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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ model/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
app.py ADDED
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+ import gradio as gr
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+ import numpy as np
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+ import tensorflow as tf
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+
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+ from PIL import Image
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+
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+ model = tf.keras.models.load_model('model')
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+
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+ def predict_model(im):
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+ im = tf.image.convert_image_dtype(im,tf.float32)
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+ im = tf.expand_dims(im,axis=0)
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+
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+ pred = model.predict(im)
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+ pred = pred[0]
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+ pred = tf.clip_by_value(pred, 0.0, 1.0)
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+
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+ pred = Image.fromarray((np.array(pred) * 255).astype(np.uint8))
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+ return pred
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+
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+ inimage = gr.Image(shape=(None,None))
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+ inimage.style(width=512,height=512)
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+
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+ outimage = gr.Image(shape=(None,None))
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+ outimage.style(width=512,height=512)
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+
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+ app = gr.Interface(fn=predict_model, inputs=inimage, outputs=outimage,examples=['./assets/examples/creature.jpg',
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+ "./assets/examples/butterfly.jpeg",
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+ "./assets/examples/bw.jpg",
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+ "./assets/examples/hillbefore.jpg"])
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+
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+ app.launch()
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+
assets/examples/butterfly.jpeg ADDED
assets/examples/bw.jpg ADDED
assets/examples/creature.jpg ADDED
assets/examples/gradio_demo.png ADDED
assets/examples/hillbefore.jpg ADDED
model/fingerprint.pb ADDED
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+ size 55
model/keras_metadata.pb ADDED
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model/saved_model.pb ADDED
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model/variables/variables.data-00000-of-00001 ADDED
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model/variables/variables.index ADDED
Binary file (18.9 kB). View file
 
requirements.txt ADDED
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+ gradio
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+ numpy
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+ tensorflow-cpu