detr-resnet-50_finetuned_cppe5

# Código para usar el modelo
from transformers import DetrForObjectDetection, DetrImageProcessor
import torch
from PIL import Image
import requests

# Cargar modelo e imagen
detr = DetrForObjectDetection.from_pretrained('AtomGradient/detr-resnet-50_finetuned_cppe5')
processor = DetrImageProcessor.from_pretrained('AtomGradient/detr-resnet-50_finetuned_cppe5')
url = 'URL_DE_LA_IMAGEN'
image = Image.open(requests.get(url, stream=True).raw)

# Procesar imagen
inputs = processor(images=image, return_tensors='pt')
outputs = detr(**inputs)

# Extraer boxes
target_sizes = torch.tensor([image.size[::-1]])
results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.9)[0]

# Mostrar resultados
for score, label, box in zip(results['scores'], results['labels'], results['boxes']):
    box = [round(i, 2) for i in box.tolist()]
    print(f'Score: {score.item()}, Label: {label.item()}, Box: {box}')