---
library_name: transformers
tags:
- remote sensing
- object detection
datasets: keremberke/satellite-building-segmentation
metrics:
- Average Precision (AP)
- Average Recall (AR)
license: mit
base_model: PekingU/rtdetr_r101vd_coco_o365
pipeline_tag: object-detection
widget:
  - src: imgs/example_groundtruth.png
    output:
      url: imgs/example_detections.png
model-index:
- name: rt-detr-finetuned-for-satellite-image-roofs-detection
  results:
    - task:
        type: object-detection
      dataset:
        type: image-segmentation
        name: keremberke/satellite-building-segmentation
      metrics:
      - name: AP @ IoU=0.50:0.95 | area=all | maxDets=100
        type: AP (IoU=0.50:0.95)
        value: 0.430
      - name: AP @ IoU=0.50 | area=all | maxDets=100
        type: AP (IoU=0.50)
        value: 0.636
      - name: AP @ IoU=0.75 | area=all | maxDets=100
        type: AP (IoU=0.75)
        value: 0.462
      - name: AP @ IoU=0.50:0.95 | area=small | maxDets=100
        type: AP (IoU=0.50:0.95) small objects
        value: 0.241
      - name: AP @ IoU=0.50:0.95 | area=medium | maxDets=100
        type: AP (IoU=0.50:0.95) medium objects
        value: 0.513
      - name: AP @ IoU=0.50:0.95 | area=large | maxDets=100
        type: AP (IoU=0.50:0.95) large objects
        value: 0.624
      - name: AR @ IoU=0.50:0.95 | area=all | maxDets=1
        type: AR (IoU=0.50:0.95) maxDets=1
        value: 0.055
      - name: AR @ IoU=0.50:0.95 | area=all | maxDets=10
        type: AR (IoU=0.50:0.95) maxDets=10
        value: 0.327
      - name: AR @ IoU=0.50:0.95 | area=all | maxDets=100
        type: AR (IoU=0.50:0.95) maxDets=100
        value: 0.507
      - name: AR @ IoU=0.50:0.95 | area=small | maxDets=100
        type: AR (IoU=0.50:0.95) small objects
        value: 0.312
      - name: AR @ IoU=0.50:0.95 | area=medium | maxDets=100
        type: AR (IoU=0.50:0.95) medium objects
        value: 0.595
      - name: AR @ IoU=0.50:0.95 | area=large | maxDets=100
        type: AR (IoU=0.50:0.95) large objects
        value: 0.712
---

# Model Card

Roof Detection for Remote Sensing task.
<!-- Provide a quick summary of what the model is/does. -->



## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

- **Developed by:** Yifeng Liu
- **Model type:** Object Detection for Remote Sensing task.
- **License:** MIT

### Model Sources 

<!-- Provide the basic links for the model. -->

- **Repository:** [Jupyter Notebook](https://github.com/ownEyes/satellite-image-roofs-auto-annotation-sourcecode/blob/dev/notebooks/finetune_rtdetr.ipynb)
- **Demo [optional]:** [Pending]




## Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.
```python
from transformers import AutoModelForObjectDetection, AutoImageProcessor

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")
```