Create README.md

README.md

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+# 🔥 Forest Fire Detection Model
+
+This model detects forest fires in images using a deep learning CNN trained on the [Wildfire Dataset](https://www.kaggle.com/datasets/elmadafri/the-wildfire-dataset).
+
+## Model Details
+
+- **Architecture:** Sequential CNN with Conv2D, MaxPooling2D, Dense, Dropout layers.
+- **Input Size:** 150x150 RGB images
+- **Output:** Binary classification (`fire` or `nofire`)
+- **Framework:** TensorFlow / Keras
+
+## Training Data
+
+- **Dataset:** [The Wildfire Dataset](https://www.kaggle.com/datasets/elmadafri/the-wildfire-dataset)
+- **Classes:** `fire`, `nofire`
+- **Preprocessing:** Images resized to 150x150, normalized to [0, 1]
+
+## Training Script
+
+The model was trained using the following script (see attached notebook for full details):
+
+```python
+model = Sequential([
+    Input(shape=(150, 150, 3)),
+    Conv2D(32, (3,3), activation='relu'),
+    MaxPooling2D(pool_size=(2,2)),
+    Conv2D(64, (3, 3), activation='relu'),
+    MaxPooling2D(pool_size=(2, 2)),
+    Conv2D(128, (3, 3), activation='relu'),
+    MaxPooling2D(pool_size=(2, 2)),
+    Flatten(),
+    Dense(512, activation='relu'),
+    Dropout(0.5),
+    Dense(1, activation='sigmoid')
+])
+model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
+model.fit(...)
+```
+
+## Intended Use
+- **Use Case:** Automated detection of forest fires in aerial or ground images.
+- **Limitations:** Not suitable for video, may not generalize to all forest types or lighting conditions.
+
+## How to Use
+```python
+import requests
+
+API_URL = "https://api-inference.huggingface.co/models/YOUR_USERNAME/YOUR_MODEL_NAME"
+headers = {"Authorization": "Bearer YOUR_HF_API_TOKEN"}
+
+with open("your_image.jpg", "rb") as f:
+    data = f.read()
+response = requests.post(API_URL, headers=headers, files={"file": data})
+print(response.json())
+```
+
+## Evaluation
+- **Test Accuracy:** 70%
+- **Metrics:** Not suitable for video, may not generalize to all forest types or lighting conditions.
+
+## Citation
+If you use this model, please cite the dataset and this repository.