| from fastai.vision.all import * |
| import gradio as gr |
| import glob |
|
|
| class Hook(): |
| def hook_func(self, m, i, o): self.stored = o.detach().clone() |
|
|
| learn = load_learner("resnet152_fit_one_cycle_freeze_91acc.pkl", cpu=True) |
|
|
| categories = ('arbanasi', 'filibe', 'gjirokoster', 'iskodra', 'kula', 'kuzguncuk', 'larissa_ampelakia', 'mardin', 'ohrid', 'pristina', 'safranbolu', 'selanik', 'sozopol_suzebolu', 'tiran', 'varna') |
| def classify_img(img): |
| pred,idx,probs=learn.predict(img) |
| return dict(zip(categories, map(float, probs))) |
|
|
| image=gr.inputs.Image(shape=(128,128)) |
| label=gr.outputs.Label() |
| examples_=[] |
| for i in glob.glob("valid/**/*.jpg", recursive=True): |
| examples_.append(i) |
|
|
| examples=["filibe-1-1.jpg", |
| "ohrid-3-1.jpg", |
| "varna-1-1.jpg"] |
|
|
|
|
| demo = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples) |
|
|
| demo.launch(inline=False) |
