import gradio as gr
from transformers import DetrImageProcessor, DetrForObjectDetection
import torch
import supervision as sv

def anylize(img):
    id2label = {k: v['name'] for k,v in categories.items()}
    box_annotator = sv.BoxAnnotator()
    image = img

    with torch.no_grad():

        # load image and predict
        inputs = image_processor(images=image, return_tensors='pt')
        outputs = model(**inputs)
    
        # post-process
        target_sizes = torch.tensor([image.shape[:2]])
        results = image_processor.post_process_object_detection(
            outputs=outputs, 
            threshold=0.8, 
            target_sizes=target_sizes
        )[0]

    # annotate
    detections = sv.Detections.from_transformers(transformers_results=results).with_nms(threshold=0.5)
    labels = [f"{id2label[class_id]} {confidence:.2f}" for _, confidence, class_id, _ in detections]
    frame = box_annotator.annotate(scene=image.copy(), detections=detections, labels=labels)

gr.Interface.load("models/Guy2/AirportSec-100epoch").launch()