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| import gradio as gr | |
| from src.model import ImageEmbedding | |
| image_embedding = ImageEmbedding() | |
| def compare_faces(person_image, id_image): | |
| embeddings1, img1 = image_embedding.get_face_embedding(person_image) | |
| embeddings2, img2 = image_embedding.get_face_embedding(id_image) | |
| similarity = image_embedding.cosine_similarity(embeddings1, embeddings2) | |
| return similarity, img1, img2 | |
| with gr.Blocks() as demo: | |
| gr.Markdown('# Image matcher') | |
| with gr.Row(): | |
| with gr.Column(): | |
| person_image = gr.Image(label="Person Image", type="numpy", height=256) | |
| sim_score = gr.Textbox(label="Similarity Score") | |
| with gr.Column(): | |
| id_image = gr.Image(label="ID Image", type="numpy", height=256) | |
| submit_button = gr.Button("Submit") | |
| submit_button.click(fn=compare_faces, | |
| inputs=[person_image, id_image], | |
| outputs=[sim_score, person_image, id_image]) | |
| if __name__ == "__main__": | |
| demo.launch() |