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. You can test the model here: here

Evaluation Metrics

The model's performance was evaluated using standard classification metrics:

Accuracy: 85%
Precision: 88%
Recall: 80%

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```

dolaposalim/filadentification

Fila Yoruba Detector

Model Description