image-analysis-art

Community

Quantify art style, color, and texture from images.

Authorxjtulyc
Version1.0.0
Installs0

System Documentation

What problem does it solve?

It helps you analyze paintings computationally by turning raw artwork images into measurable style, color, and texture signals you can compare or cluster.

Core Features & Use Cases

  • CNN feature extraction & visualization: Extract ResNet50/VGG16 embedding vectors and use PCA/UMAP or t-SNE to explore style clusters.
  • WikiArt-driven style classification: Fine-tune a pretrained CNN to predict WikiArt style/artist/genre labels and create attribution via Grad-CAM.
  • Color + texture quantification: Compute dominant palettes (k-means), compare color distributions (HSV histograms with Bhattacharyya distance), and characterize brushstroke texture using Gabor filterbanks and rotation-invariant LBP.

Quick Start

Use the image-analysis-art Skill to extract ResNet50 features from a folder of WikiArt paintings and cluster them to identify style groupings.

Dependency Matrix

Required Modules

torchtorchvisionopencv-pythonnumpymatplotlibscikit-learnumap-learndatasetsscikit-imagepillow

Components

referencesassets

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: image-analysis-art
Download link: https://github.com/xjtulyc/awesome-rosetta-skills/archive/main.zip#image-analysis-art

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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