sudip2003 commited on
Commit
0907920
·
verified ·
1 Parent(s): ff38766

Update app.py

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Files changed (1) hide show
  1. app.py +11 -13
app.py CHANGED
@@ -9,10 +9,10 @@ model = tf.keras.models.load_model('Model_catsVSdogs.h5')
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  # Define a function to make predictions
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  def predict_image(img):
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  # Preprocess the image
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- img = img.resize((224, 224))
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- img_array = image.img_to_array(img)
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- img_array = np.expand_dims(img_array, axis=0)
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- img_array = img_array / 255.0
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  # Make a prediction
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  prediction = model.predict(img_array)
@@ -22,14 +22,12 @@ def predict_image(img):
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  return "Dog"
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  # Create the Gradio interface
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- iface = gr.Interface(
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- fn=predict_image,
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- inputs=gr.Image(type="pil"),
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- outputs="text",
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- title="Cat and Dog Classifier",
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- description="Upload an image of a cat or a dog and the model will classify it.",
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- examples=["cat_example.jpg", "dog_example.jpg"]
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- )
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  # Launch the interface
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- iface.launch()
 
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  # Define a function to make predictions
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  def predict_image(img):
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  # Preprocess the image
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+ img = img.resize((256,256)) # Resize the image to 224x224 pixels
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+ img_array = image.img_to_array(img) # Convert the image to an array
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+ img_array = np.expand_dims(img_array, axis=0) # Add a batch dimension
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+ img_array = img_array / 255.0 # Normalize the image
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  # Make a prediction
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  prediction = model.predict(img_array)
 
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  return "Dog"
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  # Create the Gradio interface
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+
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+ interface = gr.Interface(fn=predict_image,
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+ inputs=gr.Image(type="pil"),
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+ outputs="text",
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+ title="Cat and Dog Classifier",
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+ description="Upload an image of a cat or dog and the model will predict which one it is.")
 
 
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  # Launch the interface
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+ interface.launch()