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| #!/usr/bin/env python | |
| # coding: utf-8 | |
| # In[ ]: | |
| from ultralytics import YOLO | |
| from PIL import Image, ImageDraw, ImageFont | |
| import gradio as gr | |
| from huggingface_hub import snapshot_download | |
| import os | |
| import numpy as np | |
| # Best Yolov8 trained model | |
| best_yolo_model = "best.pt" | |
| 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): | |
| detection_model = YOLO(best_yolo_model, task='detect') | |
| result = detection_model.predict(pilimg, conf=0.4, iou=0.5) | |
| #result = detection_model.predict(pilimg) | |
| obb = result[0].obb | |
| confs = obb.conf | |
| #print("obb : ", obb) | |
| #print( confidence : ", confs) | |
| img_bgr = result[0].plot() | |
| out_pilimg = Image.fromarray(img_bgr[..., ::-1]) # RGB-order PIL image | |
| # Show warning if no object is detected | |
| if len(result[0].obb.cls) == 0: | |
| gr.Warning("No object detected!") | |
| return out_pilimg | |
| REPO_ID = "ITI107-2024S2/8035531F" | |
| #detection_model = load_model(REPO_ID) | |
| title = "Detect Durian and Mangosteen (King and Queen of Fruits) In The Image" | |
| interface = gr.Interface( | |
| fn=predict, | |
| inputs=gr.Image(type="pil", label="Input Image"), | |
| outputs=gr.Image(type="pil", label="Object Detection With Confidence Level"), | |
| title=title, | |
| ) | |
| # Launch the interface | |
| interface.launch(share=True) | |
| # In[ ]: | |