| import matplotlib.pyplot as plt |
| from sentence_transformers import SentenceTransformer |
| from sklearn.metrics.pairwise import cosine_similarity |
| import gradio as gr |
|
|
| model = SentenceTransformer("clip-ViT-B-16") |
| def predict(im1, im2): |
| |
| embeddings = model.encode([im1,im2]) |
| cos_sim = cosine_similarity(embeddings) |
| sim = cos_sim[0][1] |
| if sim > 0.90: |
| return sim, "SAME PERSON, UNLOCK PHONE" |
| else: |
| return sim, "DIFFERENT PEOPLE, DON'T UNLOCK" |
|
|
| interface = gr.Interface(fn=predict, |
| inputs= [gr.Image(type="pil", source="webcam"), |
| gr.Image(type="pil",source="webcam")], |
| title="FaceID App", |
| description="This is a FaceID app using Sentence Transformer as part of week 3 end to end vision application project on CoRise by Abubakar Abid!", |
| outputs= [gr.Number(label="Similarity"), |
| gr.Textbox(label="Message")] |
| ) |
|
|
| interface.launch() |
|
|
