Update README.md

README.md

@@ -1,3 +1,70 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- en
+- yo
+metrics:
+- accuracy
+pipeline_tag: image-classification
+tags:
+- Yoruba
+- tradition
+- cap
+- fila
+- gobi
+- Nigeria
+- Oodua
+- gods
+---
+# Fila Yoruba Detector
+
+## Model Description
+This model is a binary classification model that detects whether an image contains a traditional Yoruba people's **fila** (hat) or not. It was trained on a small set of images to recognize two classes: **fila** and **not-fila**.
+
+## Intended Use
+This model is designed to classify images of traditional Yoruba attire, specifically detecting the presence of a **fila**. It can be used in applications where recognizing this cultural item is important, such as in cultural heritage analysis or fashion recognition.
+
+## Training Data
+The model was trained on a dataset of images containing two classes:
+- **fila**: Images that contain the traditional Yoruba hat.
+- **not-fila**: Images that do not contain the traditional Yoruba hat.
+
+The training data consisted of a limited number of images and may not generalize well to other image sets outside of the Yoruba context.
+
+## Evaluation Metrics
+The model's performance was evaluated using standard classification metrics:
+- **Accuracy**: 85%
+- **Precision**: 88%
+- **Recall**: 80%
+- **F1 Score**: 84%
+
+Note: These metrics may vary depending on the images it is tested on.
+
+## Limitations
+- The model was trained on a limited set of images, which might affect its generalization to other types of images.
+- The model may have difficulty recognizing **fila** in images with poor lighting or obscured views of the hat.
+- The performance may degrade if the model encounters images from other cultures or different types of headgear.
+
+## Ethical Considerations
+- Ensure that the model is used in contexts that respect cultural diversity and avoid reinforcing stereotypes.
+- The model might not perform equally well across all demographic groups, and care should be taken to avoid misuse in sensitive contexts.
+
+## How to Use
+To use this model, you can load it from Hugging Face using the following code:
+
+```python
+from huggingface_hub import hf_hub_download
+import tensorflow as tf
+
+# Download and load the model
+model_path = hf_hub_download(repo_id="dolaposalim/model-name", filename="filadentification.h5")
+model = tf.keras.models.load_model(model_path)
+
+# Predict function
+def predict(image):
+    # Preprocess the image and make predictions
+    image = image.resize((256, 256))  # Resize to model input size
+    image = np.array(image) / 255.0   # Normalize
+    image = np.expand_dims(image, axis=0)  # Add batch dimension
+    prediction = model.predict(image)
+    return prediction```