| import os | |
| import gradio as gr | |
| from deepface import DeepFace | |
| def inference(image1,image2,model_name,dist_met): | |
| result = DeepFace.verify(img1_path = image1, img2_path = image2,model_name=model_name,distance_metric=dist_met) | |
| return result["verified"],result["distance"],result["max_threshold_to_verify"],result["model"],result["similarity_metric"] | |
| examples=[['mona.jpeg','mona.jpeg','VGG-Face','cosine'],['mona.jpeg','pearl.jpeg','Facenet','euclidean']] | |
| title = "DeepFace" | |
| description = "Gradio demo for DeepFace for face verification: verifies face pairs as same person or different persons. To use it, simply upload your images, or click one of the examples to load them. Read more at the links below." | |
| article = "<p style='text-align: center'><a href='https://github.com/serengil/deepface' target='_blank'>Github Repo</a></p>" | |
| gr.Interface(inference,["image","image",gr.inputs.Dropdown(choices=["VGG-Face", "Facenet", "OpenFace", "DeepFace"], type="value", default="VGG-Face", label="model name"),gr.inputs.Radio(choices=["cosine", "euclidean", "euclidean_l2"], type="value", default="cosine", label="distance metric")],[gr.outputs.Label(label="same person"),gr.outputs.Label(label="distance"),gr.outputs.Label(label="max threshold to verify"),gr.outputs.Label(label="model"),gr.outputs.Label(label="similarity metric")],enable_queue=True,examples=examples, title=title,description=description,article=article,theme="darkdefault").launch(debug=True) |