Classificador de Tubarão

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('export.pkl')
+
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Shark Classifier"
+description = "Classificador de algumas espécies de tubarão treinada pela Rede Neural resnet 18 através da biblioteca do fastai"
+examples = ['gshark.jpg','tshark.jpg','hshark.jpg','wshark.jpg']
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict,
+             inputs=gr.inputs.Image(shape=(512, 512)),
+             outputs=gr.outputs.Label(num_top_classes=3),
+             title=title,
+             description=description,
+             examples=examples,
+             interpretation=interpretation,
+             enable_queue=enable_queue
+).launch()

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4523fadb10a769338d79d9ef55fee161ed0518670cd66becaa91755ff848e5f5
+size 46962526

requirements.txt

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+fastai
+scikit-image