LIU42/FlowerClassify

基于 ResNet 的花卉分类识别系统。

25
/ 100
Experimental

Implements end-to-end training and inference pipelines using PyTorch with ResNet18 backbone, exports models to ONNX format for optimized inference via ONNX Runtime, and provides containerized Flask-based REST API deployment with configurable precision (fp32/fp16) and execution providers. Trained on cleaned, multi-source Kaggle flower datasets using transfer learning from pretrained weights.

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No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 8 / 25
Maturity 8 / 25
Community 7 / 25

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47

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3

Language

Python

License

Last pushed

Aug 26, 2025

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