| import gradio as gr | |
| from huggingface_hub import hf_hub_download | |
| from fastai.learner import load_learner | |
| from fastai.vision.all import * | |
| learn = load_learner(hf_hub_download("lpattori/Vinchucas","model.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 = "Kissing Bug Recognizer" | |
| description = "Kissing Bug Recognizer trained on the CEPAVE dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces." | |
| article = "" | |
| examples = [img for img in Path("examples").rglob("*")] | |
| inputs = gr.Image(height=512, width=512) | |
| outputs = gr.Label(num_top_classes=3) | |
| demo = gr.Interface(fn=predict,inputs=inputs, | |
| outputs=outputs,title=title, | |
| description=description,article=article,examples=examples) | |
| demo.launch() |