metadata
library_name: fastai
tags:
- image-classification
- fastai
- computer-vision
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.)