initial upload

app.py

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+import gradio as gr
+from gradio.components import Image, Textbook
+from fastai.vision.all import *
+
+learn = load_learner('export_ver1.pkl')
+
+def get_headcount(filepath):
+  filepath = str(filepath)
+  filename = filepath.split('/')[-1]
+
+  return df[df['Name'] == filename]['HeadCount'].values[0]
+
+def predict(img):
+  img = PILImage.create(img)
+  op = learn.predict(img)
+  return int(op[0][0])
+
+
+
+
+title = "Face count"
+description = "This model that is trained to counts the number of faces  in the uploaded picture."
+
+eg = ['cam_mit.jpg', 'dunphys.jpg', 'group.jpg']
+
+gr.Interface(
+    fn=predict,
+    inputs=Image(shape=(512, 512)),
+    outputs=Textbox(type="number", label="Number of faces"),
+    title=title,
+    description=description,
+    examples=eg,
+).launch(share=False)
+

export_ver1.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:58cf5953ff9d8d1a561bed808bf360774035b9c14461fd38170ae4847193463e
+size 87547757

requirements.txt

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+fastai