RF-DETR
हमारे Serverless Hosted API के माध्यम से Roboflow के RF-DETR model का उपयोग करें
RF-DETR Object Detection
कोड नमूना
1
export ROBOFLOW_API_KEY="your-key-here"2
pip install inference-sdk supervision3
import os
import cv2
import numpy as np
import requests
import supervision as sv
from inference_sdk import InferenceHTTPClient
image_url = "https://media.roboflow.com/quickstart/traffic.jpg"
content = requests.get(image_url).content
image = cv2.imdecode(np.frombuffer(content, np.uint8), cv2.IMREAD_COLOR)
client = InferenceHTTPClient(
api_url="https://serverless.roboflow.com",
api_key=os.environ["ROBOFLOW_API_KEY"],
)
result = client.infer(image, model_id="rfdetr-small")
detections = sv.Detections.from_inference(result)
annotated = sv.BoxAnnotator().annotate(image.copy(), detections)
annotated = sv.LabelAnnotator().annotate(annotated, detections)
cv2.imwrite("traffic-annotated.png", annotated)
Pretrained models और benchmarks
उपनाम
इनपुट आकार
mAP50-95
ONNX latency (ms)*
TensorRT FP16 (ms)*
RF-DETR Instance Segmentation
कोड नमूना

Pretrained models और benchmarks
उपनाम
इनपुट आकार
Mask mAP50-95
ONNX latency (ms)*
TensorRT FP16 (ms)*
अंतिम अपडेट
क्या यह उपयोगी था?