Segformer B5 Andhra Landuse

--- license: apache-2.0 language: - en tags: - segformer - semantic-segmentation - land-use-classification - change-detection - remote-sensing - satellite-imagery - andhra-pradesh - geospatial - urban-planning - property-identification pipeline_tag: image-segmentation --- # SegFormer-B5 Andhra Pradesh Land Use & Change Detection Model <div align="center"> [](https://huggingface.co/yantrikaran-innovations) []() []() []() </div> --- ## 📌 Model Overview This model is a **SegFormer-B5** architecture fine-tuned for **semantic land use segmentation** and **bi-temporal change detection** on satellite imagery of **5 districts in Andhra Pradesh, India**. It was developed by **Yantrikaran Innovations Pvt. Ltd.** as part of a smart property identification system commissioned for Andhra Pradesh government land analytics. The model can: 1. **Segment land use** from a single satellite tile into 5 classes. 2. **Detect changes** between two temporal satellite images (e.g., new construction, encroachment, deforestation). --- ## 🏷️ Label Classes | ID | Class | Description | |----|-------|-------------| | 0 | **Background** | Sky, shadows, uncategorized | | 1 | **Buildings** | Residential & commercial structures | | 2 | **Road** | Roads, highways, pathways | | 3 | **Water Body** | Rivers, lakes, ponds, irrigation canals | | 4 | **Open Plot** | Vacant land, agricultural/open land | --- ## 📊 Training Metrics ### Training Configuration | Parameter | Value | |-----------|-------| | Architecture | SegFormer-B5 | | Dataset | 20,000+ chips, Andhra Pradesh (5 Districts) | | Image Source | Sentinel-2 Satellite Imagery | | Chip Size | 512×512 px | | Total Epochs | 60 (Best at Ep 56) | | Early Stopping Patience | 10 epochs | ### Final Performance (Best Checkpoint - Epoch 56) | Metric | Value | |--------|-------| | **Training Loss** | 0.8196 | | **Validation Loss** | 0.8482 | | **Best mIoU** | **0.5474** | | Learning Rate (final) | 4.04e-06 | | Training Time | ~2698s / epoch | ### Per-C...

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