Count occurrences of an object in the image using computer vision algorithm.
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See how to installReview the instructions the agent will receive before you install.
For obtaining high fidelity object counting results, it's recommended to set a higher threshold, such as 0.9, also we need to do Non-Maximum Suppression using --dedup_min_dist flag (a good default value is 3).
python3 scripts/count_objects.py \
--tool count \
--input_image <image file> \
--object_image <object image file> \
--threshold 0.9 \
--dedup_min_dist 3
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Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
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AC branch pi-model power flow equations (P/Q and |S|) with transformer tap ratio and phase shift, matching `acopf-math-model.md` and MATPOWER branch fields. Use when computing branch flows in either direction, aggregating bus injections for nodal balance, checking MVA (rateA) limits, computing branch loading %, or debugging sign/units issues in AC power flow.
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Redact text from PDF documents for blind review anonymization
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Use when checking simplified ADA-derived plan-view bathroom accessibility constraints such as turning space, door clear width, toilet centerline, grab bars, and lavatory knee/toe clearance.
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Analyze failed GitHub Action jobs for a pull request.
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Use when extracting plan-view architectural geometry from DXF files with semantic CAD layers, especially when outputs must normalize rooms, doors, fixtures, clearances, and grab bars into machine-checkable JSON.
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