app.py

import gradio as gr
import cv2
import numpy as np
import tensorflow as tf
from tensorflow.keras.applications import MobileNetV2
from tensorflow.keras.layers import Conv2DTranspose, Concatenate, Activation
from tensorflow.keras.models import Model

def load_model():
    base_model = MobileNetV2(input_shape=(None, None, 3), include_top=False)
    layer_names = [
        'block_1_expand_relu',   # 64x64
        'block_3_expand_relu',   # 32x32
        'block_6_expand_relu',   # 16x16
        'block_13_expand_relu',  # 8x8
        'block_16_project',      # 4x4
    ]
    layers = [base_model.get_layer(name).output for name in layer_names]
    down_stack = Model(inputs=base_model.input, outputs=layers)
    down_stack.trainable = False

    up_stack = [
        Conv2DTranspose(512, 3, strides=2, padding='same'),
        Concatenate(),
        Activation('relu'),
        Conv2DTranspose(256, 3, strides=2, padding='same'),
        Concatenate(),
        Activation('relu'),
        Conv2DTranspose(128, 3, strides=2, padding='same'),
        Concatenate(),
        Activation('relu'),
        Conv2DTranspose(64, 3, strides=2, padding='same'),
        Concatenate(),
        Activation('relu'),
        Conv2DTranspose(3, 3, strides=2, padding='same'),
        Activation('sigmoid'),
    ]

    inputs = tf.keras.layers.Input(shape=[None, None, 3])
    x = inputs

    skips = down_stack(x)
    skips = reversed(skips[:-1])

    for up, skip in zip(up_stack, skips):
        x = up(x)
        concat = Concatenate()
        x = concat([x, skip])

    model = Model(inputs=inputs, outputs=x)

    return model

model = load_model()

def sketch_image(img):
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    img = img / 255.0
    img = cv2.resize(img, (256, 256))
    img = np.expand_dims(img, axis=0)
    output = model.predict(img)
    output = np.squeeze(output, axis=0)
    output = cv2.resize(output, (img.shape[2], img.shape[1]))
    output = np.clip(output * 255, 0, 255).astype('uint8')
    return output

title = "Picture to Drawing"
description = "Turn your pictures into beautiful drawings!"
inputs = gr.inputs.Image(label="Input Image")
outputs = gr.outputs.Image(label="Output Image")
examples = [['examples/1.jpg'], ['examples/2.jpg'], ['examples/3.jpg']]
gr.Interface(sketch_image, inputs, outputs, title=title, description=description, examples=examples).launch()