first commit

.gitignore

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+.DS_Store
+.ipynb_checkpoints/

app.py

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+import gradio as gr
+import tensorflow as tf
+
+IMG_SIZE = (128, 128)
+
+# load keras model
+model_path = 'my_model.h5'
+model = tf.keras.models.load_model(model_path)
+
+categories = ('happy', 'sad')
+
+def classify_image(img):
+    img_array_expanded_dims = img.reshape((-1, 128, 128, 3))
+    prediction = model.predict(img_array_expanded_dims)
+    prediction_prob = float(tf.nn.sigmoid(prediction))
+    probs = [prediction_prob, 1-prediction_prob]
+    return dict(zip(categories, probs))
+
+gr_image = gr.inputs.Image(shape=IMG_SIZE)
+label = gr.outputs.Label()
+examples = ['happy.jpg', 'sad.jpg']
+
+iface = gr.Interface(fn=classify_image, inputs=gr_image, outputs=label, examples=examples)
+iface.launch(inline=False)

my_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5ee3128a8b6ccdf0b26fa8c0b7caafb77f7b7c0adca4763eaf6084b436e0c595
+size 13549184

requirements.txt

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+tensorflow