import numpy as np from PIL import Image import gradio as gr from main import predict def process_image(image): if image is not None: if not isinstance(image, np.ndarray): image = np.array(Image.open(image)) print(image) translated_image = predict(image) return translated_image return None with gr.Blocks() as demo: gr.Markdown( """

Manga Translator

""" ) with gr.Row(): with gr.Column(scale=1): image_input = gr.Image() submit_button = gr.Button("Translate") with gr.Column(scale=1): image_output = gr.Image() submit_button.click(process_image, inputs=image_input, outputs=image_output) examples = gr.Examples(examples=[ ["./examples/ex1.jpg"], ["./examples/ex2.jpg"], ["./examples/ex3.jpg"], ["./examples/ex4.jpg"], ], inputs=image_input) if __name__ == "__main__": demo.launch()