wenmin-wu/ds-skills

60Stars on the repository
200Mods indexed here, across every type
4mo agoLast push, which is what freshness is scored on
noneNo LICENSE: all rights reserved, so bodies are not copied

wenmin-wu/ds-skills

Skill Claude CodeCodex

Convert raw DICOM pixel arrays to Hounsfield Units using per-slice RescaleSlope/RescaleIntercept, with outside-scanner clamping.

not rated 60 +1 4mo ago A 38 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Order DICOM slices into a coherent 3D volume by sorting on ImagePositionPatient[2] (the Z coordinate in patient space), with a filename-integer fallback for series whose tag is missing — never trust filename alphabetical order, never trust InstanceNumber.

not rated 60 +1 4mo ago A 61 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Decodes MRI scan plane (axial, coronal, sagittal) from DICOM ImageOrientationPatient direction cosine vectors.

not rated 60 +1 4mo ago A 33 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Read DICOM X-ray files with VOI LUT transformation and MONOCHROME1 inversion for correct pixel intensity rendering.

not rated 60 +1 4mo ago A 33 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Use a soft macro-F1 loss 1 − mean(2·tp / (2·tp + fp + fn)) computed from raw sigmoid probabilities (no thresholding) as a direct training objective for multi-label classification, optionally combined with BCE — closes the gap between training surrogate and the F1 metric the leaderboard scores.

not rated 60 +1 4mo ago A 75 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Recover (x, y, class) point labels from color-coded dot-annotation image pairs via absdiff + blackout masking + Laplacian-of-Gaussian blob detection + center-pixel RGB classification.

not rated 60 +1 4mo ago A 51 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Reshape dual-view stacked channels into doubled batch dimension for shared backbone, then concatenate with tabular features for classification.

not rated 60 +1 4mo ago A 30 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Load EfficientDet pretrained on COCO with the original 90-class head, then swap in a fresh HeadNet with your own numclasses — keeps the BiFPN feature pyramid pretrained and only retrains the classification head, the canonical transfer-learning recipe for the effdet PyTorch port.

not rated 60 +1 4mo ago A 64 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Tracks an Exponential Moving Average of model weights during training and evaluates both live and EMA models for more stable predictions.

not rated 60 +1 4mo ago A 31 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

GPU-accelerated k-NN regression on CLIP image embeddings using cosine distance and inverse-distance-power weighting to predict target embedding vectors.

not rated 60 +1 4mo ago A 34 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Collect test predictions each epoch via callback and combine with exponentially increasing weights favoring later epochs.

not rated 60 +1 4mo ago A 27 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Aggregate per-slice predictions into exam-level labels that satisfy a competition's mutual-exclusion hierarchy (positive vs negative vs indeterminate), using a top-down rule cascade — first decide the exam class, then conditionally rescale the dependent labels so the submission stays internally consistent.

not rated 60 +1 4mo ago A 63 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Pad variable-length per-slice sequences to a fixed batch length, carry a 0/1 mask alongside, and multiply per-slice BCE by the mask before reducing — gives correct per-exam loss with batched training and zero contamination from padding tokens.

not rated 60 +1 4mo ago A 60 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Models multiple conditions with a single flat output layer of Nlabels × Nclasses logits, sliced into per-condition softmax at inference.

not rated 60 +1 4mo ago A 35 tokens

cv-focal-loss

63

wenmin-wu/ds-skills

Skill Claude CodeCodex

Alpha-weighted focal loss that down-weights easy examples to focus training on hard, misclassified pixels in imbalanced segmentation tasks.

not rated 60 +1 4mo ago A 31 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Encode motion and velocity by computing per-channel pixel differences between consecutive frames instead of stacking raw frames for RL visual observations.

not rated 60 +1 4mo ago A 32 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Average per-frame sigmoid predictions across sampled video frames to produce a stable video-level classification probability.

not rated 60 +1 4mo ago A 26 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Unfreezes backbone layers for fine-tuning while keeping BatchNorm layers frozen to preserve pretrained running statistics.

not rated 60 +1 4mo ago A 31 tokens

cv-gem-pooling

68

wenmin-wu/ds-skills

Skill Claude CodeCodex

Replaces global average pooling with Generalized Mean (GeM) pooling, using a learnable or fixed exponent to emphasize high-activation regions.

not rated 60 +1 4mo ago A 35 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Clean noisy numeric strings from generative model output by removing invalid characters, fixing malformed floats, and handling multiple decimal points.

not rated 60 +1 4mo ago A 32 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Accumulates gradients over multiple mini-batches before stepping the optimizer, simulating larger effective batch sizes.

not rated 60 +1 4mo ago A 28 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Resolve overlapping instance masks by greedily assigning contested pixels to higher-confidence predictions using a running occupancy map.

not rated 60 +1 4mo ago A 28 tokens

wenmin-wu/ds-skills

Skill Claude CodeCodex

Overlay real hair PNGs (masked via threshold) onto dermoscopy images to simulate body-hair occlusion as a domain-specific augmentation.

not rated 60 +1 4mo ago A 33 tokens

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