| import gradio as gr | |
| from fastai.vision.all import * | |
| def is_cat(x): return x[0].isupper() | |
| if platform.system().lower() == "windows": | |
| import pathlib | |
| posix_path = pathlib.PosixPath | |
| pathlib.PosixPath = pathlib.WindowsPath | |
| learner=load_learner("model.pkl") | |
| if platform.system().lower() == "windows": | |
| pathlib.PosixPath = posix_path | |
| categories=('Dog','Cat') | |
| def classify_image(img): | |
| pred,idx,prob=learner.predict(img) | |
| return dict(zip(categories,map(float,prob))) | |
| image=gr.inputs.Image(shape=(192,192)) | |
| label=gr.outputs.Label() | |
| examples=['dog.jpg','cat.jpg','unknown.jpg','cat_2.jpg'] | |
| 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() |