add app.py etc.

app.py

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+# The A.M.A.Z.I.N.G  B.E.A.R.D D.E.T.E.C.T.I.V.E  ! ! !
+
+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 = "The A.M.A.Z.I.N.G    B.E.A.R.D    D.E.T.E.C.T.I.V.E  ! ! !"
+description = "A Beard Detector created using a pretrained ResNet50 model fine tuned using fast.ai"
+article="<p style='text-align: center'><a href='https://www.kaggle.com/code/mikemoloch/the-amazing-beard-detector' target='_blank'>Kaggle Notebook</a></p>"
+examples = [ 'beard_00000111.jpg', 'beard_00000119.jpg', 'beard_00000129.jpg', 'beard_00000162.jpg', 'clean_00000115.jpg', 'clean_00000138.jpeg', 'clean_00000197.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,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()

requirements.txt

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+fastai
+scikit-image