Dev tools skills.
20,965 dev tools skills, including improve-codebase-architecture, tdd and setup-matt-pocock-skills, are listed on ahel today. Each one has a page of its own that says what it does and whether ahel can serve it in Claude, Claude Code, ChatGPT, Codex and Cursor.
Category: Dev tools
20,965 results · page 548 of 699
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cv-isotropic-voxel-resamplingSkillDev tools
Resample 3D CT volumes to uniform voxel spacing using scipy zoom, normalizing physical dimensions across scanners
Ready to connect★ 61
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cv-keypoint-aware-raster-augmentationSkillDev tools
Use albumentations keypoint_params to jointly augment BEV rasters and trajectory target points so the spatial transform stays consistent
Ready to connect★ 61
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cv-lateralized-label-flip-tta-disableSkillDev tools
Disable horizontal-flip augmentation (both train-time and TTA) when label columns encode left/right anatomy — flipping silently corrupts the targets because "Left ICA" must map to "Right ICA" after a flip, not stay as "Left ICA"
Ready to connect★ 61
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cv-lovasz-hinge-lossSkillDev tools
Lovasz hinge loss that directly optimizes IoU for binary segmentation by computing a convex surrogate via sorted prediction errors and cumulative Jaccard gradients.
Ready to connect★ 61
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cv-map-iou-precision-sweepSkillDev tools
Compute mean Average Precision by sweeping IoU thresholds from 0.5 to 0.95 on RLE-encoded instance masks using pycocotools
Ready to connect★ 61
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cv-mask-to-polygon-contour-hierarchySkillDev tools
Convert binary segmentation masks to Shapely MultiPolygons using cv2 contour hierarchy to correctly handle interior holes, with Douglas-Peucker simplification
Ready to connect★ 61
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cv-metadata-injection-bottleneckSkillDev tools
Inject scalar metadata (depth, position, clinical features) into U-Net bottleneck via RepeatVector and Reshape for metadata-aware segmentation
Ready to connect★ 61
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cv-morphological-lung-segmentationSkillDev tools
Segment lung regions from CT using HU thresholding, connected-component labeling, and morphological opening
Ready to connect★ 61
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cv-multi-annotator-bbox-consensusSkillDev tools
Merges overlapping same-class bounding boxes from multiple annotators into a consensus box using IoU-based matching and intersection.
Ready to connect★ 61
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cv-multi-window-channel-stackingSkillDev tools
Stack multiple CT window settings (brain, subdural, bone) as separate RGB channels for CNN input
Ready to connect★ 61
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cv-multichannel-to-rgb-adaptationSkillDev tools
Composites multi-channel imagery (microscopy, satellite) into 3-channel RGB for pretrained CNN backbones.
Ready to connect★ 61
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cv-nested-unet-dense-skip-connectionsSkillDev tools
UNet++ dense cross-depth skip connections that propagate deeper decoder features into all shallower decoder levels
Ready to connect★ 61
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cv-numeric-categorical-auto-detectionSkillDev tools
Auto-detect whether a generated data series is numeric or categorical by measuring the fraction of digit characters in the concatenated values
Ready to connect★ 61
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cv-open-set-distance-cutoffSkillDev tools
Assign an unknown/novel class when all nearest-neighbor distances exceed a tuned cutoff threshold for open-set recognition
Ready to connect★ 61
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cv-optimized-ordinal-thresholdsSkillDev tools
Uses Nelder-Mead optimization to find per-class decision thresholds that maximize Quadratic Weighted Kappa for regression-to-ordinal conversion.
Ready to connect★ 61
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cv-ordinal-multilabel-encodingSkillDev tools
Encodes ordinal classes as cumulative binary labels (class N activates labels 0..N), enabling sigmoid + BCE training for ordinal regression.
Ready to connect★ 61
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cv-pack-padded-sequence-lossSkillDev tools
Uses pack_padded_sequence to exclude padding tokens from cross-entropy loss in variable-length sequence generation.
Ready to connect★ 61
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cv-pairwise-tracking-feature-mergeSkillDev tools
Double left-join on tracking data to create pairwise features (positions, velocities, distance) for both entities in an interaction pair
Ready to connect★ 61
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cv-per-class-soft-f1-threshold-fittingSkillDev tools
Optimize per-class decision thresholds for macro-F1 by replacing the non-differentiable hard threshold with a sigmoid-sharpened soft-F1 surrogate and fitting the per-class threshold vector via least-squares — averaged over multiple random validation splits to suppress overfitting on rare classes
Ready to connect★ 61
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cv-per-organ-multihead-sigmoid-softmaxSkillDev tools
Single CNN backbone with one shallow Dense neck per organ and mixed sigmoid (binary) + softmax (multi-class severity) heads, trained with a dict of losses so each organ is calibrated independently while sharing visual features
Ready to connect★ 61
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cv-per-patient-slice-maxpool-aggregationSkillDev tools
Aggregate per-slice CNN predictions into a single patient-level injury score by mean-pooling across TTA copies first, then max-pooling across slices — the worst-slice wins, which matches the medical reality that one bad slice is enough to grade the patient
Ready to connect★ 61
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cv-percentile-contrast-stretchSkillDev tools
Normalize high-dynamic-range satellite or medical imagery to [0,1] using per-channel percentile clipping to suppress outliers while preserving relative contrast
Ready to connect★ 61
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cv-pfbeta-threshold-optimizationSkillDev tools
Grid-searches the optimal classification threshold to maximize probabilistic F-beta score on validation predictions.
Ready to connect★ 61
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cv-point-centered-fixed-patch-croppingSkillDev tools
Convert (x, y, class) point annotations into a CNN classification training set by cropping fixed-size square patches centered on each point, using a numpy shape check to silently reject border-clipped crops
Ready to connect★ 61
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cv-prediction-map-stitching-averagingSkillDev tools
Stitch overlapping tile predictions into a full-resolution output by accumulating probabilities and dividing by per-pixel overlap counts
Ready to connect★ 61
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cv-progressive-dropout-unetSkillDev tools
Apply lower dropout in shallow/final U-Net layers and higher dropout in deep layers to preserve spatial detail while regularizing abstract features
Ready to connect★ 61
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cv-quantile-slice-samplingSkillDev tools
Samples a fixed number of slices from variable-length CT/MRI stacks using quantile indexing to produce consistent input depth.
Ready to connect★ 61
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cv-quantile-threshold-prevalence-matchingSkillDev tools
Sets the binary classification threshold as a prediction quantile matching the expected positive prevalence rate, avoiding manual threshold tuning.
Ready to connect★ 61
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cv-rotation-tta-segmentationSkillDev tools
Test-time augmentation via 4 rotation angles (0/90/180/270), applying inverse rotation to each prediction before averaging
Ready to connect★ 61
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cv-sigmoid-normalized-rmseSkillDev tools
Sigmoid-transformed normalized RMSE that maps error from [0,inf) to a bounded (0,1] similarity score using R2-score ratio
Ready to connect★ 61
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