Аренда GPU для RF-DETR
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# В Ubuntu 24 системный Python managed, ставим в venv:
python3 -m venv /opt/rfdetr && source /opt/rfdetr/bin/activate
# torch+cu128 (для NVIDIA driver 570.x). На свежих 580+ можно дефолтный cu130.
pip install torch torchvision \
  --index-url https://download.pytorch.org/whl/cu128
pip install rfdetr supervision

# Inference на одном изображении:
python3 - <<'PY'
import supervision as sv
from rfdetr import RFDETRMedium
from rfdetr.assets.coco_classes import COCO_CLASSES

model = RFDETRMedium()
detections = model.predict('https://media.roboflow.com/dog.jpg', threshold=0.5)
labels = [COCO_CLASSES[i] for i in detections.class_id]
img = sv.BoxAnnotator().annotate(detections.metadata['source_image'], detections)
img = sv.LabelAnnotator().annotate(img, detections, labels)
PY

python3 -m venv /opt/rfdetr && source /opt/rfdetr/bin/activate
pip install rfdetr

python3 - <<'PY'
from rfdetr import RFDETRMedium

model = RFDETRMedium()
model.train(
    dataset_dir='/data/my_dataset',  # COCO-формат
    epochs=50,
    batch_size=16,
    grad_accum_steps=1,  # на 4090 48 ГБ хватает
    lr=1e-4,
    output_dir='/runs/rfdetr_medium',
)
PY

python3 -m venv /opt/inference && source /opt/inference/bin/activate
pip install inference[gpu] supervision pillow

python3 - <<'PY'
import supervision as sv
from PIL import Image
from inference import get_model

model = get_model('rfdetr-medium')
image = Image.open('frame.jpg')
predictions = model.infer(image, confidence=0.5)[0]
detections = sv.Detections.from_inference(predictions)
annotated = sv.BoxAnnotator().annotate(image, detections)
annotated = sv.LabelAnnotator().annotate(annotated, detections)
PY

# Или поднять HTTP-сервер:
inference server start --port 9001

pip install rfdetr onnxruntime-gpu

python3 - <<'PY'
from rfdetr import RFDETRMedium

model = RFDETRMedium()
model.export(format='onnx', output_dir='/exports/rfdetr_medium.onnx')
PY

# Сборка TensorRT-движка (CUDA 12.x):
trtexec --onnx=/exports/rfdetr_medium.onnx \
  --saveEngine=/exports/rfdetr_medium.engine \
  --fp16 --workspace=4096