AI Analysis
The package shows low individual risks across various categories, but the newness of the author and poor metadata quality introduce some uncertainty. This combination slightly raises the suspicion level.
- New author with low metadata quality
- Lack of package description
Per-check LLM notes
- Network: No network calls suggest normal behavior for a camera toolkit.
- Shell: No shell executions indicate no immediate risk from command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: Low risk due to lack of suspicious indicators, but author's newness and low metadata quality raise some concerns.
Package Quality Overall: Low (3.6/10)
Test suite present — 6 test file(s) found
6 test file(s) detected (e.g. test_config.py)
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
154 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: ugent.be
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
2 maintainer concern(s) found
Author "Thomas Lips" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a real-time object detection and tracking application using the 'airo-camera-toolkit' package. This application will serve as a proof-of-concept for integrating camera tools into robotic manipulation tasks. The app should capture video from a connected RGB-D camera, process frames to detect objects, and track their movement over time. Utilize the 'airo-camera-toolkit' for interfacing with the camera and processing depth information alongside RGB data. Key features include: 1. Real-time video feed from an RGB-D camera. 2. Object detection using pre-trained models or custom models trained on specific datasets. 3. Tracking of detected objects across consecutive frames to estimate motion. 4. Displaying bounding boxes around detected objects and their labels. 5. Saving tracked trajectories of objects in a log file for further analysis. 6. Optional feature: Adjusting detection parameters dynamically based on user input or environmental conditions. Use the 'airo-camera-toolkit' to handle camera initialization, frame acquisition, and processing of both RGB and depth data. Ensure the application is modular, allowing easy integration of different models for object detection and tracking.
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