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README.md

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+---
+license: mit
+library_name: pytorch
+pipeline_tag: image-classification
+tags:
+  - thermal-imaging
+  - anomaly-detection
+  - resnet
+  - lstm
+  - pytorch
+---
+
+# Thermal Pattern Analysis — CNN + Bi-LSTM
+
+Anomaly detection model for infrared thermal images of power transformers.
+
+## Architecture
+
+3-stage pipeline:
+1. **Feature Extraction** — Modified ResNet-18 (grayscale input, 256-dim embeddings)
+2. **Temporal Analysis** — Bidirectional LSTM + Self-Attention (128 hidden, 2 layers)
+3. **Anomaly Detection** — Cosine similarity scorer (threshold: 0.7)
+
+## Usage
+
+```python
+import torch
+from huggingface_hub import hf_hub_download
+
+ckpt_path = hf_hub_download("Zorrojurro/thermal-pattern-analysis", "best_model.pt")
+ckpt = torch.load(ckpt_path, map_location="cpu", weights_only=False)
+# model.load_state_dict(ckpt["model_state_dict"])
+# classifier.load_state_dict(ckpt["classifier_state_dict"])
+```
+
+## Demo
+
+Live demo: [Zorrojurro/thermal-backend](https://huggingface.co/spaces/Zorrojurro/thermal-backend)
+
+## Training
+
+- Dataset: SciDB Infrared Thermal Image Dataset (895 IR images)
+- Optimizer: AdamW (lr: 3e-4)
+- Epochs: 100 with early stopping (patience: 25)
+- Image size: 224×224 grayscale