
elif key == ord(' ') and ret:
# Zpřesnit detekci rohů
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
corners_refined = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
obj_points.append(self.objp)
img_points.append(corners_refined)
captured += 1
print(f"Captured image {captured}/{num_images}")
cap.release()
cv2.destroyAllWindows()
if captured < 10:
raise ValueError("Not enough calibration images captured (minimum 10)")
# Vypočítat kalibrační parametry
print("Computing calibration parameters...")
ret, camera_matrix, dist_coeffs, rvecs, tvecs = cv2.calibrateCamera(
obj_points, img_points, gray.shape[::-1], None, None
)
# Vypočítat reprojection error
mean_error = 0
for i in range(len(obj_points)):
img_points2, _ = cv2.projectPoints(obj_points[i], rvecs[i], tvecs[i],
camera_matrix, dist_coeffs)
error = cv2.norm(img_points[i], img_points2, cv2.NORM_L2) / len(img_points2)
mean_error += error
mean_error /= len(obj_points)
print(f"Mean reprojection error: {mean_error:.4f} pixels")
if mean_error > 1.0:
print("WARNING: High reprojection error. Consider recalibrating.")
return {
'camera_matrix': camera_matrix.tolist(),
'dist_coeffs': dist_coeffs.tolist(),
'rvecs': [r.tolist() for r in rvecs],
'tvecs': [t.tolist() for t in tvecs],
'reprojection_error': float(mean_error),
'image_size': [1920, 1080],
'calibrated_at': datetime.now().isoformat()
}
def compute_homography(self, camera_data: dict, camera_position: str) -> np.ndarray:
"""
Vypočítá homography matrix pro bird's eye view transformaci.
Args:
camera_data: Kalibrační data kamery
camera_position: Pozice kamery ('front', 'rear', 'left', 'right')
Returns:
np.ndarray: 3x3 homography matrix
"""
# Definovat zdrojové body v obraze kamery
# a cílové body v bird's eye view
if camera_position == 'front':
src_points = np.float32([
[400, 400], # Levý dolní roh
[1520, 400], # Pravý dolní roh
[1520, 800], # Pravý horní roh
[400, 800] # Levý horní roh
])
dst_points = np.float32([
[320, 0],
[960, 0],
[960, 720],
[320, 720]
])
elif camera_position == 'rear':
src_points = np.float32([
[400, 800],
[1520, 800],
[1520, 400],
[400, 400]
])
dst_points = np.float32([
[320, 720],
[960, 720],
[960, 0],
[320, 0]
])
# ... podobně pro 'left' a 'right'
# Vypočítat homography
H, _ = cv2.findHomography(src_points, dst_points)
return H
def main():
parser = argparse.ArgumentParser(description='Camera calibration tool')
parser.add_argument('--cameras', type=int, default=4, help='Number of cameras')
parser.add_argument('--pattern', default='chessboard', help='Calibration pattern')
parser.add_argument('--size', default='9x6', help='Pattern size (e.g., 9x6)')
parser.add_argument('--output', default='calibration', help='Output directory')
args = parser.parse_args()
# Parse pattern size
cols, rows = map(int, args.size.split('x'))
pattern_size = (cols, rows)
# Create calibrator
calibrator = CameraCalibrator(pattern_size=pattern_size)
# Create output directory
output_dir = Path(args.output)
output_dir.mkdir(exist_ok=True)
# Calibrate each camera
camera_positions = ['front', 'rear', 'left', 'right']
for i in range(args.cameras):
position = camera_positions[i] if i < len(camera_positions) else f'camera{i}'
print(f"\n=== Calibrating {position} camera (index {i}) ===")
calibration_data = calibrator.calibrate(camera_index=i)
# Compute homography for surround view
homography = calibrator.compute_homography(calibration_data, position)
calibration_data['homography_matrix'] = homography.tolist()
calibration_data['position'] = position
# Save calibration data
output_file = output_dir / f'{position}_calibration.json'
with open(output_file, 'w') as f:
json.dump(calibration_data, f, indent=2)
print(f"Calibration saved to {output_file}")
print("\n=== Calibration Complete ===")
print(f"Calibration files saved in: {output_dir}")
print("Next step: Deploy the camera system")
if __name__ == '__main__':
main()
```
## 5. Cost Analysis
### 5.1 Development Costs
| Položka | Cena (Kč) | Poznámka |
|---------|-----------|----------|
| NVIDIA Jetson Xavier NX | 10,000 | Computing platform |
| 4x Wide-angle kamery | 8,000 | Arducam nebo podobné |
| GPS modul | 1,000 | u-blox NEO-M9N |
| CAN Bus adapter | 800 | CANable USB |
| microSD 128GB | 500 | Samsung EVO Plus |
| NVMe SSD 256GB | 1,200 | Pro recordings |
| Display 7" | 2,000 | Touchscreen LCD |
| Kabeláž a konektory | 1,500 | FAKRA, USB kabely |
| Napájecí systém | 1,000 | 12V DC-DC converter |
| **Celkem hardware** | **26,000 Kč** | (~$1,100) |
| | | |
| Vývoj software (200h) | 400,000 | @ 2,000 Kč/h |
| Testing & validace (50h) | 100,000 | @ 2,000 Kč/h |
| Dokumentace (20h) | 40,000 | @ 2,000 Kč/h |
| **Celkem vývoj** | **540,000 Kč** | (~$23,000) |
### 5.2 Operating Costs (Monthly per vehicle)
| AWS Service | Cena (Kč/měsíc) | Poznámka |
|-------------|-----------------|----------|
| IoT Core | 15-50 | Telemetry messages |
| Kinesis Video | 120-240 | 1h streaming/day |
| S3 Storage | 50-120 | 30-day retention |
| Lambda | 25-50 | Event processing |
| Data Transfer | 120-240 | Upload recordings |
| CloudWatch | 25-50 | Logs & metrics |
| **Celkem AWS** | **355-750 Kč** | (~$15-32/month) |
### 5.3 ROI Calculation
```python
# Výpočet návratnosti investice
# Předpoklady
development_cost = 540_000 # Kč
hardware_per_vehicle = 26_000 # Kč
aws_monthly_per_vehicle = 550 # Kč (průměr)
installation_cost = 5_000 # Kč per vehicle
# Scénář: Fleet 100 vozidel
num_vehicles = 100
total_initial_investment = (
development_cost +
(hardware_per_vehicle + installation_cost) * num_vehicles
)
print(f"Initial investment: {total_initial_investment:,} Kč")
# = 540,000 + 3,100,000 = 3,640,000 Kč (~$155,000)
# Monthly operating costs
monthly_operating = aws_monthly_per_vehicle * num_vehicles
print(f"Monthly operating: {monthly_operating:,} Kč")
# = 55,000 Kč/month (~$2,350)
# Break-even analysis
# Pokud prodáváme systém za 50,000 Kč per vozidlo
selling_price = 50_000 # Kč
total_revenue = selling_price * num_vehicles # 5,000,000 Kč
profit = total_revenue - total_initial_investment
print(f"Profit after initial deployment: {profit:,} Kč")
# = 1,360,000 Kč (~$58,000)
# Payback period (months)
monthly_profit_per_vehicle = selling_price - hardware_per_vehicle - installation_cost - aws_monthly_per_vehicle * 12
payback_period = development_cost / (monthly_profit_per_vehicle * num_vehicles / 12)
print(f"Payback period: {payback_period:.1f} months")
```
## 6. Regulatory Compliance
### 6.1 EU Regulations
```markdown
## UN R46 - Camera Monitor Systems
Požadavky:
- Field of view: minimálně 20m za vozidlem
- Display lag: max 200ms
- Display resolution: min 480x240 px
- Aktivace: automatická při zpětném chodu
- Životnost: 5,000 hodin provozu
Compliance checklist:
- [x] FOV > 20m (150° širokoúhlá kamera)
- [x] Latence < 100ms (real-time processing)
- [x] Rozlišení 1280x720 (výrazně nad minimum)
- [x] Auto-aktivace přes CAN bus signal
- [x] Industrial-grade komponenty
```
### 6.2 GDPR Compliance
```python
class PrivacyFilter:
"""
GDPR-compliant privacy filter pro automatické rozmazání obličejů.
Detekuje a rozmazává obličeje osob v záznamu před nahráním do cloudu.
Zachovává metadata pro forensic analysis.
"""
def __init__(self):
# Použít lightweight face detection model
self.face_detector = cv2.CascadeClassifier(
cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
)
def anonymize_frame(self, frame: np.ndarray) -> np.ndarray:
"""
Anonymizuje frame rozmazáním obličejů.
Args:
frame: Input RGB frame
Returns:
Anonymized frame with blurred faces
"""
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Detekovat obličeje
faces = self.face_detector.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30)
)
# Rozmazat každý obličej
for (x, y, w, h) in faces:
# Extrahovat ROI
face_roi = frame[y:y+h, x:x+w]
# Aplikovat Gaussian blur
blurred_face = cv2.GaussianBlur(face_roi, (99, 99), 30)
# Vložit zpět
frame[y:y+h, x:x+w] = blurred_face
return frame
```
## 7. Testing & Validation
### 7.1 HIL (Hardware-in-the-Loop) Testing
```python
# tests/hil/test_camera_system.py
"""
Hardware-in-the-Loop testy pro automotive kamerový systém.
"""
import pytest
import time
import numpy as np
from automotive_camera import SurroundViewSystem, ADASSystem
@pytest.fixture
def camera_system():
"""Inicializuje camera system pro testing."""
return SurroundViewSystem(cameras=4)
class TestSurroundView:
"""Testy pro surround view systém."""
def test_camera_initialization(self, camera_system):
"""Test inicializace všech kamer."""
assert len(camera_system.cameras) == 4
for cam in camera_system.cameras:
assert cam.isOpened()
def test_frame_acquisition(self, camera_system):
"""Test získání frame ze všech kamer."""
frames = camera_system.get_frames()
assert len(frames) == 4
for frame in frames:
assert frame.shape == (1080, 1920, 3)
def test_surround_view_generation(self, camera_system):
"""Test generování surround view."""
surround = camera_system.generate_surround_view()
# Zkontrolovat rozlišení
assert surround.shape == (720, 1280, 3)
# Zkontrolovat že není černý frame
assert np.mean(surround) > 10
def test_latency(self, camera_system):
"""Test latence zpracování."""
times = []
for _ in range(100):
start = time.time()
_ = camera_system.generate_surround_view()
elapsed = (time.time() - start) * 1000 # ms
times.append(elapsed)
avg_latency = np.mean(times)
max_latency = np.max(times)
print(f"Average latency: {avg_latency:.2f}ms")
print(f"Max latency: {max_latency:.2f}ms")
# Assert latence požadavky
assert avg_latency < 50, "Average latency too high"
assert max_latency < 100, "Max latency exceeds requirement"
def test_fps(self, camera_system):
"""Test framerate."""
start = time.time()
frames = 0
while time.time() - start < 10: # 10 sekund test
_ = camera_system.generate_surround_view()
frames += 1
fps = frames / (time.time() - start)
print(f"FPS: {fps:.1f}")
assert fps >= 30, "FPS below requirement"
class TestADAS:
"""Testy pro ADAS funkce."""
def test_object_detection(self):
"""Test detekce objektů."""
adas = ADASSystem()
# Load test image s vozidlem
test_image = cv2.imread('tests/data/car_front.jpg')
results = adas.detect_objects(test_image)
# Zkontrolovat že detekoval auto
assert any(obj['class'] == 'car' for obj in results)
# Zkontrolovat confidence
car_detections = [obj for obj in results if obj['class'] == 'car']
assert all(obj['confidence'] > 0.5 for obj in car_detections)
def test_lane_detection(self):
"""Test detekce jízdních pruhů."""
adas = ADASSystem()
test_image = cv2.imread('tests/data/highway.jpg')
lanes = adas.detect_lanes(test_image)
# Zkontrolovat že detekoval alespoň 2 pruhy
assert len(lanes) >= 2
# Zkontrolovat že jsou relativně rovnoběžné
slopes = [lane['slope'] for lane in lanes]
assert max(slopes) - min(slopes) < 0.5
```
### 7.2 Performance Benchmarks
```python
# tests/benchmarks/benchmark_inference.py
"""
Performance benchmarking pro ML inference.
"""
import time
import numpy as np
from automotive_camera.models import YOLODetector, LaneDetector
def benchmark_yolo():
"""Benchmark YOLO object detection."""
detector = YOLODetector(model_path='models/yolov8n.engine')
# Dummy input
dummy_frame = np.random.randint(0, 255, (1080, 1920, 3), dtype=np.uint8)
# Warmup
for _ in range(10):
_ = detector.detect(dummy_frame)
# Benchmark
times = []
for _ in range(1000):
start = time.perf_counter()
results = detector.detect(dummy_frame)
elapsed = (time.perf_counter() - start) * 1000
times.append(elapsed)
print(f"\n=== YOLO Inference Benchmark ===")
print(f"Average: {np.mean(times):.2f}ms")
print(f"Median: {np.median(times):.2f}ms")
print(f"P95: {np.percentile(times, 95):.2f}ms")
print(f"P99: {np.percentile(times, 99):.2f}ms")
print(f"Max: {np.max(times):.2f}ms")
print(f"FPS: {1000 / np.mean(times):.1f}")
def benchmark_lane():
"""Benchmark lane detection."""
detector = LaneDetector(model_path='models/scnn_lane.engine')
dummy_frame = np.random.randint(0, 255, (1080, 1920, 3), dtype=np.uint8)
# Warmup
for _ in range(10):
_ = detector.detect(dummy_frame)
# Benchmark
times = []
for _ in range(1000):
start = time.perf_counter()
results = detector.detect(dummy_frame)
elapsed = (time.perf_counter() - start) * 1000
times.append(elapsed)
print(f"\n=== Lane Detection Benchmark ===")
print(f"Average: {np.mean(times):.2f}ms")
print(f"P95: {np.percentile(times, 95):.2f}ms")
print(f"FPS: {1000 / np.mean(times):.1f}")
if __name__ == '__main__':
benchmark_yolo()
benchmark_lane()
```
## 8. Production Deployment Checklist
```markdown
## Pre-Deployment
- [ ] Hardware commissioning
- [ ] All cameras working and calibrated
- [ ] Jetson Xavier configured and tested
- [ ] Power supply validated (12V → 5V conversion)
- [ ] CAN bus communication verified
- [ ] GPS lock confirmed
- [ ] Software validation
- [ ] All tests passing (unit + integration + HIL)
- [ ] Performance benchmarks meeting targets
- [ ] Memory leaks checked (valgrind)
- [ ] Power consumption measured (<15W)
- [ ] AWS infrastructure
- [ ] IoT thing provisioned and certificates installed
- [ ] Greengrass components deployed
- [ ] S3 buckets created with lifecycle policies
- [ ] CloudWatch alarms configured
- [ ] IAM roles and policies verified
## Installation
- [ ] Vehicle preparation
- [ ] Camera mounting positions marked
- [ ] Wiring harness routed
- [ ] Computing unit mounted in dry, ventilated area
- [ ] Display integrated into dashboard
- [ ] System integration
- [ ] CAN bus tapped (with proper isolation)
- [ ] Power connected through fused circuit
- [ ] Ground connections solid
- [ ] Cameras aimed and focused
- [ ] Calibration
- [ ] Camera intrinsic calibration completed
- [ ] Homography matrices calculated
- [ ] Surround view stitching verified
- [ ] ADAS calibration (if applicable)
## Testing & Validation
- [ ] Functional tests
- [ ] All camera views displaying correctly
- [ ] Surround view seamless stitching
- [ ] Object detection working
- [ ] Lane detection accurate
- [ ] Recording and playback functional
- [ ] Integration tests
- [ ] CAN bus data received correctly
- [ ] GPS position accurate
- [ ] Cloud connectivity established
- [ ] Firmware OTA update tested
- [ ] Road tests
- [ ] Parking scenarios (tight spaces, angles)
- [ ] Highway driving (lane keeping, FCW)
- [ ] Various lighting conditions (day, night, tunnel)
- [ ] Weather conditions (rain, fog if possible)
## Documentation
- [ ] User manual delivered
- [ ] Installation guide provided
- [ ] Maintenance schedule defined
- [ ] Warranty terms documented
- [ ] Emergency procedures outlined
## Handover
- [ ] Customer training completed
- [ ] System demonstration performed
- [ ] Support contacts provided
- [ ] Feedback mechanism established
- [ ] Final acceptance signed
```
---
**Dokument vytvořen**: 2025-10-01
**Verze**: 1.0.0
**Autor**: MCP Project Orchestrator
**Jazyk**: Čeština
Pro další informace nebo podporu kontaktujte: [email protected]
```