| from fastai.vision.all import * | |
| import gradio as gr | |
| from PIL import Image | |
| def style(x): return x[0].isupper() | |
| learn = load_learner('model1.pkl') | |
| categories = ('Real','fake') | |
| def classify_image(img): | |
| pred, idx, probs = learn.predict(img) | |
| img = img.resize((192, 192)) | |
| # Your classification logic here | |
| return dict(zip(categories,map (float,probs))) | |
| # image = gr.inputs.Image(shape=(192, 192)) | |
| # label = gr.outputs.Label() | |
| # intf = gr. Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
| intf = gr.Interface( | |
| fn=classify_image, | |
| inputs=gr.Image(type="pil"), | |
| outputs=gr.Label() | |
| # examples=[''] | |
| ) | |
| intf.launch(inline=False) |