Files changed (1) hide show
  1. app.py +10 -14
app.py CHANGED
@@ -5,9 +5,8 @@ import tensorflow as tf
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  from tensorflow import keras
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  from huggingface_hub import from_pretrained_keras
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-
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  model = from_pretrained_keras("keras-io/low-light-image-enhancement", compile=False)
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- examples = ['got2.png', 'gotj.png', 'goti.png' ]
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  def get_enhanced_image(data, output):
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  r1 = output[:, :, :, :3]
@@ -27,25 +26,22 @@ def get_enhanced_image(data, output):
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  x = x + r7 * (tf.square(x) - x)
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  enhanced_image = x + r8 * (tf.square(x) - x)
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  return enhanced_image
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-
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-
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  def infer(original_image):
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  image = keras.preprocessing.image.img_to_array(original_image)
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  image = image.astype("float32") / 255.0
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  image = np.expand_dims(image, axis=0)
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  output = model.predict(image)
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  output = get_enhanced_image(image, output)
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- output_image = tf.cast((output[0, :, :, :] * 255), dtype=np.uint8)
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- output_image = Image.fromarray(output_image.numpy())
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- return output_image
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-
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  iface = gr.Interface(
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  fn=infer,
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- title="Zero-DCE for low-light image enhancement",
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- description = "Implementing Zero-Reference Deep Curve Estimation for low-light image enhancement.",
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- inputs=[gr.inputs.Image(label="Original Image", type="pil")],
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- outputs=[gr.outputs.Image(label="Enhanced Image", type="numpy")],
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  examples=examples,
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- article = "**Original Author**: [Soumik Rakshit](https://github.com/soumik12345) <br>**HF Contribution**: [Harveen Singh Chadha](https://github.com/harveenchadha)<br>",
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- ).launch(debug=True, enable_queue=False, cache_examples=True)
 
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  from tensorflow import keras
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  from huggingface_hub import from_pretrained_keras
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  model = from_pretrained_keras("keras-io/low-light-image-enhancement", compile=False)
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+ examples = ['got2.png', 'gotj.png', 'goti.png']
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  def get_enhanced_image(data, output):
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  r1 = output[:, :, :, :3]
 
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  x = x + r7 * (tf.square(x) - x)
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  enhanced_image = x + r8 * (tf.square(x) - x)
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  return enhanced_image
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+
 
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  def infer(original_image):
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  image = keras.preprocessing.image.img_to_array(original_image)
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  image = image.astype("float32") / 255.0
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  image = np.expand_dims(image, axis=0)
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  output = model.predict(image)
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  output = get_enhanced_image(image, output)
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+ output_image = tf.cast(output[0, :, :, :] * 255, dtype=tf.uint8).numpy()
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+ return Image.fromarray(output_image)
 
 
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  iface = gr.Interface(
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  fn=infer,
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+ title="Zero-DCE for Low-Light Image Enhancement",
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+ description="Implementing Zero-Reference Deep Curve Estimation for low-light image enhancement.",
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+ inputs=gr.Image(label="Original Image", type="pil"),
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+ outputs=gr.Image(label="Enhanced Image"),
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  examples=examples,
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+ article="**Original Author**: [Soumik Rakshit](https://github.com/soumik12345) <br>**HF Contribution**: [Harveen Singh Chadha](https://github.com/harveenchadha)<br>",
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+ ).launch(debug=True, enable_queue=False, cache_examples=True)