itsTomLie/Gender_Classification

1import gradio as gr2import numpy as np3import os4 5from PIL import Image6from transformers import pipeline7 8def predict_image(image):9    pipe = pipeline("image-classification", model="rizvandwiki/gender-classification")10 11    if isinstance(image, np.ndarray):12        image = Image.fromarray(image.astype('uint8'))13    elif isinstance(image, str): 14        image = Image.open(image)15 16    result = pipe(image)17 18    label = result[0]['label']19    confidence = result[0]['score']20 21    return label, confidence22 23example_images = [24    os.path.join("examples", img_name) for img_name in sorted(os.listdir("examples"))25]26 27interface = gr.Interface(28    fn=predict_image,29    inputs=gr.Image(type="numpy", label="Upload an Image"),30    outputs=[gr.Textbox(label="Prediction"), gr.Textbox(label="Confidence")],31    examples=example_images32)33 34interface.launch()