| import gradio as gr | |
| from fastai.vision.all import * | |
| learn = load_learner('export.pkl') | |
| labels = learn.dls.vocab | |
| def predict(img): | |
| img = PILImage.create(img) | |
| pred, pred_idx, probs = learn.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| title = "Breast cancer detection with Deep Transfer Learning(ResNet18)." | |
| description = "Upload a breast X-ray image to detect potential issues." | |
| article = "Web app built and managed by Addai Fosberg" | |
| examples = ['img1.jpeg', 'img2.jpeg'] | |
| iface = gr.Interface( | |
| fn=predict, | |
| inputs=gr.Image(), | |
| outputs=gr.Label(num_top_classes=3), | |
| title=title, | |
| description=description, | |
| article=article, | |
| examples=examples, | |
| enable_queue=True | |
| ) | |
| iface.launch() |