Add application file

app.py

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+#!/usr/bin/env python
+
+import pathlib
+import os
+import cv2
+import gradio as gr
+import huggingface_hub
+import numpy as np
+import functools
+
+from ultralytics import YOLO
+from ultralytics.yolo.engine.results import Results
+
+TITLE = 'Age and Gender Estimation with Transformers from Face and Body Images in the Wild'
+DESCRIPTION = 'This is an official demo for https://github.com/...'
+
+HF_TOKEN = os.getenv('HF_TOKEN')
+
+def load_model():
+    path = huggingface_hub.hf_hub_download('iitolstykh/demo_yolov8_detector',
+                                           'yolov8x_person_face.pt',
+                                           use_auth_token=HF_TOKEN)
+    yolo = YOLO(path)
+    yolo.fuse()
+
+    return yolo
+
+def detect(image: np.ndarray, detector: YOLO) -> np.ndarray:
+    detector_kwargs = {'conf': 0.5, 'iou': 0.5, 'half': False, 'verbose': False}
+
+    results: Results = detector.predict(image, **detector_kwargs)[0]
+    out_im = results.plot()
+
+    return out_im
+
+
+detector = load_model()
+
+image_dir = pathlib.Path('images')
+examples = [[path.as_posix()] for path in sorted(image_dir.glob('*.jpg'))]
+
+func = functools.partial(detect, detector=detector)
+
+gr.Interface(
+    fn=func,
+    inputs=gr.Image(label='Input', type='numpy'),
+    outputs=gr.Image(label='Output', type='numpy'),
+    examples=examples,
+    examples_per_page=30,
+    title=TITLE,
+    description=DESCRIPTION,
+).launch(show_api=False)

requirements.txt

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+Cython==0.29.28
+ultralytics
+timm==0.8.13.dev0
+huggingface_hub
+gradio