Delete app.py

app.py

@@ -1,43 +0,0 @@
-import gradio as gr
-import keras
-from keras.models import load_model
-# from keras_contrib.layers.normalization.instancenormalization import InstanceNormalization
-from tensorflow_addons.layers import InstanceNormalization
-import matplotlib.pyplot as plt
-import numpy as np
-
-cust = {'InstanceNormalization': InstanceNormalization}
-model=load_model('g_model_AtoB_002160.h5',cust)
-# model=load_model('g_model_AtoB_000540.h5',cust)
-
-path  = [['ex1.jpg'], ['ex2.jpg'], ['ex3.jpg'],['ex4.jpg'],['ex5.jpg']]
-
-def show_preds_image(image_path):
-    A = plt.imread(image_path)
-    # A = (A - 127.5) / 127.5
-    A = np.expand_dims(A,axis=0)
-    B = model.predict(A)
-    B = np.squeeze(B,axis=0)
-    B = (B + 1) / 2.0
-    return B
- 
-inputs_image = [
-    gr.components.Image(shape=(256,256),type="filepath", label="Input Image"),
-]
-outputs_image = [
-    gr.components.Image(shape=(256,256),type="numpy", label="Output Image").style(width=256, height=256),
-]
-interface_image = gr.Interface(
-    fn=show_preds_image,
-    inputs=inputs_image,
-    outputs=outputs_image,
-    title="photo2monet",
-    examples=path,
-    cache_examples=False,
-)
-
-gr.TabbedInterface(
-    [interface_image],
-    tab_names=['Image inference']
-).queue().launch()
-