| import gradio as gr | |
| from fastai.vision.all import * | |
| def greet(name): | |
| return "Hello " + name + "!!" | |
| learn = load_learner("model.pkl"); | |
| def is_cat(x): return x[0].isupper() | |
| categories = {"No_Cat","Cat"} | |
| def classify_image(img): | |
| pred,idx,probs = learn.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| image = gr.inputs.Image(shape=(192,192)) | |
| label = gr.outputs.Label() | |
| examples = ["WX20240713-091831@2x.png","WX20240713-091821@2x.png","WX20240713-091430@2x.png","WX20240713-090252@2x.png"] | |
| intf = gr.Interface(fn=classify_image,inputs = image,outputs = label,examples = examples) | |
| intf.launch(inline=False) | |
| demo = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| demo.launch() |