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Know More About Your Flowers 🌸
Flowerly is iOS App that uses CoreML to predict image name and information
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This app require .mlmodel file in order to run and I couldn't upload this file because of the size 😥 but you can generate it with python 2.7 & Coremltools to convert the ML Model from .caffemodel to .mlmodel.
- Download the .caffemodel (~230Mb) here, and run the following python script:
import coremltools
coreml_model = coremltools.converters.caffe.convert(('oxford102.caffemodel','deploy.prototxt'),class_labels='flower-labels.txt',image_input_names='data')
coreml_model.save('FlowerlyClassifier.mlmodel')
Drag the FlowerlyClassifier.mlmodel into the Xcode project and you can run it!
This Model from Oxford 102 Flowers Dataset
| 🌟 Uses |
|---|
| Delegate Design Pattern |
| CoreML Framework |
| Alamofire to get flower information from Wikipedia Api |
| Chameleon Framework |
| SwiftyJSON to parse the json response from the API |
and a lot more 😊 ...
- iOS 10.0+
- Xcode 11.3.1
- Python 2.7
Code and documentation copyright 2020 the authors. Code released under the MIT License.
Enjoy