# model_card_template.yaml # ===================================================== # 🌊 Water Surface Segmentation on Beach Images # ===================================================== # Hugging Face model metadata file # ===================================================== language: - en license: gpl-3.0 library_name: pytorch tags: - segmentation - computer-vision - yolo - beach - water - open-source task_categories: - image-segmentation model-index: - name: Water Surface Segmentation (NWSD) results: - task: type: image-segmentation name: Image Segmentation metrics: - type: mAP50 name: Mean Average Precision @ 0.5 value: 0.85 - type: inference_speed name: Inference Speed (CPU) value: 50 unit: "ms/image" model_details: description: > A YOLOv11n-based segmentation model fine-tuned for detecting and segmenting water surfaces in coastal or beach images. Trained on a custom-labeled dataset containing a single class: "water". developed_by: Lucas Iglesia repo: https://huggingface.co/Lucas-Iglesia/NWSD license: GPL-3.0 framework: PyTorch model_size: 6.07 MB input_size: "640x640" num_classes: 1 class_labels: ["water"] release_date: "2025-11-07" inference: parameters: device: "cpu or cuda" conf_threshold: 0.5 example_inputs: - beachTest.jpg example_outputs: - binary_mask.png - overlay.png usage_snippet: | from huggingface_hub import hf_hub_download import torch model_path = hf_hub_download(repo_id="Ehlum-Lucas/NWSD", filename="nwsd-v2.pt") model = torch.load(model_path, map_location="cpu") model.eval() recommended_use: - Coastal monitoring - Beach safety and drowning prevention - Environmental water coverage analysis limitations: - Optimized for daylight beach scenes - May underperform in low-visibility or night images citation: - type: misc title: "Water Surface Segmentation on Beach Images" author: "Lucas Iglesia" year: 2025 url: "https://huggingface.co/Ehlum-Lucas/NWSD"