Fix default target face handling for empty clusters

[duyua9]

Summary

• Skip target-face clusters that contain no detected faces instead of dereferencing None.
• Add focused regression coverage for empty clusters and continued processing of later clusters.

Validation

• python3 -m unittest tests/test_face_analyser_default_target.py
• python3 -m py_compile modules/face_analyser.py tests/test_face_analyser_default_target.py
• git diff --check
• bash /Users/ming/.openclaw/skills/code-change-delivery-contract/scripts/scan_delivery_blockers.sh

Summary by Sourcery

Handle clusters without detected faces when selecting a default target face and add regression coverage for these scenarios.

Bug Fixes:

• Avoid dereferencing missing face or frame data when a target-face cluster contains no detected faces.

Tests:

• Add unit tests covering empty target-face clusters and continued processing of subsequent clusters when computing the default target face.

[sourcery-ai]

Reviewer's Guide

Handles clusters with no detected faces in default_target_face without crashing and adds regression tests to verify skipping empty clusters while still processing subsequent ones.

Flow diagram for updated default_target_face empty-cluster handling

flowchart TD
    A[start_default_target_face] --> B["Initialize best_face and best_frame to None"]
    B --> C["For each cluster in clusters"]
    C --> D["For each frame in cluster"]
    D --> E["For each face in frame"]
    E --> F["Update best_face and best_frame if this face is better"]
    F --> G["Finished iterating faces in this cluster"]

    G --> H{best_face is None or best_frame is None?}
    H -->|Yes| I["continue to next cluster (skip empty cluster)"]
    I --> C
    H -->|No| J["Read target_frame from best_frame location with cv2.imread"]
    J --> K["Extract x_min, y_min, x_max, y_max from best_face bbox"]
    K --> L["Return chosen target frame and bounding box"]

Loading

File-Level Changes

Change	Details	Files
Avoid crashing when a target-face cluster has no detected faces by skipping clusters without a selected best face/frame.	After computing best_face and best_frame in the cluster loop, add a guard that continues to the next cluster if either best_face or best_frame is None Leave the subsequent bounding-box extraction and cv2.imread logic unchanged so it only runs when a valid best_face/best_frame pair exists	modules/face_analyser.py
Add regression tests that exercise empty target-face clusters and ensure later clusters are still processed and assigned targets.	Introduce a dedicated test module that builds a fully stubbed environment for modules.face_analyser, including fake cv2, numpy, insightface, globals, cluster_analysis, utilities, typing, and tqdm Test that default_target_face leaves clusters with no detected faces without adding a target entry Test that clusters following an empty cluster still get their target selected based on highest det_score and that the returned cv2 crop indexes match the expected bbox-derived slices	tests/test_face_analyser_default_target.py

Possibly linked issues

• #fix: default_target_face crashes with TypeError when no faces detected in any frame: PR adds a best_face/best_frame None-guard in default_target_face and tests, exactly fixing the reported crash.

---

Tips and commands

Interacting with Sourcery

• Trigger a new review: Comment @sourcery-ai review on the pull request.
• Continue discussions: Reply directly to Sourcery's review comments.
• Generate a GitHub issue from a review comment: Ask Sourcery to create an
  issue from a review comment by replying to it. You can also reply to a
  review comment with @sourcery-ai issue to create an issue from it.
• Generate a pull request title: Write @sourcery-ai anywhere in the pull
  request title to generate a title at any time. You can also comment
  @sourcery-ai title on the pull request to (re-)generate the title at any time.
• Generate a pull request summary: Write @sourcery-ai summary anywhere in
  the pull request body to generate a PR summary at any time exactly where you
  want it. You can also comment @sourcery-ai summary on the pull request to
  (re-)generate the summary at any time.
• Generate reviewer's guide: Comment @sourcery-ai guide on the pull
  request to (re-)generate the reviewer's guide at any time.
• Resolve all Sourcery comments: Comment @sourcery-ai resolve on the
  pull request to resolve all Sourcery comments. Useful if you've already
  addressed all the comments and don't want to see them anymore.
• Dismiss all Sourcery reviews: Comment @sourcery-ai dismiss on the pull
  request to dismiss all existing Sourcery reviews. Especially useful if you
  want to start fresh with a new review - don't forget to comment
  @sourcery-ai review to trigger a new review!

Customizing Your Experience

Access your dashboard to:

• Enable or disable review features such as the Sourcery-generated pull request
  summary, the reviewer's guide, and others.
• Change the review language.
• Add, remove or edit custom review instructions.
• Adjust other review settings.

Getting Help

• Contact our support team for questions or feedback.
• Visit our documentation for detailed guides and information.
• Keep in touch with the Sourcery team by following us on X/Twitter, LinkedIn or GitHub.

[sourcery-ai]

Hey - I've reviewed your changes and they look great!

---

Sourcery is free for open source - if you like our reviews please consider sharing them ✨

• X
• Mastodon
• LinkedIn
• Facebook

_{Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.}