Upload app.py

app.py

@@ -6,19 +6,13 @@ pathlib.PosixPath = pathlib.WindowsPath
 from fastai.vision.all import *
 import gradio as gr
 import pickle
+import timm
 
-with open('./model.pkl', 'rb') as f:
-    model = pickle.load(f)
+# Cell
+learn = load_learner('model.pkl')
 
-if [ ! -f /etc/apt/sources.list ]; then
-    echo "Creating /etc/apt/sources.list"
-    echo "deb http://deb.debian.org/debian buster main" > /etc/apt/sources.list
-    echo "deb-src http://deb.debian.org/debian buster main" >> /etc/apt/sources.list
-    echo "deb http://security.debian.org/debian-security buster/updates main" >> /etc/apt/sources.list
-    echo "deb-src http://security.debian.org/debian-security buster/updates main" >> /etc/apt/sources.list
-    echo "deb http://deb.debian.org/debian buster-updates main" >> /etc/apt/sources.list
-    echo "deb-src http://deb.debian.org/debian buster-updates main" >> /etc/apt/sources.list
-fi
+# Cell
+#categories = learn.dls.vocab
 
 def is_real(x): return x[0].isupper()
 
@@ -35,8 +29,7 @@ def classify_image(img):
 #*** We have to cast to float above because KAGGLE does not return number on the answer it returns tensors, and Gradio does not deal with numpy so we have to cast to float
 
 #|export
-#import gradio as gr
-import gradio as gr
+
 image = gr.inputs.Image(shape=(192,192))
 label = gr.outputs.Label()
 examples = ['virtual.jpg','real.jpg','dunno.jpg']