| --- |
| license: other |
| library_name: pytorch |
| pipeline_tag: image-segmentation |
| tags: |
| - remote-sensing |
| - change-detection |
| - binary-change-detection |
| - semantic-segmentation |
| - mamba |
| - mambarefine-cd |
| - mercon |
| metrics: |
| - f1 |
| - iou |
| - precision |
| - recall |
| --- |
| |
| # MambaRefine-CD |
|
|
| MambaRefine-CD is a remote sensing binary change detection model. It takes a bi-temporal image pair as input and outputs a binary change mask. The paper has been accepted at MERCon. This Hugging Face repository contains trained weights, configs, and usage instructions. |
|
|
| ## Model Details |
|
|
| - Model name: MambaRefine-CD |
| - Task: binary remote sensing change detection |
| - Input: pre-change and post-change image pair |
| - Output: binary change mask |
| - Framework: PyTorch |
| - Paper status: Accepted at MERCon |
| - GitHub repository: `https://github.com/Dineth14/MambaRefine-CD` |
|
|
| ## Released Checkpoints |
|
|
| | Dataset | Checkpoint | Config | Train Split | Validation Split | Test Split | Main Metric | Notes | |
| | ------- | ---------- | ------ | ----------- | ---------------- | ---------- | ----------- | ----- | |
| | WHU-CD | `checkpoints/mambarefine_cd_whu_cd_best.pth` | `configs/whu_cd_run_config.yaml` | 6096 samples | 762 samples | 762 samples | Test F1 95.5324 | Best validation checkpoint, iteration 45000, threshold 0.55, EMA found. | |
| | DSIFN-CD | `checkpoints/mambarefine_cd_dsifn_cd_best.pth` | `configs/dsifn_cd_run_config.yaml` | 3153 samples | 3152 samples | Not specified in selected run manifest | Test F1 96.3963 | Best validation checkpoint, iteration 50000, threshold 0.60, EMA found. | |
|
|
| ## Datasets and Splits |
|
|
| ### WHU-CD |
|
|
| - Official/common dataset name: WHU-CD |
| - Dataset name used in config: `WHU-CD` |
| - Number of image pairs: train 6096, validation 762, test 762 |
| - Image size: 256 |
| - Mask format: binary change mask |
| - Binary threshold: `127` in `configs/active.yaml` |
| - Ignore index: Not specified in selected WHU-CD run config |
| - Normalization: ImageNet mean `[0.485, 0.456, 0.406]` and std `[0.229, 0.224, 0.225]` in `src/datasets/transforms.py` |
|
|
| ### DSIFN-CD |
|
|
| - Official/common dataset name: DSIFN-CD |
| - Dataset name used in config: `DSIFN-CD` |
| - Number of image pairs: train 3153, validation 3152, test not specified in selected run manifest |
| - Image size: 256 |
| - Mask format: binary change mask |
| - Binary threshold: `127` in `configs/active.yaml` |
| - Ignore index: Not specified in selected DSIFN-CD binary release run config |
| - Normalization: ImageNet mean `[0.485, 0.456, 0.406]` and std `[0.229, 0.224, 0.225]` in `src/datasets/transforms.py` |
|
|
| ## Results |
|
|
| | Dataset | Precision | Recall | F1 | IoU | OA | Notes | |
| | ------- | --------: | -----: | -: | --: | -: | ----- | |
| | WHU-CD | 96.0072 | 95.0623 | 95.5324 | 91.4469 | 99.5715 | From selected WHU-CD test metrics. | |
| | DSIFN-CD | 96.2591 | 96.5340 | 96.3963 | 93.0434 | 97.4721 | From selected DSIFN-CD test metrics. | |
|
|
| ## Installation |
|
|
| ```bash |
| git clone https://github.com/Dineth14/MambaRefine-CD |
| cd MambaRefine-CD |
| pip install -r requirements.txt |
| pip install huggingface_hub |
| ``` |
|
|
| ## Download Weights |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| |
| ckpt_path = hf_hub_download( |
| repo_id="<HF_USERNAME_OR_ORG>/MambaRefine0cd", |
| filename="checkpoints/mambarefine_cd_whu_cd_best.pth", |
| ) |
| print(ckpt_path) |
| ``` |
|
|
| ## Loading the Model |
|
|
| ```python |
| from src.engine.checkpoint import load_checkpoint |
| from src.models.build import build_model |
| from src.utils.config import load_config |
| from src.utils.device import get_device |
| |
| cfg = load_config("configs/active.yaml") |
| device = get_device(cfg) |
| model = build_model(cfg).to(device) |
| checkpoint = load_checkpoint("checkpoints/mambarefine_cd_whu_cd_best.pth", model) |
| model.eval() |
| ``` |
|
|
| ## Evaluation |
|
|
| The repository scripts read `configs/active.yaml`. |
|
|
| ```bash |
| python val.py |
| python test.py |
| python infer.py |
| ``` |
|
|
| Before running evaluation with downloaded weights, set `checkpoint.path` in `configs/active.yaml` to the downloaded checkpoint path and set the dataset root to your local dataset. |
|
|
| ## Limitations |
|
|
| - The weights are intended for remote sensing binary change detection. |
| - Results depend on dataset domain, resolution, preprocessing, and split consistency. |
| - Users should evaluate with the same preprocessing and splits used during training. |
| - DSIFN-CD test split count for the selected release run was not specified in the selected run manifest. |
|
|
| ## Citation |
|
|
| Official citation will be added after the MERCon proceedings information is available. |
|
|
