mirror of
https://github.com/azaion/detections.git
synced 2026-04-22 05:26:32 +00:00
Fixed dynamic ONNX input
Fix dynamic ONNX input Update docs with correct file name for tests
This commit is contained in:
Roman Meshko
@@ -0,0 +1,187 @@
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# Codex Context Bridge
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This file is a compact compatibility layer for Codex. It explains how the repository uses `.cursor/`, where project memory lives, and what should be read first in a new chat.
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## First Read Order
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When starting a new Codex session in this repository, read in this order:
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1. `AGENTS.md`
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2. `.cursor/CODEX_CONTEXT.md`
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3. `_docs/_autopilot_state.md`
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4. The skill file relevant to the user's request under `.cursor/skills/*/SKILL.md`
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5. Only the `_docs/` artifacts and `.cursor/rules/*.mdc` files relevant to that request
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Do not bulk-read all of `_docs/` or all skill files unless the task truly needs it.
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## Mental Model
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- `.cursor/` is the workflow engine, policy layer, and skill library
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- `_docs/` is the persisted working memory for the project
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- `src/`, `tests/`, `e2e/`, and related runtime files are the implementation layer
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For Codex, the important distinction is:
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- `.cursor/` tells you **how the team wants work to happen**
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- `_docs/` tells you **what has already been decided or completed**
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## Project Snapshot
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- Product: `Azaion.Detections`
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- Type: Python/Cython microservice for aerial object detection
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- API: FastAPI + SSE
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- Engines: TensorRT on compatible NVIDIA GPUs, ONNX Runtime fallback
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- Main code areas: `src/`, `tests/`, `e2e/`, `scripts/`
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- Workflow memory: `_docs/`
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Relevant documented architecture:
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- 4 components: Domain, Inference Engines, Inference Pipeline, API
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- 10 documented modules under `_docs/02_document/modules/`
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- External services: Loader service, Annotations service
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## Current Workflow State
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As of `2026-04-15`, the persisted workflow state says:
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- Flow: `existing-code`
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- Current step: `2`
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- Current step name: `Test Spec`
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- Current status: `in_progress`
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- Current sub-step: `Phase 3 - Test Data Validation Gate`
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Important rollback note from `_docs/_autopilot_state.md`:
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- On `2026-04-10`, the workflow was rolled back from Step 8 (`New Task`) to Step 2 (`Test Spec`)
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- Reason: expected-result artifacts were incomplete for verification
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Concrete blocker confirmed from current files:
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- `_docs/00_problem/input_data/expected_results/results_report.md` still contains `?` for most expected detection counts
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- Per-file expected-result CSVs for non-empty datasets are header-only
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- That means black-box tests cannot verify detection correctness yet
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Practical unblocker:
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1. Populate the expected-result CSVs for the non-empty image/video fixtures
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2. Replace `?` counts in `results_report.md` with real values
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3. Re-run or continue the `test-spec` workflow from Phase 3
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## Cursor Asset Map
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### Core entry points
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- `.cursor/README.md`: high-level overview of the whole Cursor system
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- `.cursor/skills/autopilot/SKILL.md`: orchestrator contract
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- `.cursor/skills/autopilot/flows/existing-code.md`: active flow for this repository
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- `.cursor/skills/autopilot/protocols.md`: decision, retry, and re-entry rules
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- `.cursor/agents/implementer.md`: only defined subagent
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### Rules
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Always-check rules:
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- `.cursor/rules/meta-rule.mdc`
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- `.cursor/rules/techstackrule.mdc`
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- `.cursor/rules/git-workflow.mdc`
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- `.cursor/rules/quality-gates.mdc`
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Highly relevant contextual rules for this repo:
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- `.cursor/rules/python.mdc`
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- `.cursor/rules/testing.mdc`
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- `.cursor/rules/docker.mdc`
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- `.cursor/rules/cursor-meta.mdc`
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Other rules exist for security, trackers, OpenAPI, React, Rust, SQL, and .NET. Read them only if the task touches those domains.
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## Skills Index
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Use this table as the fast map instead of opening every skill up front.
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| Skill | Primary use | Main outputs |
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|------|-------------|--------------|
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| `autopilot` | Continue the end-to-end workflow | state progression in `_docs/_autopilot_state.md` |
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| `problem` | Gather or refine the problem definition | `_docs/00_problem/` |
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| `research` | Investigate solutions or unknowns | `_docs/01_solution/` or standalone research folder |
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| `plan` | Architecture, components, risks, tests, epics | `_docs/02_document/` |
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| `test-spec` | Black-box test specifications and test runners | `_docs/02_document/tests/`, `scripts/run-tests.sh`, `scripts/run-performance-tests.sh` |
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| `decompose` | Break plan or tests into atomic tasks | `_docs/02_tasks/` |
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| `implement` | Batch orchestration of coding tasks | `_docs/03_implementation/` plus code changes |
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| `test-run` | Execute and diagnose test suites | test results and pass/fail guidance |
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| `code-review` | Review implemented batches against specs | review report and verdict |
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| `new-task` | Plan new functionality for existing code | `_docs/02_tasks/todo/` and optional `_docs/02_task_plans/` |
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| `refactor` | Structured refactoring with safety checks | `_docs/04_refactoring/` |
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| `security` | Security audit and OWASP-style review | `_docs/05_security/` |
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| `document` | Reverse-engineer or update docs from code | `_docs/02_document/` and related problem/solution docs |
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| `deploy` | Containerization, CI/CD, observability | `_docs/04_deploy/` |
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| `retrospective` | Review implementation metrics and trends | `_docs/06_metrics/` |
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| `ui-design` | UI mockups and design system artifacts | `_docs/02_document/ui_mockups/` |
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## Agents
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Defined agent:
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- `implementer`
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- File: `.cursor/agents/implementer.md`
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- Role: implement one task spec with tests and AC verification
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- Invoked by: `implement` skill
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No other `.cursor/agents/` definitions are currently present.
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## Codex Operating Notes
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### When the user asks for Cursor-style continuation
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If the user says things like:
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- "continue autopilot"
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- "what's next"
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- "continue workflow"
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- "/autopilot"
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then:
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1. Read `_docs/_autopilot_state.md`
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2. Read `.cursor/skills/autopilot/SKILL.md`
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3. Read `.cursor/skills/autopilot/protocols.md`
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4. Read the active flow file
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5. Read only the specific downstream skill file needed for the current step
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### When the user asks for direct coding help
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You do not need to force the full Cursor workflow. Work directly in the codebase, but still:
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- respect `.cursor/rules/*.mdc`
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- use `_docs/` as authoritative project memory
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- preserve alignment with existing task specs and documented architecture when relevant
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### Context discipline
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- Prefer progressive loading over reading everything
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- Treat disk artifacts as the source of truth, not prior chat history
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- Cross-check state file claims against actual files when something seems inconsistent
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## Most Relevant Files For This Repo
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- `AGENTS.md`
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- `.cursor/CODEX_CONTEXT.md`
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- `.cursor/README.md`
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- `.cursor/skills/autopilot/SKILL.md`
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- `.cursor/skills/autopilot/flows/existing-code.md`
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- `.cursor/skills/test-spec/SKILL.md`
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- `.cursor/agents/implementer.md`
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- `_docs/_autopilot_state.md`
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- `_docs/00_problem/`
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- `_docs/01_solution/solution.md`
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- `_docs/02_document/`
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- `_docs/02_tasks/`
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## Short Version
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If you only have a minute:
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- This repo uses Cursor as a workflow framework and `_docs/` as persistent memory
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- The project is already documented and mid-workflow
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- The current workflow is blocked in `test-spec` because expected-result data is incomplete
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- For future Codex chats, start with `AGENTS.md`, this file, and `_docs/_autopilot_state.md`
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@@ -80,3 +80,6 @@ data/
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# Runtime logs
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Logs/
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#IDEA
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.idea/
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@@ -49,9 +49,9 @@ For videos, the additional field:
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| # | Input File | Description | Expected Result File | Notes |
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|---|------------|-------------|---------------------|-------|
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| 7 | `video_short01.mp4` | Standard test video | `video_short01_expected.csv` | Primary async/SSE/video test. List key-frame detections. |
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| 8 | `video_short02.mp4` | Video variant | `video_short02_expected.csv` | Used for resilience and concurrent tests |
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| 9 | `video_long03.mp4` | Long video (288MB), generates >100 SSE events | `video_long03_expected.csv` | SSE overflow test. Only key-frame samples needed. |
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| 7 | `video_test01.mp4` | Standard test video | `video_test01_expected.csv` | Primary async/SSE/video test. List key-frame detections. |
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| 8 | `video_1.mp4` | Video variant | `video_1_expected.csv` | Secondary local fixture for resilience and concurrent-style validation. |
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| 9 | `video_1_faststart.mp4` | Faststart video variant | `video_1_faststart_expected.csv` | Streaming compatibility variant. Separate long-video overflow fixture is not currently present in local fixtures. |
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## How to Fill
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@@ -12,9 +12,9 @@
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| image-dense-02 | `input_data/image_dense02.jpg` | JPEG 1920×1080 — dense scene variant, borderline tiling | FT-P-06 (variant) | Volume mount to consumer `/media/` | N/A (read-only) |
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| image-different-types | `input_data/image_different_types.jpg` | JPEG 900×1600 — varied object classes for class variant tests | FT-P-13 | Volume mount to consumer `/media/` | N/A (read-only) |
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| image-empty-scene | `input_data/image_empty_scene.jpg` | JPEG 1920×1080 — clean scene with no detectable objects | Edge case (zero detections) | Volume mount to consumer `/media/` | N/A (read-only) |
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| video-short-01 | `input_data/video_short01.mp4` | MP4 video — standard async/SSE/video detection tests | FT-P-08..12, FT-N-04, 07, NFT-PERF-04, NFT-RES-02, NFT-SEC-03 | Volume mount to consumer `/media/` | N/A (read-only) |
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| video-short-02 | `input_data/video_short02.mp4` | MP4 video — variant for concurrent and resilience tests | NFT-RES-02 (variant), NFT-RES-04 | Volume mount to consumer `/media/` | N/A (read-only) |
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| video-long-03 | `input_data/video_long03.mp4` | MP4 long video (288MB) — generates >100 SSE events for overflow tests | FT-N-08, NFT-RES-LIM-02 | Volume mount to consumer `/media/` | N/A (read-only) |
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| video-test-01 | `input_data/video_test01.mp4` | MP4 video — standard async/SSE/video detection tests | FT-P-08..12, FT-N-04, 07, NFT-PERF-04, NFT-RES-02, NFT-SEC-03 | Volume mount to consumer `/media/` | N/A (read-only) |
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| video-1 | `input_data/video_1.mp4` | MP4 video — local variant for concurrent and resilience-style tests | NFT-RES-02 (variant), NFT-RES-04 | Volume mount to consumer `/media/` | N/A (read-only) |
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| video-1-faststart | `input_data/video_1_faststart.mp4` | MP4 video — faststart/local streaming variant | Streaming compatibility checks | Volume mount to consumer `/media/` | N/A (read-only) |
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| empty-image | Generated at build time | Zero-byte file | FT-N-01 | Generated in e2e/fixtures/ | N/A |
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| corrupt-image | Generated at build time | Random binary garbage (not valid image format) | FT-N-02 | Generated in e2e/fixtures/ | N/A |
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| jwt-token | Generated at runtime | Valid JWT with exp claim (not signature-verified by detections) | FT-P-08, 09, FT-N-04, 07, NFT-SEC-03 | Generated by consumer at runtime | N/A |
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@@ -35,9 +35,9 @@ Each test run starts with fresh containers (`docker compose down -v && docker co
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| image_dense02.jpg | `_docs/00_problem/input_data/image_dense02.jpg` | Dense scene 1920×1080 | Dedup variant |
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| image_different_types.jpg | `_docs/00_problem/input_data/image_different_types.jpg` | Varied classes 900×1600 | Class variant tests |
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| image_empty_scene.jpg | `_docs/00_problem/input_data/image_empty_scene.jpg` | Empty scene 1920×1080 | Zero-detection edge case |
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| video_short01.mp4 | `_docs/00_problem/input_data/video_short01.mp4` | Standard video | Async, SSE, video, perf tests |
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| video_short02.mp4 | `_docs/00_problem/input_data/video_short02.mp4` | Video variant | Resilience, concurrent tests |
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| video_long03.mp4 | `_docs/00_problem/input_data/video_long03.mp4` | Long video (288MB) | SSE overflow, queue depth tests |
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| video_test01.mp4 | `_docs/00_problem/input_data/video_test01.mp4` | Standard video | Async, SSE, video, perf tests |
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| video_1.mp4 | `_docs/00_problem/input_data/video_1.mp4` | Video variant | Resilience, concurrent tests |
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| video_1_faststart.mp4 | `_docs/00_problem/input_data/video_1_faststart.mp4` | Faststart video variant | Streaming compatibility checks |
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| classes.json | repo root `classes.json` | 19 detection classes | All tests |
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## External Dependency Mocks
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@@ -1,3 +1,4 @@
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cimport constants_inf
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from loader_http_client cimport LoaderHttpClient, LoadResult
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@@ -42,7 +43,6 @@ class EngineFactory:
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def build_and_cache(self, bytes source_bytes, LoaderHttpClient loader_client, str models_dir):
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cdef LoadResult res
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import constants_inf
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engine_bytes, engine_filename = self.build_from_source(source_bytes, loader_client, models_dir)
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res = loader_client.upload_big_small_resource(engine_bytes, engine_filename, models_dir)
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if res.err is not None:
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@@ -56,7 +56,6 @@ class OnnxEngineFactory(EngineFactory):
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return OnnxEngine(model_bytes)
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def get_source_filename(self):
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import constants_inf
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return constants_inf.AI_ONNX_MODEL_FILE
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@@ -81,7 +80,6 @@ class TensorRTEngineFactory(EngineFactory):
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return TensorRTEngine.get_engine_filename()
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def get_source_filename(self):
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import constants_inf
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return constants_inf.AI_ONNX_MODEL_FILE
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def build_from_source(self, onnx_bytes, loader_client, models_dir):
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@@ -8,6 +8,8 @@ cdef class OnnxEngine(InferenceEngine):
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cdef object model_inputs
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cdef str input_name
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cdef object input_shape
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cdef object _resolved_input_hw
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cdef tuple _resolve_input_hw(self, object metadata)
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cdef tuple get_input_shape(self)
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cdef run(self, input_data)
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@@ -2,6 +2,7 @@ from engines.inference_engine cimport InferenceEngine
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import onnxruntime as onnx
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cimport constants_inf
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import ast
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import os
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def _select_providers():
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@@ -29,15 +30,40 @@ cdef class OnnxEngine(InferenceEngine):
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model_meta = self.session.get_modelmeta()
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constants_inf.log(f"Metadata: {model_meta.custom_metadata_map}")
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self._resolved_input_hw = self._resolve_input_hw(model_meta.custom_metadata_map)
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self._cpu_session = None
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if any("CoreML" in p for p in self.session.get_providers()):
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constants_inf.log(<str>'CoreML active — creating CPU fallback session')
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self._cpu_session = onnx.InferenceSession(
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model_bytes, providers=["CPUExecutionProvider"])
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cdef tuple _resolve_input_hw(self, object metadata):
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cdef object h = self.input_shape[2] if len(self.input_shape) > 2 else None
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cdef object w = self.input_shape[3] if len(self.input_shape) > 3 else None
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cdef int resolved_h
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cdef int resolved_w
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if isinstance(h, int) and h > 0 and isinstance(w, int) and w > 0:
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return <tuple>(h, w)
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try:
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imgsz = metadata.get("imgsz") if metadata is not None else None
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if imgsz:
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parsed = ast.literal_eval(imgsz)
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if isinstance(parsed, (list, tuple)) and len(parsed) == 2:
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resolved_h = int(parsed[0])
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resolved_w = int(parsed[1])
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if resolved_h > 0 and resolved_w > 0:
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return <tuple>(resolved_h, resolved_w)
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except Exception:
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pass
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# Dynamic ONNX models are expected to use the project's canonical 1280x1280 input.
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return <tuple>(1280, 1280)
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cdef tuple get_input_shape(self):
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shape = self.input_shape
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return <tuple>(shape[2], shape[3])
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return self._resolved_input_hw
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cdef run(self, input_data):
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try:
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Reference in New Issue
Block a user