flower-classifier

This is an image classification model trained using fastai. It classifies images into the following categories: ['golden_dewdrop', 'peepal_tree']

Model Details

• Architecture: <function resnet34 at 0x7a5c724aa2a0>
• Image Size: 224
• Training Data: Custom dataset (flower images)

How to use this model

from fastai.vision.all import *
from huggingface_hub import hf_hub_download

# Download the model file
model_path = hf_hub_download(repo_id='lucypatrice/flower-classifier', filename='model.pkl')

# Load the fastai learner
learn = load_learner(model_path)

# Example prediction
img = PILImage.create('your_image.jpg') # Replace with your image path
pred, pred_idx, probs = learn.predict(img)

print(f"Prediction: {pred} (confidence {probs[pred_idx]:.2%})")

Training Metrics

(You can add more detailed metrics, confusion matrices, etc. here after evaluating.)