app.py

import numpy as np
from deepface import DeepFace
import gradio as gr


def save_identity(image , name):
  try:
    embeddings = DeepFace.represent(image , model_name="Facenet")
    return str(embeddings)
  except Exception as error:
    return str(error)


# image_input = gr.inputs.Image(shape=(160,160))
label_output = gr.outputs.Textbox()

# Create the Gradio interface
# gr.Interface(fn=predict_image, inputs=image_input, outputs=label_output).launch()


# Create Gradio interfaces for input and output
image_input = gr.inputs.Image(shape=(160, 160))
label_input = gr.inputs.Textbox(label="Enter Label")
output_image = gr.outputs.Image(type="numpy")

# Create the Gradio interface
interface = gr.Interface(
    fn=save_identity,
    inputs=[image_input, label_input],
    outputs=label_output,
    title="Face Identification",
    description="Upload an image, enter a label, and get the output image.",
)

# Launch the Gradio interface
interface.launch()