Update README.md

README.md

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----
-license: mit
----
+---
+license: apache-2.0
+tags:
+  - emotion-detection
+  - affective-computing
+  - classification
+  - cnn
+datasets:
+  - custom
+model-index:
+  - name: AffectSense
+    results: []
+---
+
+# 🧠 AffectSense
+
+**AffectSense** is a Convolutional Neural Network (CNN)-based model designed for emotion and affect recognition from visual or image-based data. The model leverages a pre-trained **ResNet-50** backbone and has been fine-tuned for affective computing tasks such as emotion classification and mood detection.
+
+## 🚀 Usage
+
+You can load a model like this:
+
+```python
+import torch
+from torchvision import models
+
+# Load the model (example if using torch.load)
+model = torch.load("path_to_checkpoint.pth")
+model.eval()
+```
+
+> Or, if packaged in a model class:
+
+```python
+from affectsense import AffectSenseModel
+
+model = AffectSenseModel.from_pretrained("tawheed-tariq/AffectSense")
+```
+
+## 📊 Intended Uses & Limitations
+
+### Use Cases
+- Emotion recognition from facial images
+- Affective content tagging in videos
+- Visual mood estimation
+- Human-computer interaction systems
+
+### Limitations
+- May not generalize well across unseen demographics or lighting conditions
+- Not suitable for clinical diagnosis
+- Accuracy depends on the diversity of training data
+
+## 🏗️ Model Architecture
+
+- **Backbone**: ResNet-50 (pre-trained on ImageNet)
+- **Modified Head**: Custom classification head for emotion categories
+- **Input Size**: Typically 224×224 RGB images
+
+## 📁 Training Data
+
+The models were trained on custom-curated datasets with emotion-labeled visual data. Examples include facial emotion datasets or affective scene datasets.
+
+## 📜 License
+
+This model is licensed under the Apache 2.0 License.
+
+## ✍️ Citation
+
+If you use this model in your research, please cite:
+
+```
+@misc{affectsense2025,
+  title={AffectSense: CNN-based Emotion Recognition Model using ResNet-50},
+  author={Tariq, Tavaheed},
+  year={2025},
+  howpublished={\url{https://huggingface.co/tawheed-tariq/AffectSense}},
+}
+```
+
+---