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license: apache-2.0 |
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language: |
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- et |
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- en |
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tags: |
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- image classifier |
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metrics: |
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- accuracy |
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--- |
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# Introduction |
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Hello, and welcome to the Estonian Bird Classifier model page! This model was created by Karl-Erik Kanal as a part of his Bachelor's thesis and can recognise 50 common Estonian bird species. |
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# About the model |
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The model estonian_birds_classifier is a pretrained InceptionV3 model on ImageNet weights that has been trained using transfer learning to recognise 50 bird species that can be found in Estonia. |
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The complete list of birds that it can classify can be found in the label map provided with the model. |
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The model was trained and tested using a custom-made dataset for this model, with 5926 images in the training set and 1064 images in the test set. |
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On the test set, the model achieved 74% accuracy, 89% Top-3 accuracy and 91% Top-5 accuracy with a loss of 1.119. |
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In comparison, the [Google AIY bird classifier](https://tfhub.dev/google/aiy/vision/classifier/birds_V1/1) that can recognise 45 species of the 50 achieved 71% accuracy on the test set with the 5 species taken out, while this model achieved 75% accuracy with the same 45 species. |
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# How to use |
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**The model requires the images to be resized to 150 x 150 and normalized before predicting.** You can use the ImageDataGenerator class from keras.preprocessing.image to achieve this. |
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The images should be well-cropped to achieve the best results. |
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You can load in the model like you would load in other Keras type models by using the load_model function. |
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You can load the labels into a dataframe using pandas read_csv. The labels of the birds are provided both in Estonian and in Latin. |
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model = keras.models.load_model('estonian_birds_classifier.h5') |
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labels = pd.read_csv('ebc_labelmap.csv', sep=";") |
