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# AUTOGENERATED! DO NOT EDIT! File to edit: 02_spider_deploy.ipynb. | |
# %% auto 0 | |
__all__ = ['repo_id', 'learn', 'path', 'categories', 'image', 'output', 'examples', 'intf', 'second', 'classify_image'] | |
# %% 02_spider_deploy.ipynb 1 | |
from fastai.vision.all import * | |
from huggingface_hub import from_pretrained_fastai | |
import gradio as gr | |
# %% 02_spider_deploy.ipynb 2 | |
repo_id = "xt0r3/spider-classifier" | |
learn = from_pretrained_fastai(repo_id) | |
# %% 02_spider_deploy.ipynb 3 | |
path = Path("data/spiders") | |
categories = learn.dls.vocab | |
# %% 02_spider_deploy.ipynb 4 | |
def second(x): | |
a, b = x | |
return b | |
def classify_image(img): | |
image = Image.fromarray(img) | |
image.thumbnail(size=(224,224)) | |
img = np.asarray(img) | |
ans,idx,preds = learn.predict(img) | |
results = zip(categories, map(float, preds)) | |
results = sorted(results, key=second, reverse=True) | |
return dict(results[:10]) | |
# %% 02_spider_deploy.ipynb 6 | |
image = gr.inputs.Image() | |
output = gr.outputs.Label() | |
examples = ["data/spider1.jpg", "data/spider2.jpg"] | |
intf = gr.Interface(fn=classify_image, inputs=image, outputs=output, examples=examples) | |
intf.launch(inline=False) | |