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 |
Model Plot
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