import os from PIL import Image from ultralytics import YOLO import gradio as gr from huggingface_hub import snapshot_download model_path = "/best_int8_openvino_model" def load_model(repo_id): download_dir = snapshot_download(repo_id) print(download_dir) path = os.path.join(download_dir, "best_int8_openvino_model") print(path) detection_model = YOLO(path, task='detect') return detection_model def predict(pilimg): source = pilimg # x = np.asarray(pilimg) # print(x.shape) result = detection_model.predict(source, conf=0.5, iou=0.6) img_bgr = result[0].plot() out_pilimg = Image.fromarray(img_bgr[..., ::-1]) # RGB-order PIL image return out_pilimg REPO_ID = "kim1688/ironman_minions_yolov8" detection_model = load_model(REPO_ID) gr.Interface(fn = predict, inputs = gr.Image(type="pil"), outputs = gr.Image(type="pil") ).launch(share=True)