Interactive Demo: Satellite Roof Annotation - Hugging Face Space
MCP Tool: Connect to Gradio MCP server to use this model from MCP-compatible clients such as Claude Code, Cursor, and Codex.

Limitations

Model type: Object Detection for Remote Sensing task.
License: MIT

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.

How to Get Started with the Model

Use the code below to get started with the model.

python

from transformers import AutoModelForObjectDetection, AutoImageProcessor
import torch
import cv2

image_path=YOUR_IMAGE_PATH
image = cv2.imread(image_path)

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

model = AutoModelForObjectDetection.from_pretrained("Yifeng-Liu/rt-detr-finetuned-for-satellite-image-roofs-detection")
image_processor = AutoImageProcessor.from_pretrained("Yifeng-Liu/rt-detr-finetuned-for-satellite-image-roofs-detection")


CONFIDENCE_TRESHOLD = 0.5

with torch.no_grad():
    model.to(device)

    # load image and predict
    inputs = image_processor(images=image, return_tensors='pt').to(device)
    outputs = model(**inputs)

    # post-process
    target_sizes = torch.tensor([image.shape[:2]]).to(device)
    results = image_processor.post_process_object_detection(
        outputs=outputs,
        threshold=CONFIDENCE_TRESHOLD,
        target_sizes=target_sizes
    )[0]