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DeepKnowledge1 merged 2 commits into
feat/tensorrt-int8-light-patchcorefrom
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Aug 17, 2026
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uiol;'#154
DeepKnowledge1 merged 2 commits into
feat/tensorrt-int8-light-patchcorefrom
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@DeepKnowledge1 DeepKnowledge1 commented Aug 17, 2026

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🔗 Related Issue

Fixes #

📝 Description

🔄 Type of Change

  • 🐛 Bug fix (non-breaking change which fixes an issue)
  • 🚀 New feature (non-breaking change which adds functionality)
  • 💥 Breaking change (fix or feature that would cause existing functionality to not work as expected)
  • 📖 Documentation update
  • 🏗️ Infrastructure / CI/CD update

🧪 Hardware & Matrix Testing

I have successfully built and tested this code using uv on:

  • anomavision[cpu] (Standard/Edge)
  • anomavision[cu121] (CUDA 12.1)
  • anomavision[cu124] (CUDA 12.4)
  • anomavision[cu118] (CUDA 11.8)

Host OS used for testing:

  • Linux / Ubuntu
  • Windows (Native or WSL2)
  • macOS

✅ Developer Checklist

  • My code follows the core style guidelines of this project (Ruff/Black formatting).
  • I have run uv run pytest and all unit tests pass locally.
  • Lockfile Guard: If I added or modified a dependency in pyproject.toml, I have run uv lock --python 3.10 and committed the updated uv.lock file.
  • I have added tests that prove my fix is effective or that my feature works.
  • I have updated the documentation accordingly (if applicable).

📸 Screenshots / Visual Proof (Optional)

@DeepKnowledge1
Feat/tensorrt int8 light patchcore (#152)
66e6446 
## 🔗 Related Issue
Fixes #

## 📝 Description
-
-
-

## 🔄 Type of Change
- [ ] 🐛 Bug fix (non-breaking change which fixes an issue)
- [x] 🚀 New feature (non-breaking change which adds functionality)
- [ ] 💥 Breaking change (fix or feature that would cause existing
functionality to not work as expected)
- [ ] 📖 Documentation update
- [ ] 🏗️ Infrastructure / CI/CD update

## 🧪 Hardware & Matrix Testing
**I have successfully built and tested this code using `uv` on:**
- [x] `anomavision[cpu]` (Standard/Edge)
- [ ] `anomavision[cu121]` (CUDA 12.1)
- [ ] `anomavision[cu124]` (CUDA 12.4)
- [ ] `anomavision[cu118]` (CUDA 11.8)

**Host OS used for testing:**
- [ ] Linux / Ubuntu
- [ ] Windows (Native or WSL2)
- [ ] macOS

## ✅ Developer Checklist
- [x] My code follows the core style guidelines of this project
(Ruff/Black formatting).
- [x] I have run `uv run pytest` and all unit tests pass locally.
- [x] **Lockfile Guard:** If I added or modified a dependency in
`pyproject.toml`, I have run `uv lock --python 3.10` and committed the
updated `uv.lock` file.
- [x] I have added tests that prove my fix is effective or that my
feature works.
- [x] I have updated the documentation accordingly (if applicable).

## 📸 Screenshots / Visual Proof (Optional)
@DeepKnowledge1
Feat/tensorrt int8 light patchcore (#153)
e7cf41e 
## 🔗 Related Issue
Fixes #

## 📝 Description
-
-
-

## 🔄 Type of Change
- [ ] 🐛 Bug fix (non-breaking change which fixes an issue)
- [ ] 🚀 New feature (non-breaking change which adds functionality)
- [ ] 💥 Breaking change (fix or feature that would cause existing
functionality to not work as expected)
- [ ] 📖 Documentation update
- [ ] 🏗️ Infrastructure / CI/CD update

## 🧪 Hardware & Matrix Testing
**I have successfully built and tested this code using `uv` on:**
- [ ] `anomavision[cpu]` (Standard/Edge)
- [ ] `anomavision[cu121]` (CUDA 12.1)
- [ ] `anomavision[cu124]` (CUDA 12.4)
- [ ] `anomavision[cu118]` (CUDA 11.8)

**Host OS used for testing:**
- [ ] Linux / Ubuntu
- [ ] Windows (Native or WSL2)
- [ ] macOS

## ✅ Developer Checklist
- [ ] My code follows the core style guidelines of this project
(Ruff/Black formatting).
- [ ] I have run `uv run pytest` and all unit tests pass locally.
- [ ] **Lockfile Guard:** If I added or modified a dependency in
`pyproject.toml`, I have run `uv lock --python 3.10` and committed the
updated `uv.lock` file.
- [ ] I have added tests that prove my fix is effective or that my
feature works.
- [ ] I have updated the documentation accordingly (if applicable).

## 📸 Screenshots / Visual Proof (Optional)
@DeepKnowledge1
DeepKnowledge1 merged commit d78db38 into feat/tensorrt-int8-light-patchcore Aug 17, 2026
9 checks passed
DeepKnowledge1 added a commit that referenced this pull request Aug 17, 2026
@DeepKnowledge1
uiol;' (#154) (#155)
91dbd47 
## Pull Request: Production-ready TensorRT/INT8 export, ultra-light
PatchCore, and Production Autopilot

### Summary

This pull request merges `feat/tensorrt-int8-light-patchcore` into
`main`. It adds production-oriented anomaly-detection capabilities,
improves deployment workflows, strengthens benchmarking, and makes the
project easier for new users to evaluate.

### What changed

#### Native TensorRT and INT8 export

- Added native TensorRT engine export with FP16 and FP32 support.
- Added calibrated INT8 TensorRT export using real normal calibration
images.
- Added dynamic batch profiles and configurable TensorRT workspace
limits.
- Added calibration-cache support and engine validation.
- Added automatic conversion support for compact PaDiM and PatchCore
deployment artifacts.
- Updated the configuration template and deployment documentation with
the new export parameters.

#### Ultra-light PatchCore

- Added a production-oriented PatchCore implementation designed for
bounded memory and predictable inference.
- Added deterministic k-center coreset selection.
- Added configurable memory-bank limits, pooled patch grids, and chunked
nearest-neighbor search.
- Added support for CLI training, validation, testing, inference,
export, and configuration workflows consistent with PaDiM.
- Restored PatchCore localization output and corrected threshold and
boundary-color behavior.

#### Production Autopilot

- Added a hardware-aware CLI workflow that compares PaDiM and
ultra-light PatchCore.
- Added algorithm-specific threshold calibration using the complete
labeled test split by default.
- Added image-level and pixel-level AUROC reporting when valid targets
are available.
- Added localization-health diagnostics, including anomaly coverage and
normal-image false-positive localization.
- Added median and P95 latency profiling.
- Added model selection based on accuracy, latency, and production
constraints.
- Added a self-contained HTML deployment dashboard, deployment manifest,
localization report, and selected model package.

Example:

```bash
anomavision autopilot \
  --config config.yml \
  --padim_model ./distributions/padim/bottle/anomav_exp/model.pt \
  --patchcore_model ./distributions/patchcore/bottle/anomav_exp/model.pt \
  --device cpu \
  --validation_split 1.0 \
  --target_latency_ms 50 \
  --output_dir ./production_package
```

#### Documentation and adoption improvements

- Added a five-minute CPU quickstart that does not require CUDA.
- Added copy-ready examples for CPU PaDiM, ultra-light PatchCore, and
TensorRT INT8 export.
- Improved README navigation, visual explanations, Autopilot guidance,
and CI visibility.
- Added reproducible benchmark instructions and P95 latency reporting.
- Updated the public repository description and GitHub topic tags for
improved discoverability.
- Added direct links to the live demo, quickstart, examples, and
benchmark methodology.

#### Release preparation

- Bumped the package version from `3.4.0` to `3.5.0`.
- Updated `uv.lock` to match the new package version.
- The existing release workflow is configured to build the package,
publish it to PyPI through trusted publishing, and attach artifacts to
the GitHub release.

### Validation

The complete repository validation suite passes:

```text
black       Passed
isort       Passed
flake8      Passed
pytest      Passed
```

The final branch is clean and synchronized with the remote feature
branch.

### Compatibility and deployment notes

- CPU installation and inference remain supported.
- CUDA and TensorRT export require the corresponding NVIDIA software
stack.
- INT8 export requires real, representative normal calibration images.
- TensorRT engines should be validated on the target GPU and TensorRT
runtime.
- PaDiM and PatchCore use different score scales; their thresholds must
be calibrated separately.
- Existing users should review the updated configuration template before
upgrading.

### Recommended merge and release sequence

1. Review and merge this pull request into `main`.
2. Confirm the package version is `3.5.0` on `main`.
3. Create and publish a GitHub release tagged `v3.5.0`.
4. Allow the release workflow to build and publish the package to PyPI
and attach the artifacts.

### Checklist

- [x] Native TensorRT FP16/FP32 export added.
- [x] Calibrated TensorRT INT8 export added.
- [x] Ultra-light PatchCore added and documented.
- [x] Production Autopilot added.
- [x] Threshold and localization behavior corrected.
- [x] README and deployment documentation updated.
- [x] CPU quickstart and runnable examples added.
- [x] P95 benchmark reporting added.
- [x] Package version updated to `3.5.0`.
- [x] Full pre-commit validation passed.
- [ ] Merge into `main`.
- [ ] Create GitHub release `v3.5.0`.
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@DeepKnowledge1