TileFlow
High-performance tile-based image processing for scientific computing
Process gigapixel images with minimal memory footprint through intelligent tiling and reconstruction. Designed for microscopy, whole-slide imaging, and large-scale computer vision workflows.
🚀 Key Features
- 🧠 Memory Efficient: Process images larger than RAM using intelligent tiling
- 🔬 Multi-Channel Ready: Native CHW format support for microscopy workflows
- 🔧 Seamless Reconstruction: Intelligent overlap handling eliminates artifacts
- 🎯 Pluggable Pipeline: Custom processing functions integrate seamlessly
📦 Installation
pip install tileflow
📄 License
MIT License - see LICENSE file for details.
🙏 Acknowledgments
Valentin Poque - Core development and architecture (July-September 2025)
Metadata
Release files for tileflow 0.7.11
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| tileflow-0.7.11.tar.gz | 7.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| tileflow-0.7.11-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.6 kB
Release files / tileflow-0.7.11.tar.gz
| Download URL | tileflow-0.7.11.tar.gz |
|---|---|
| Size | 7.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / tileflow-0.7.11-py3-none-any.whl
| Download URL | tileflow-0.7.11-py3-none-any.whl |
|---|---|
| Size | 9.1 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| Uploaded via |
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