| import torch | |
| import gradio as gr | |
| import matplotlib.pyplot as plt | |
| from sentence_transformers import SentenceTransformer | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| model = SentenceTransformer('clip-ViT-L-14') | |
| def predict(im1, im2): | |
| embeding = model.encode([im1, im2]) | |
| sim = cosine_similarity(embeding) | |
| sim = sim[0][1] | |
| if sim > 0.75: | |
| return sim, "SAME PERSON, UNLOCK PHONE" | |
| else: | |
| return sim, "DIFFERENT PEOPLE, DON'T UNLOCK" | |
| title="Face-id Application Demo" | |
| description = "Upload similar/different images to compare Image similarity for face-id demo" | |
| article = """ | |
| - Select an image from the examples provided as demo image | |
| - Click submit button to make Image classification | |
| - Click clear button to try new Image for classification | |
| """ | |
| img_upload = gr.Interface( | |
| fn=predict, | |
| inputs= [gr.Image(type="pil", source="upload"), | |
| gr.Image(type="pil", source="upload")], | |
| outputs= [gr.Number(label="Similarity"), | |
| gr.Textbox(label="Message")], | |
| title=title, | |
| description=description, | |
| article=article, | |
| examples=[['examples/img1.jpg', 'examples/img2.jpg'], | |
| ['examples/img1.jpg', 'examples/img3.jpg']] | |
| ) | |
| webcam_upload = 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")], | |
| title=title, | |
| description=description, | |
| article=article, | |
| ) | |
| face_id = gr.TabbedInterface( | |
| [img_upload, webcam_upload], | |
| ["Upload-Image", "Use Webcam"]) | |
| face_id.launch(debug=True) | |