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Dragon detector with Tensor Flow

This is a simple tensorflow model to detect dragon in images. If you just want to test the trained model, make sure you have the following packages:

tensorflow keras sklearn-deap datasets transformers[torch] sentencepiece

Predict

To run prediction you need to run below code:

from huggingface_hub import from_pretrained_keras

model = from_pretrained_keras("hadilq/dragon-notdragon")

img = keras.preprocessing.image.load_img(filename, target_size=(224, 224))
x = keras.preprocessing.image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = keras.applications.vgg16.preprocess_input(x)
prediction = model.predict(x)
print("model:", filename, "dragon" if prediction[0][0] >= 0.99 else "notdragon")

Additionally, you can check https://replicate.com/hadilq/dragon-notdragon to play around.

Training procedure

I trained it in Google colab, where you can find the original code in training directory.

Training hyperparameters

The following hyperparameters were used during training:

Hyperparameters Value
name Adam
weight_decay None
clipnorm None
global_clipnorm None
clipvalue None
use_ema False
ema_momentum 0.99
ema_overwrite_frequency None
jit_compile True
is_legacy_optimizer False
learning_rate 9.999999747378752e-05
beta_1 0.9
beta_2 0.999
epsilon 1e-07
amsgrad False
training_precision float32

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