flower classifier initial commit

app.py

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+import gradio as gr
+from fastai.vision.all import *
+
+learn = load_learner('flowersclassifier.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 = "Flower Classifier"
+description = "A flower classifier trained on the images downloaded from the internet."
+examples = ['sunflower.jpg','marigold.jpg']
+interpretation='default'
+enable_queue=True
+
+intf = gr.Interface(fn=predict,inputs=gr.Image(type="pil"),outputs=gr.Label(),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue)
+intf.launch()

flowersclassifier.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ad91a31a33b19439553855abe982710a1fac36cca0f2a40f577fddd0baac1096
+size 46985022

requirements.txt

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+fastai