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Update main.py
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main.py
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@@ -3,36 +3,12 @@ import keras # for network
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import gradio # for interface
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import matplotlib.pyplot # for colormap
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import matplotlib.colors # for color conversion
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# model1 = keras.models.Sequential()
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# model1.add(keras.layers.InputLayer(input_shape=(101, 636, 1)))
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# model1.add(keras.layers.Conv2D(4, (9, 9), activation='relu', padding='same', strides=1))
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# model1.add(keras.layers.Conv2D(4, (9, 9), activation='relu', padding='same'))
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# model1.add(keras.layers.Conv2D(8, (7, 7), activation='relu', padding='same', strides=1))
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# model1.add(keras.layers.Conv2D(8, (7, 7), activation='relu', padding='same'))
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# model1.add(keras.layers.Conv2D(16, (5, 5), activation='relu', padding='same'))
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# model1.add(keras.layers.Conv2D(16, (5, 5), activation='relu', padding='same', strides=1))
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# model1.add(keras.layers.Conv2D(16, (3, 3), activation='relu', padding='same'))
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# model1.add(keras.layers.Conv2D(16, (3, 3), activation='relu', padding='same', strides=1))
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# model1.add(keras.layers.Conv2D(16, (2, 2), activation='relu', padding='same'))
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# model1.add(keras.layers.Conv2D(16, (2, 2), activation='relu', padding='same', strides=1))
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# model1.add(keras.layers.UpSampling2D((1, 1)))
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# model1.add(keras.layers.Conv2D(16, (2, 2), activation='relu', padding='same'))
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# model1.add(keras.layers.UpSampling2D((1, 1)))
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# model1.add(keras.layers.Conv2D(8, (3, 3), activation='relu', padding='same'))
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# model1.add(keras.layers.UpSampling2D((1, 1)))
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# model1.add(keras.layers.Conv2D(4, (7, 7), activation='tanh', padding='same'))
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# model1.add(keras.layers.UpSampling2D((1, 1)))
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# model1.add(keras.layers.Conv2D(3, (9, 9), activation='tanh', padding='same'))
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from huggingface_hub import from_pretrained_keras
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model1 = from_pretrained_keras("cmudrc/microstructure-colorization")
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#Loading the weights in the architecture (The file should be stored in the same directory as the code)
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model1.load_weights('modelV13_500trained_1.h5')
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# Get the color map by name:
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cm = matplotlib.pyplot.get_cmap('RdBu')
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import gradio # for interface
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import matplotlib.pyplot # for colormap
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import matplotlib.colors # for color conversion
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import huggingface_hub
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model1 = huggingface_hub.from_pretrained_keras("cmudrc/microstructure-colorization")
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#Loading the weights in the architecture (The file should be stored in the same directory as the code)
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# model1.load_weights('modelV13_500trained_1.h5')
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# Get the color map by name:
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cm = matplotlib.pyplot.get_cmap('RdBu')
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