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ad540f4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | import gradio as gr
from tensorflow.keras.models import load_model
from tensorflow.keras.layers import Input
from tensorflow_addons.layers import InstanceNormalization
import numpy as np
from PIL import Image
def load_image(img):
with open(img.name, 'rb') as f:
img_data = f.read()
return img_data
def translate_image(image):
# load the model
cust = {'InstanceNormalization': InstanceNormalization}
model_AtoB = load_model('/Users/riyaparikh/Desktop/ML Projects /CycleGAN/g_model_BtoA_004000.h5', cust)
# convert to numpy array
image_np = np.array(image)
# image = Resizing(256, 256)(image)
# normalize pixels
image_np = (image_np - 127.5) / 127.5
# add batch dimension
image_np = np.expand_dims(image_np, axis=0)
# translate image
image_tar = model_AtoB.predict(image_np)
# scale from [-1,1] to [0,1]
image_tar = (image_tar + 1) / 2.0
# convert back to PIL image
image_tar = (image_tar[0] * 255).astype(np.uint8)
image_tar = Image.fromarray(image_tar)
return image_tar
# create the interface
input_image = gr.inputs.Image(type="pil")
output_image = gr.outputs.Image(type="pil")
iface = gr.Interface(fn=translate_image, inputs=input_image, outputs=output_image,
title="Van Gogh-ify Your Images🎨👨🎨",
description="Translate an image from one domain to another using CycleGAN")
iface.launch()
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