| import gradio as gr | |
| import matplotlib.pyplot as plt | |
| from sentence_transformers import SentenceTransformer | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| def predict(im1, im2): | |
| model = SentenceTransformer('sentence-transformers/clip-ViT-B-16') | |
| emb = model.encode([im1, im2]) | |
| sim = cosine_similarity(emb)[0][1] | |
| if sim > .90: | |
| return sim, "SAME PERSON, UNLOCK PHONE" | |
| else: | |
| return sim, "DIFFERENT PEOPLE, DON'T UNLOCK" | |
| description = "A simple vision app that 'unlocks' a phone if two faces are similar." | |
| title = "Simple Face Id" | |
| interface = gr.Interface(fn=predict, | |
| inputs= [gr.Image(type="pil", source="webcam"), | |
| gr.Image(type="pil", source="webcam")], | |
| outputs= [gr.Number(label="Similarity"), | |
| gr.Textbox(label="Message")] | |
| ) | |
| interface.launch(debug=True) |