🖼️ Get image shapes, analyze type, get preprocessing recommendations & check model compatibility
Project description
🖼️ imgshape — Smart Image Analysis & Preprocessing Toolkit (v2.0.0)
imgshape is a lightweight Python toolkit designed for image shape detection, dataset inspection, preprocessing recommendation, and AI model compatibility checks — all optimized for ML/DL workflows, both in research and production.
⚡️ Why use imgshape?
- 🔍 Automatically detect shape, dominant color, entropy, and type of an image.
- 🧠 Recommend preprocessing steps like resize dims, normalization, and suitable model types.
- 🖬 Analyze entire datasets to get size/shape distribution and dimension scatter plots.
- ✅ Check model compatibility (e.g. with
mobilenet_v2,resnet18, etc.). - 🌐 Supports CLI, Python API, and even a Gradio-based GUI for visual workflows.
🚀 Installation
pip install imgshape
Requires Python 3.8+ and packages: Pillow, matplotlib, seaborn, numpy, scikit-image, gradio
💻 CLI Usage
imgshape --path ./sample.jpg # Get image shape
imgshape --path ./sample.jpg --analyze # Analyze image type and entropy
imgshape --path ./sample.jpg --recommend # Recommend preprocessing steps
imgshape --dir ./images --check mobilenet_v2 # Check dataset compatibility with a model
imgshape --batch --path ./folder # Batch mode shape detection
imgshape --viz ./images # Visualize size/shape distribution
imgshape --web # Launch Gradio GUI
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