chore: bump version to 0.4.2, update changelog

CUDA base image downgraded to 12.8.1 (driver 570 compatibility fix),
benchmark script added.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

.github/workflows/docker-publish.yml

@@ -2,7 +2,7 @@ name: Publish Docker Image
 
 on:
   push:
-    branches: ["main", "dev"]
+    branches: ["dev"]
     paths-ignore:
       - "**.md"
       - "docs/**"
@@ -15,6 +15,16 @@ on:
       - "uv-cpu.lock"
       - "uv-rocm.lock"
       - "uv-intel.lock"
+  workflow_call:
+    inputs:
+      tag:
+        type: string
+        required: false
+        description: "Release tag, e.g. v0.4.1 — triggers :latest + versioned image tags"
+      version:
+        type: string
+        required: false
+        description: "Version string without v prefix, e.g. 0.4.1"
 
 concurrency:
   group: docker-${{ github.ref }}
@@ -50,6 +60,8 @@ jobs:
 
       - name: Checkout repository
         uses: actions/checkout@v6
+        with:
+          ref: ${{ inputs.tag || github.ref }}
 
       - name: Set up QEMU
         if: matrix.platform == 'linux/arm64'
@@ -65,6 +77,15 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
+      - name: Compute build version
+        id: version
+        run: |
+          if [ -n "${{ inputs.version }}" ]; then
+            echo "value=${{ inputs.version }}" >> "$GITHUB_OUTPUT"
+          else
+            echo "value=dev" >> "$GITHUB_OUTPUT"
+          fi
+
       - name: Build and push by digest
         id: build
         uses: docker/build-push-action@v7
@@ -72,6 +93,7 @@ jobs:
           context: .
           file: ./Dockerfile
           platforms: ${{ matrix.platform }}
+          build-args: VERSION=${{ steps.version.outputs.value }}
           cache-from: type=gha,scope=${{ matrix.platform }}
           cache-to: type=gha,mode=max,scope=${{ matrix.platform }}
           github-token: ${{ secrets.GITHUB_TOKEN }}
@@ -120,22 +142,26 @@ jobs:
       - name: Determine image tags
         id: tags
         run: |
-          if [ "${{ github.ref_name }}" = "dev" ]; then
-            echo "tags=${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:dev" >> "$GITHUB_OUTPUT"
+          IMAGE="${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}"
+          INPUT_TAG="${{ inputs.tag }}"
+          if [ -n "$INPUT_TAG" ]; then
+            echo "tag_args=-t ${IMAGE}:latest -t ${IMAGE}:${INPUT_TAG}" >> "$GITHUB_OUTPUT"
+            echo "inspect_tag=${IMAGE}:latest" >> "$GITHUB_OUTPUT"
           else
-            echo "tags=${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest" >> "$GITHUB_OUTPUT"
+            echo "tag_args=-t ${IMAGE}:dev" >> "$GITHUB_OUTPUT"
+            echo "inspect_tag=${IMAGE}:dev" >> "$GITHUB_OUTPUT"
           fi
 
       - name: Create and push multi-arch manifest
         working-directory: /tmp/digests
         run: |
           docker buildx imagetools create \
-            -t ${{ steps.tags.outputs.tags }} \
+            ${{ steps.tags.outputs.tag_args }} \
             $(printf '${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}@sha256:%s ' *)
 
       - name: Inspect image
         run: |
-          docker buildx imagetools inspect ${{ steps.tags.outputs.tags }}
+          docker buildx imagetools inspect ${{ steps.tags.outputs.inspect_tag }}
 
       - name: Ensure package is public
         run: |
@@ -162,6 +188,8 @@ jobs:
 
       - name: Checkout repository
         uses: actions/checkout@v6
+        with:
+          ref: ${{ inputs.tag || github.ref }}
 
       - name: Set up QEMU
         uses: docker/setup-qemu-action@v4
@@ -176,13 +204,30 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Determine CPU image tag
-        id: cpu-tag
+      - name: Determine CPU image tags
+        id: cpu-tags
         run: |
-          if [ "${{ github.ref_name }}" = "dev" ]; then
-            echo "tag=${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:dev-cpu" >> "$GITHUB_OUTPUT"
+          IMAGE="${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}"
+          INPUT_TAG="${{ inputs.tag }}"
+          if [ -n "$INPUT_TAG" ]; then
+            {
+              echo "tags<<EOF"
+              printf '%s\n' "${IMAGE}:cpu" "${IMAGE}:${INPUT_TAG}-cpu"
+              echo "EOF"
+            } >> "$GITHUB_OUTPUT"
+            echo "inspect_tag=${IMAGE}:cpu" >> "$GITHUB_OUTPUT"
           else
-            echo "tag=${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:cpu" >> "$GITHUB_OUTPUT"
+            echo "tags=${IMAGE}:dev-cpu" >> "$GITHUB_OUTPUT"
+            echo "inspect_tag=${IMAGE}:dev-cpu" >> "$GITHUB_OUTPUT"
+          fi
+
+      - name: Compute build version
+        id: version
+        run: |
+          if [ -n "${{ inputs.version }}" ]; then
+            echo "value=${{ inputs.version }}" >> "$GITHUB_OUTPUT"
+          else
+            echo "value=dev" >> "$GITHUB_OUTPUT"
           fi
 
       - name: Build and push CPU image
@@ -191,16 +236,18 @@ jobs:
           context: .
           file: ./Dockerfile
           platforms: linux/amd64,linux/arm64
-          build-args: VARIANT=cpu
+          build-args: |
+            VARIANT=cpu
+            VERSION=${{ steps.version.outputs.value }}
           cache-from: type=gha,scope=cpu
           cache-to: type=gha,mode=max,scope=cpu
           github-token: ${{ secrets.GITHUB_TOKEN }}
           push: true
-          tags: ${{ steps.cpu-tag.outputs.tag }}
+          tags: ${{ steps.cpu-tags.outputs.tags }}
 
       - name: Inspect CPU image
         run: |
-          docker buildx imagetools inspect ${{ steps.cpu-tag.outputs.tag }}
+          docker buildx imagetools inspect ${{ steps.cpu-tags.outputs.inspect_tag }}
 
       - name: Ensure package is public
         run: |
@@ -227,6 +274,8 @@ jobs:
 
       - name: Checkout repository
         uses: actions/checkout@v6
+        with:
+          ref: ${{ inputs.tag || github.ref }}
 
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v4
@@ -238,13 +287,30 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Determine ROCm image tag
-        id: rocm-tag
+      - name: Determine ROCm image tags
+        id: rocm-tags
         run: |
-          if [ "${{ github.ref_name }}" = "dev" ]; then
-            echo "tag=${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:dev-rocm" >> "$GITHUB_OUTPUT"
+          IMAGE="${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}"
+          INPUT_TAG="${{ inputs.tag }}"
+          if [ -n "$INPUT_TAG" ]; then
+            {
+              echo "tags<<EOF"
+              printf '%s\n' "${IMAGE}:rocm" "${IMAGE}:${INPUT_TAG}-rocm"
+              echo "EOF"
+            } >> "$GITHUB_OUTPUT"
+            echo "inspect_tag=${IMAGE}:rocm" >> "$GITHUB_OUTPUT"
           else
-            echo "tag=${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:rocm" >> "$GITHUB_OUTPUT"
+            echo "tags=${IMAGE}:dev-rocm" >> "$GITHUB_OUTPUT"
+            echo "inspect_tag=${IMAGE}:dev-rocm" >> "$GITHUB_OUTPUT"
+          fi
+
+      - name: Compute build version
+        id: version
+        run: |
+          if [ -n "${{ inputs.version }}" ]; then
+            echo "value=${{ inputs.version }}" >> "$GITHUB_OUTPUT"
+          else
+            echo "value=dev" >> "$GITHUB_OUTPUT"
           fi
 
       - name: Build and push ROCm image
@@ -253,16 +319,18 @@ jobs:
           context: .
           file: ./Dockerfile
           platforms: linux/amd64
-          build-args: VARIANT=rocm
+          build-args: |
+            VARIANT=rocm
+            VERSION=${{ steps.version.outputs.value }}
           cache-from: type=gha,scope=linux/amd64-rocm
           cache-to: type=gha,mode=max,scope=linux/amd64-rocm
           github-token: ${{ secrets.GITHUB_TOKEN }}
           push: true
-          tags: ${{ steps.rocm-tag.outputs.tag }}
+          tags: ${{ steps.rocm-tags.outputs.tags }}
 
       - name: Inspect ROCm image
         run: |
-          docker buildx imagetools inspect ${{ steps.rocm-tag.outputs.tag }}
+          docker buildx imagetools inspect ${{ steps.rocm-tags.outputs.inspect_tag }}
 
       - name: Ensure package is public
         run: |
@@ -289,6 +357,8 @@ jobs:
 
       - name: Checkout repository
         uses: actions/checkout@v6
+        with:
+          ref: ${{ inputs.tag || github.ref }}
 
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v4
@@ -300,13 +370,30 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Determine Intel image tag
-        id: intel-tag
+      - name: Determine Intel image tags
+        id: intel-tags
         run: |
-          if [ "${{ github.ref_name }}" = "dev" ]; then
-            echo "tag=${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:dev-intel" >> "$GITHUB_OUTPUT"
+          IMAGE="${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}"
+          INPUT_TAG="${{ inputs.tag }}"
+          if [ -n "$INPUT_TAG" ]; then
+            {
+              echo "tags<<EOF"
+              printf '%s\n' "${IMAGE}:intel" "${IMAGE}:${INPUT_TAG}-intel"
+              echo "EOF"
+            } >> "$GITHUB_OUTPUT"
+            echo "inspect_tag=${IMAGE}:intel" >> "$GITHUB_OUTPUT"
           else
-            echo "tag=${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:intel" >> "$GITHUB_OUTPUT"
+            echo "tags=${IMAGE}:dev-intel" >> "$GITHUB_OUTPUT"
+            echo "inspect_tag=${IMAGE}:dev-intel" >> "$GITHUB_OUTPUT"
+          fi
+
+      - name: Compute build version
+        id: version
+        run: |
+          if [ -n "${{ inputs.version }}" ]; then
+            echo "value=${{ inputs.version }}" >> "$GITHUB_OUTPUT"
+          else
+            echo "value=dev" >> "$GITHUB_OUTPUT"
           fi
 
       - name: Build and push Intel image
@@ -315,16 +402,18 @@ jobs:
           context: .
           file: ./Dockerfile
           platforms: linux/amd64
-          build-args: VARIANT=intel
+          build-args: |
+            VARIANT=intel
+            VERSION=${{ steps.version.outputs.value }}
           cache-from: type=gha,scope=linux/amd64-intel
           cache-to: type=gha,mode=max,scope=linux/amd64-intel
           github-token: ${{ secrets.GITHUB_TOKEN }}
           push: true
-          tags: ${{ steps.intel-tag.outputs.tag }}
+          tags: ${{ steps.intel-tags.outputs.tags }}
 
       - name: Inspect Intel image
         run: |
-          docker buildx imagetools inspect ${{ steps.intel-tag.outputs.tag }}
+          docker buildx imagetools inspect ${{ steps.intel-tags.outputs.inspect_tag }}
 
       - name: Ensure package is public
         run: |

.github/workflows/release.yml

@@ -127,188 +127,14 @@ jobs:
               prerelease: false,
             });
 
-  build-gpu:
-    name: Build GPU image
+  build-images:
+    name: Build and push Docker images
     needs: release
-    runs-on: ubuntu-latest
+    uses: ./.github/workflows/docker-publish.yml
+    with:
+      tag: ${{ needs.release.outputs.tag }}
+      version: ${{ needs.release.outputs.version }}
+    secrets: inherit
     permissions:
       packages: write
-    steps:
-      - name: Free up disk space
-        run: |
-          sudo rm -rf /usr/share/dotnet
-          sudo rm -rf /opt/ghc
-          sudo rm -rf "/usr/local/share/boost"
-          sudo rm -rf "$AGENT_TOOLSDIRECTORY"
-          echo "Disk space freed."
-
-      - name: Checkout
-        uses: actions/checkout@v6
-
-      - name: Set up QEMU
-        uses: docker/setup-qemu-action@v4
-
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v4
-
-      - name: Log in to GHCR
-        uses: docker/login-action@v4
-        with:
-          registry: ghcr.io
-          username: ${{ github.actor }}
-          password: ${{ secrets.GITHUB_TOKEN }}
-
-      - name: Build and push GPU image (latest)
-        uses: docker/build-push-action@v7
-        with:
-          context: .
-          file: ./Dockerfile
-          platforms: linux/amd64,linux/arm64
-          push: true
-          build-args: VERSION=${{ needs.release.outputs.version }}
-          cache-from: type=gha,scope=release-gpu
-          cache-to: type=gha,mode=max,scope=release-gpu
-          tags: |
-            ghcr.io/sudolulo/winnow:latest
-            ghcr.io/sudolulo/winnow:${{ needs.release.outputs.tag }}
-
-  build-cpu:
-    name: Build CPU image
-    needs: release
-    runs-on: ubuntu-latest
-    permissions:
-      packages: write
-    steps:
-      - name: Free up disk space
-        run: |
-          sudo rm -rf /usr/share/dotnet
-          sudo rm -rf /opt/ghc
-          sudo rm -rf "/usr/local/share/boost"
-          sudo rm -rf "$AGENT_TOOLSDIRECTORY"
-          echo "Disk space freed."
-
-      - name: Checkout
-        uses: actions/checkout@v6
-
-      - name: Set up QEMU
-        uses: docker/setup-qemu-action@v4
-
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v4
-
-      - name: Log in to GHCR
-        uses: docker/login-action@v4
-        with:
-          registry: ghcr.io
-          username: ${{ github.actor }}
-          password: ${{ secrets.GITHUB_TOKEN }}
-
-      - name: Build and push CPU image
-        uses: docker/build-push-action@v7
-        with:
-          context: .
-          file: ./Dockerfile
-          platforms: linux/amd64,linux/arm64
-          push: true
-          build-args: |
-            VARIANT=cpu
-            VERSION=${{ needs.release.outputs.version }}
-          cache-from: type=gha,scope=release-cpu
-          cache-to: type=gha,mode=max,scope=release-cpu
-          tags: |
-            ghcr.io/sudolulo/winnow:cpu
-            ghcr.io/sudolulo/winnow:${{ needs.release.outputs.tag }}-cpu
-
-  build-rocm:
-    name: Build ROCm image
-    needs: release
-    runs-on: ubuntu-latest
-    permissions:
-      packages: write
-    steps:
-      - name: Free up disk space
-        run: |
-          sudo rm -rf /usr/share/dotnet
-          sudo rm -rf /opt/ghc
-          sudo rm -rf "/usr/local/share/boost"
-          sudo rm -rf "$AGENT_TOOLSDIRECTORY"
-          echo "Disk space freed."
-
-      - name: Checkout
-        uses: actions/checkout@v6
-
-      - name: Set up QEMU
-        uses: docker/setup-qemu-action@v4
-
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v4
-
-      - name: Log in to GHCR
-        uses: docker/login-action@v4
-        with:
-          registry: ghcr.io
-          username: ${{ github.actor }}
-          password: ${{ secrets.GITHUB_TOKEN }}
-
-      - name: Build and push ROCm image
-        uses: docker/build-push-action@v7
-        with:
-          context: .
-          file: ./Dockerfile
-          platforms: linux/amd64
-          push: true
-          build-args: |
-            VARIANT=rocm
-            VERSION=${{ needs.release.outputs.version }}
-          cache-from: type=gha,scope=release-rocm
-          cache-to: type=gha,mode=max,scope=release-rocm
-          tags: |
-            ghcr.io/sudolulo/winnow:rocm
-            ghcr.io/sudolulo/winnow:${{ needs.release.outputs.tag }}-rocm
-
-  build-intel:
-    name: Build Intel image
-    needs: release
-    runs-on: ubuntu-latest
-    permissions:
-      packages: write
-    steps:
-      - name: Free up disk space
-        run: |
-          sudo rm -rf /usr/share/dotnet
-          sudo rm -rf /opt/ghc
-          sudo rm -rf "/usr/local/share/boost"
-          sudo rm -rf "$AGENT_TOOLSDIRECTORY"
-          echo "Disk space freed."
-
-      - name: Checkout
-        uses: actions/checkout@v6
-
-      - name: Set up QEMU
-        uses: docker/setup-qemu-action@v4
-
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v4
-
-      - name: Log in to GHCR
-        uses: docker/login-action@v4
-        with:
-          registry: ghcr.io
-          username: ${{ github.actor }}
-          password: ${{ secrets.GITHUB_TOKEN }}
-
-      - name: Build and push Intel image
-        uses: docker/build-push-action@v7
-        with:
-          context: .
-          file: ./Dockerfile
-          platforms: linux/amd64
-          push: true
-          build-args: |
-            VARIANT=intel
-            VERSION=${{ needs.release.outputs.version }}
-          cache-from: type=gha,scope=release-intel
-          cache-to: type=gha,mode=max,scope=release-intel
-          tags: |
-            ghcr.io/sudolulo/winnow:intel
-            ghcr.io/sudolulo/winnow:${{ needs.release.outputs.tag }}-intel
+      contents: read

CHANGELOG.md

@@ -7,6 +7,23 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.4.2] - 2026-06-13
+
+### Changed
+
+- **GPU image now uses CUDA 12.8.1** (was 13.3): CUDA 13.3 requires driver ≥ 575; driver 570 (the current stable release) was incorrectly rejected with "CUDA driver version is insufficient" at startup. The `:latest` image now works with any NVIDIA driver ≥ 570.
+
+### Added
+
+- **`scripts/benchmark.py`**: measures InsightFace and SigLIP inference latency and throughput across GPU and CPU modes. Run inside the container with `python /app/scripts/benchmark.py`. RTX 2070 SUPER results: InsightFace 12.8 ms / 78 img/s (8× CPU), SigLIP batch 32 at 5.4 ms/img / 187 img/s (33× CPU).
+
+## [0.4.1] - 2026-06-13
+
+### Fixed
+
+- **`RESET_PERSON` no longer creates duplicate Frigate files**: previously, resetting a person only wiped the local tracker — existing Frigate training files were left as unmanaged orphans, causing the next run to upload a full new batch on top of them. `reset_person` now deletes all winnow-managed files for that person from Frigate before clearing the tracker. Manually-added Frigate files are unaffected.
+- **No spurious warning when `FRIGATE_URL` is unset and `RESET_PERSON` is used**: the deletion step is now skipped silently at info level rather than logging a misleading "could not delete" warning.
+
 ## [0.4.0] - 2026-06-13
 
 ### Added

Dockerfile

@@ -1,5 +1,5 @@
 # ── Base images ───────────────────────────────────────────────────────────────
-#   amd64 + gpu:   NVIDIA CUDA 13.3 + cuDNN (GPU acceleration via NVIDIA Container Toolkit)
+#   amd64 + gpu:   NVIDIA CUDA 12.8 + cuDNN (GPU acceleration via NVIDIA Container Toolkit)
 #   amd64 + rocm:  Ubuntu 22.04 (AMD GPU via ROCm — pass /dev/kfd and /dev/dri)
 #   amd64 + intel: Ubuntu 22.04 (Intel Arc / iGPU via OpenVINO — pass /dev/dri)
 #   amd64 + cpu:   Ubuntu 22.04 (CPU-only, ~2 GB smaller image)
@@ -7,7 +7,7 @@
 
 ARG VARIANT=gpu
 
-FROM --platform=$BUILDPLATFORM nvidia/cuda:13.3.0-cudnn-runtime-ubuntu22.04 AS base-amd64-gpu
+FROM --platform=$BUILDPLATFORM nvidia/cuda:12.8.1-cudnn-runtime-ubuntu22.04 AS base-amd64-gpu
 FROM ubuntu:22.04 AS base-amd64-rocm
 FROM ubuntu:22.04 AS base-amd64-intel
 FROM ubuntu:22.04 AS base-amd64-cpu

README.md

@@ -11,6 +11,8 @@
 
 Frigate's face recognition is only as good as its training data — and the key quality metric is **diversity**, not volume. A hundred photos from the same week teach the model one lighting condition. What you need is a spread: different years, different angles, different lighting, different contexts. Your photo library already has that data. winnow finds and delivers the right subset automatically.
 
+> **winnow only touches files it uploaded.** Faces added to Frigate manually through its UI are never deleted, replaced, or modified — not by quality replacement, not by `RESET_PERSON`, not by stale cleanup. If you have a curated training set you want to keep, it is safe.
+
 ---
 
 ## How It Works
@@ -222,7 +224,7 @@ In scheduled mode the process (and loaded models) stays resident between runs. T
 | :--- | :--- | :--- |
 | `DRY_RUN` | `false` | Preview selection without downloading or uploading |
 | `RETRY_REJECTED` | `false` | Re-attempt assets previously rejected by Frigate |
-| `RESET_PERSON` | *(unset)* | Clear upload and rejection history for one person by name |
+| `RESET_PERSON` | *(unset)* | Clear upload history for one person and delete their winnow-managed Frigate training files so the next run starts fresh. Manually added Frigate files are never touched |
 
 ### Scheduling
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "winnow"
-version = "0.4.0"
+version = "0.4.2"
 description = "Selects diverse, high-quality photos from Immich as training data for Frigate face recognition and object classification."
 license = "AGPL-3.0-or-later"
 requires-python = ">=3.13"

scripts/benchmark.py

@@ -0,0 +1,196 @@
+#!/usr/bin/env python3
+"""
+winnow inference benchmark: GPU vs CPU throughput.
+
+Measures InsightFace (face mode) and SigLIP (object mode) latency and
+throughput. Run with FORCE_CPU=true for CPU-only baseline.
+
+Usage inside container:
+    # GPU mode:
+    docker exec winnow python /app/scripts/benchmark.py
+
+    # CPU mode:
+    docker exec -e FORCE_CPU=true winnow python /app/scripts/benchmark.py
+"""
+
+import os
+import sys
+import time
+
+import numpy as np
+from PIL import Image, ImageDraw
+
+
+def _mode_label() -> str:
+    if os.getenv("FORCE_CPU", "").lower() in ("true", "1", "yes"):
+        return "CPU (FORCE_CPU=true)"
+    return "GPU (auto)"
+
+
+def make_face_image(size: int = 640) -> Image.Image:
+    """Synthetic face-like image: skin-tone rectangle with landmark blobs."""
+    img = Image.new("RGB", (size, size), (200, 170, 140))
+    draw = ImageDraw.Draw(img)
+    # Head oval
+    cx, cy = size // 2, size // 2
+    hw, hh = int(size * 0.3), int(size * 0.38)
+    draw.ellipse([cx - hw, cy - hh, cx + hw, cy + hh], fill=(220, 185, 155))
+    # Eyes
+    for ex in [cx - int(size * 0.1), cx + int(size * 0.1)]:
+        ey = cy - int(size * 0.05)
+        r = max(4, size // 40)
+        draw.ellipse([ex - r, ey - r, ex + r, ey + r], fill=(40, 30, 20))
+    # Nose
+    draw.ellipse([cx - 5, cy + 5, cx + 5, cy + 15], fill=(180, 140, 110))
+    # Mouth
+    draw.arc([cx - 20, cy + 25, cx + 20, cy + 45], start=0, end=180, fill=(160, 80, 80), width=3)
+    return img
+
+
+def make_random_image(width: int = 224, height: int = 224) -> Image.Image:
+    rng = np.random.default_rng(42)
+    return Image.fromarray(rng.integers(0, 256, (height, width, 3), dtype=np.uint8), "RGB")
+
+
+def _stats(times_s: list[float]) -> dict:
+    arr = np.array(times_s) * 1000  # ms
+    return {
+        "median_ms": float(np.median(arr)),
+        "mean_ms": float(np.mean(arr)),
+        "min_ms": float(np.min(arr)),
+        "p95_ms": float(np.percentile(arr, 95)),
+        "ips": 1000.0 / float(np.median(arr)),
+    }
+
+
+def bench_insightface(n_warmup: int = 5, n_runs: int = 30) -> None:
+    import cv2
+
+    import winnow.embeddings as emb_mod
+    from winnow.embeddings import get_insightface_app
+
+    # Reset singleton so we get a fresh load
+    emb_mod._insightface_app = None
+    emb_mod._insightface_loaded = False
+
+    print("  Loading model...")
+    t_load = time.perf_counter()
+    app = get_insightface_app()
+    load_s = time.perf_counter() - t_load
+
+    if app is None:
+        print("  SKIP: InsightFace failed to load")
+        return
+
+    img_pil = make_face_image(640)
+    img_bgr = cv2.cvtColor(np.asarray(img_pil), cv2.COLOR_RGB2BGR)
+
+    # Warmup
+    for _ in range(n_warmup):
+        app.get(img_bgr)
+
+    # Timed — single image 640×640
+    times: list[float] = []
+    for _ in range(n_runs):
+        t0 = time.perf_counter()
+        app.get(img_bgr)
+        times.append(time.perf_counter() - t0)
+
+    s = _stats(times)
+    print(f"  Model load time : {load_s:.2f} s")
+    print("  Input size      : 640×640")
+    print(f"  Runs            : {n_runs} (after {n_warmup} warmup)")
+    print(f"  Median latency  : {s['median_ms']:.1f} ms")
+    print(f"  Mean / p95      : {s['mean_ms']:.1f} ms / {s['p95_ms']:.1f} ms")
+    print(f"  Min latency     : {s['min_ms']:.1f} ms")
+    print(f"  Throughput      : {s['ips']:.1f} images/s")
+
+    # Also test at 320×320
+    img_sm = make_face_image(320)
+    img_sm_bgr = cv2.cvtColor(np.asarray(img_sm), cv2.COLOR_RGB2BGR)
+    for _ in range(n_warmup):
+        app.get(img_sm_bgr)
+    times_sm: list[float] = []
+    for _ in range(n_runs):
+        t0 = time.perf_counter()
+        app.get(img_sm_bgr)
+        times_sm.append(time.perf_counter() - t0)
+    s2 = _stats(times_sm)
+    print(f"  320×320 median  : {s2['median_ms']:.1f} ms  ({s2['ips']:.1f} img/s)")
+
+
+def bench_siglip(
+    n_warmup: int = 3,
+    n_runs: int = 20,
+    batch_sizes: tuple = (1, 4, 8, 16, 32),
+) -> None:
+    import torch
+
+    import winnow.embeddings as emb_mod
+    emb_mod._siglip_model = None
+    emb_mod._siglip_processor = None
+    emb_mod._siglip_loaded = False
+
+    print("  Loading model...")
+    t_load = time.perf_counter()
+    model, processor = emb_mod.get_siglip_model()
+    load_s = time.perf_counter() - t_load
+
+    if model is None:
+        print("  SKIP: SigLIP failed to load")
+        return
+
+    device = next(model.parameters()).device
+    print(f"  Model load time : {load_s:.2f} s  (device: {device})")
+
+    print(f"  {'Batch':>5}  {'ms/batch':>10}  {'ms/img':>8}  {'img/s':>8}  {'p95/img':>9}")
+    for bs in batch_sizes:
+        imgs = [make_random_image(224, 224) for _ in range(bs)]
+        inputs = processor(images=imgs, return_tensors="pt")
+        inputs = {k: v.to(device) for k, v in inputs.items()}
+
+        # Warmup
+        for _ in range(n_warmup):
+            with torch.no_grad():
+                model(**inputs)
+        if str(device) != "cpu":
+            torch.cuda.synchronize()
+
+        times: list[float] = []
+        for _ in range(n_runs):
+            if str(device) != "cpu":
+                torch.cuda.synchronize()
+            t0 = time.perf_counter()
+            with torch.no_grad():
+                model(**inputs)
+            if str(device) != "cpu":
+                torch.cuda.synchronize()
+            times.append(time.perf_counter() - t0)
+
+        s = _stats(times)
+        print(
+            f"  {bs:>5}  {s['median_ms']:>10.1f}  {s['median_ms']/bs:>8.2f}"
+            f"  {bs * 1000 / s['median_ms']:>8.1f}  {s['p95_ms']/bs:>9.2f}"
+        )
+
+
+def main() -> None:
+    print("=" * 56)
+    print("  winnow inference benchmark")
+    print(f"  Mode: {_mode_label()}")
+    print("=" * 56)
+    print()
+
+    print("── InsightFace Buffalo_L  (face detection + ArcFace) ──")
+    bench_insightface()
+    print()
+
+    print("── SigLIP google/siglip-base-patch16-224  (objects) ───")
+    bench_siglip()
+    print()
+
+
+if __name__ == "__main__":
+    # Add winnow to path when run directly inside container
+    sys.path.insert(0, "/app")
+    main()

uv.lock

@@ -2348,7 +2348,7 @@ wheels = [
 
 [[package]]
 name = "winnow"
-version = "0.3.3"
+version = "0.4.1"
 source = { editable = "." }
 dependencies = [
     { name = "croniter" },

winnow/executor.py

@@ -13,7 +13,12 @@ from rich import print as rprint
 from rich.progress import BarColumn, Progress, SpinnerColumn, TaskProgressColumn, TextColumn
 
 from .config import Config, get_headers
-from .frigate_api import delete_frigate_person_files, get_all_frigate_person_files, get_frigate_person_files, recognize_face
+from .frigate_api import (
+    delete_frigate_person_files,
+    get_all_frigate_person_files,
+    get_frigate_person_files,
+    recognize_face,
+)
 from .image_processing import process_face_mode, process_full_mode, process_object_mode
 from .immich_api import fetch_face_data, fetch_full_image
 from .log_config import console
@@ -395,6 +400,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
             actually_uploaded: list[tuple[str, str | None]] = []
             failed_deletes: set[str] = set()
             min_quality_score_for_slot: float | None = None
+            person_has_fscores: bool = has_frigate_scores(name)
 
             for fname in person_files:
                 fpath = os.path.join(person_dir, fname)
@@ -427,9 +433,9 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                 # handles this conservatively by skipping that candidate until the next run.
                 pre_fscore: float | None = None
                 if Config.ENABLE_FRIGATE_SCORES and pre_run_count > 0:
-                    if not at_cap or has_frigate_scores(name):
+                    if not at_cap or person_has_fscores:
                         _result = recognize_face(fpath)
-                        if _result is not None and _result[0] == name:
+                        if _result is not None and (_result[0] or "").casefold() == name.casefold():
                             pre_fscore = _result[1]
 
                 # Ceiling check: skip if the existing training set already covers this
@@ -450,7 +456,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                         progress.advance(upload_task)
                         continue
 
-                    using_fscore = has_frigate_scores(name) and Config.ENABLE_FRIGATE_SCORES
+                    using_fscore = person_has_fscores and Config.ENABLE_FRIGATE_SCORES
                     if using_fscore:
                         candidate_score = pre_fscore
                         if candidate_score is None:
@@ -476,8 +482,10 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                         )
                         if delete_frigate_person_files(name, [target_frigate_file]):
                             remove_frigate_file(name, target_frigate_file)
+                            person_has_fscores = has_frigate_scores(name)
                             effective_count -= 1
-                            min_quality_score_for_slot = None  # clear any blur-mode slot floor — Frigate uses a different score metric
+                            # clear any blur-mode slot floor — Frigate uses a different score metric
+                            min_quality_score_for_slot = None
                         else:
                             logger.warning(f"Failed to delete {target_frigate_file} for {name}, skipping replacement")
                             failed_deletes.add(target_frigate_file)
@@ -507,6 +515,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                         )
                         if delete_frigate_person_files(name, [target_frigate_file]):
                             remove_frigate_file(name, target_frigate_file)
+                            person_has_fscores = has_frigate_scores(name)
                             effective_count -= 1
                             min_quality_score_for_slot = score_map.get(fname)
                         else:
@@ -538,6 +547,8 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                                     crop_dims=dims_map.get(fname),
                                     frigate_score=pre_fscore,
                                 )
+                                if pre_fscore is not None:
+                                    person_has_fscores = True
                                 actually_uploaded.append((fname, asset_id))
 
                             break

winnow/frigate_api.py

@@ -22,24 +22,6 @@ def _get_faces_data() -> dict | None:
         return None
 
 
-def get_frigate_face_counts() -> dict[str, int] | None:
-    """Return {person_name: training_image_count} from Frigate's train directory.
-
-    Returns None if FRIGATE_URL is not set or the API is unreachable, so callers
-    can distinguish "API unavailable" from "person has 0 images."
-    """
-    data = _get_faces_data()
-    if data is None:
-        return None
-    # Response: {person_name: [file, ...], "train": [...], ...}
-    # "train" is a flat pending list, not a person — skip it.
-    return {
-        name: len(files)
-        for name, files in data.items()
-        if name != "train" and isinstance(files, list)
-    }
-
-
 def get_all_frigate_person_files() -> dict[str, list[str]] | None:
     """Return {person_name: [filename, ...]} for every person in Frigate.
 
@@ -49,6 +31,8 @@ def get_all_frigate_person_files() -> dict[str, list[str]] | None:
     data = _get_faces_data()
     if data is None:
         return None
+    # Response: {person_name: [file, ...], "train": [...], ...}
+    # "train" is a flat pending list, not a person — skip it.
     return {
         name: files
         for name, files in data.items()
@@ -56,6 +40,18 @@ def get_all_frigate_person_files() -> dict[str, list[str]] | None:
     }
 
 
+def get_frigate_face_counts() -> dict[str, int] | None:
+    """Return {person_name: training_image_count} from Frigate's train directory.
+
+    Returns None if FRIGATE_URL is not set or the API is unreachable, so callers
+    can distinguish "API unavailable" from "person has 0 images."
+    """
+    all_files = get_all_frigate_person_files()
+    if all_files is None:
+        return None
+    return {name: len(files) for name, files in all_files.items()}
+
+
 def get_frigate_person_files(person_name: str) -> list[str] | None:
     """Return the list of training filenames for a person in Frigate.
 

winnow/upload_tracker.py

@@ -29,8 +29,11 @@ Frigate's UI are never mapped here and are never touched by quality replacement.
 
 import json
 import logging
+import os
 from pathlib import Path
 
+from .frigate_api import delete_frigate_person_files
+
 logger = logging.getLogger(__name__)
 
 UPLOAD_TRACKER_FILE = "frigate_uploaded_ids.json"
@@ -167,7 +170,9 @@ def remove_frigate_file(person_name: str, frigate_filename: str) -> None:
     data = _load(UPLOAD_TRACKER_FILE)
     by_person = data.get("by_person", {})
     entry = _migrate_entry(by_person.get(person_name, {}))
-    entry["frigate_files"].pop(frigate_filename, None)
+    asset_id = entry["frigate_files"].pop(frigate_filename, None)
+    if asset_id:
+        entry["frigate_scores"].pop(asset_id, None)
     by_person[person_name] = entry
     _save(UPLOAD_TRACKER_FILE, data)
     logger.debug(f"Removed Frigate file mapping {frigate_filename} ({person_name})")
@@ -204,6 +209,22 @@ def has_frigate_scores(person_name: str) -> bool:
     return any(asset_id in frigate_scores for asset_id in frigate_files.values())
 
 
+def _pick_mapped_file(
+    person_name: str, score_key: str, *, highest: bool, exclude: set[str] | None = None
+) -> tuple[str, str, float] | None:
+    data = _load(UPLOAD_TRACKER_FILE)
+    entry = _migrate_entry(data.get("by_person", {}).get(person_name, {}))
+    scores = entry.get(score_key, {})
+    candidates = [
+        (ff, asset_id, scores[asset_id])
+        for ff, asset_id in entry.get("frigate_files", {}).items()
+        if (exclude is None or ff not in exclude) and asset_id in scores
+    ]
+    if not candidates:
+        return None
+    return max(candidates, key=lambda x: x[2]) if highest else min(candidates, key=lambda x: x[2])
+
+
 def get_lowest_quality_mapped_file(
     person_name: str, exclude: set[str] | None = None
 ) -> tuple[str, str, float] | None:
@@ -213,21 +234,7 @@ def get_lowest_quality_mapped_file(
     Used for quality replacement when no Frigate scores are available.
     Pass `exclude` to skip files that failed to delete this run.
     """
-    data = _load(UPLOAD_TRACKER_FILE)
-    entry = _migrate_entry(data.get("by_person", {}).get(person_name, {}))
-    frigate_files = entry.get("frigate_files", {})
-    blur_scores = entry.get("scores", {})
-
-    candidates = [
-        (ff, asset_id, blur_scores[asset_id])
-        for ff, asset_id in frigate_files.items()
-        if (exclude is None or ff not in exclude)
-        and asset_id in blur_scores
-    ]
-
-    if not candidates:
-        return None
-    return min(candidates, key=lambda x: x[2])
+    return _pick_mapped_file(person_name, "scores", highest=False, exclude=exclude)
 
 
 def get_most_redundant_mapped_file(
@@ -240,21 +247,7 @@ def get_most_redundant_mapped_file(
     = the most redundant file and therefore the best replacement target.
     Pass `exclude` to skip files that failed to delete this run.
     """
-    data = _load(UPLOAD_TRACKER_FILE)
-    entry = _migrate_entry(data.get("by_person", {}).get(person_name, {}))
-    frigate_files = entry.get("frigate_files", {})
-    frigate_scores = entry.get("frigate_scores", {})
-
-    candidates = [
-        (ff, asset_id, frigate_scores[asset_id])
-        for ff, asset_id in frigate_files.items()
-        if (exclude is None or ff not in exclude)
-        and asset_id in frigate_scores
-    ]
-
-    if not candidates:
-        return None
-    return max(candidates, key=lambda x: x[2])
+    return _pick_mapped_file(person_name, "frigate_scores", highest=True, exclude=exclude)
 
 
 def get_frigate_filename_for_asset(person_name: str, asset_id: str) -> str | None:
@@ -307,19 +300,41 @@ def update_frigate_count(person_name: str, count: int) -> None:
 
 
 def reset_person(person_name: str) -> None:
-    """Remove all uploaded and rejected records for a given person."""
-    for filename in (UPLOAD_TRACKER_FILE, REJECT_TRACKER_FILE):
-        data = _load(filename)
+    """Remove all uploaded and rejected records for a given person.
+
+    Also deletes winnow-managed Frigate training files so the next run starts
+    clean rather than uploading on top of orphaned files. Manually-added Frigate
+    files (not in frigate_files) are never touched. Proceeds with tracker reset
+    even if Frigate is unreachable.
+    """
+    upload_data = _load(UPLOAD_TRACKER_FILE)
+    entry = _migrate_entry(upload_data.get("by_person", {}).get(person_name, {}))
+    frigate_filenames = list(entry.get("frigate_files", {}).keys())
+    if frigate_filenames:
+        if not os.environ.get("FRIGATE_URL", "").strip():
+            logger.info(f"FRIGATE_URL not set — skipping Frigate file deletion for {person_name}")
+        elif delete_frigate_person_files(person_name, frigate_filenames):
+            logger.info(f"Deleted {len(frigate_filenames)} Frigate file(s) for {person_name}")
+        else:
+            logger.warning(f"Could not delete Frigate files for {person_name} — tracker reset proceeding anyway")
+
+    changed = False
+    tracker_files = ((UPLOAD_TRACKER_FILE, upload_data), (REJECT_TRACKER_FILE, _load(REJECT_TRACKER_FILE)))
+    for filename, data in tracker_files:
         flat_key = _flat_key(filename)
         by_person = data.get("by_person", {})
-        entry = by_person.pop(person_name, None)
-        if entry is not None:
-            person_ids = set(_get_ids(entry))
+        tracker_entry = by_person.pop(person_name, None)
+        if tracker_entry is not None:
+            person_ids = set(_get_ids(tracker_entry))
             flat = set(data.get(flat_key, [])) - person_ids
             data[flat_key] = sorted(flat)
             data["by_person"] = by_person
             _save(filename, data)
-    logger.info(f"Reset tracking data for {person_name}")
+            changed = True
+    if changed:
+        logger.info(f"Reset tracking data for {person_name}")
+    else:
+        logger.debug(f"reset_person: no tracking data found for {person_name}")
 
 
 def get_person_summary() -> dict[str, dict]: