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@@ -14,6 +14,7 @@ Hello and welcome to the Estonian Bird Classifier model page! This model is crea
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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 full 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.
@@ -21,7 +22,8 @@ In comparison, the [Google AIY bird classifier](https://tfhub.dev/google/aiy/vis
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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 simply 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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  # 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 full list of birds that it can classify can be found in the label map provided with the model.
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+
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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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+
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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')