Senior Computer Vision

Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Fast...

This skill appears coherent for production CV work and contains helpful scripts and docs. Before running anything: (1) Inspect the scripts locally (they are included) and run them in a contained environment (VM, container, or isolated user) with a Python virtualenv. (2) Do not run analysis commands (e.g., inference_optimizer.py) on model files from untrusted sources — torch.load can execute code via pickle. (3) Be prepared for scripts to read/write files (dataset conversions, ONNX/TensorRT exports, calibration caches) and to require heavy dependencies (PyTorch, ONNX, TensorRT). (4) Install dependencies from trusted sources and limit network access if you want extra safety. If you need, I can point out the exact lines that call torch.load / deserialize operations and where files are written so you can audit them before running.

Type: OpenClaw Skill Name: senior-computer-vision Version: 2.1.1 The 'senior-computer-vision' skill bundle is a legitimate set of tools and documentation for computer vision engineering. The included Python scripts (dataset_pipeline_builder.py, inference_optimizer.py, and vision_model_trainer.py) provide functional logic for dataset management, model benchmarking, and training configuration without any evidence of malicious behavior, data exfiltration, or unauthorized system access. The instructions in SKILL.md are well-aligned with the stated purpose, and the documentation in the references directory provides standard industry guidance for CV architectures and deployment.