WIP

app.py

@@ -1,14 +1,20 @@
 import gradio as gr
-import pickle
+from fastai.vision.all import *
+import os
+
+# list all file names in the samples directory
+examples = []
+for file in os.listdir('samples'):
+    examples.append(['samples/' + file])
+
+categories = ['Jazzmaster', 'Stratocaster', 'Telecaster']
+
 
-categories = ['Telecaster', 'Stratocaster', 'Jazzmaster']
-examples = ['stratocaster.jpt', 'telecaster.jpg', 'jazzmaster.jpg']
 image = gr.inputs.Image(shape=(192, 192))
 label = gr.outputs.Label()
 
 # Load the trained model from the model.pkl file
-with open("model.pkl", "rb") as f:
-    model = pickle.load(f)
+model = load_learner('model.pkl')
 
 
 def predict(image):

model.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f516a4010723ec3b58a91e97fa317ddb97dd81a8b34becce9956714efa219199
-size 102886051
+oid sha256:cea884c093ed7feadcfa6b49f383795ccec5f59ea4df33dad4deb40a9f26207b
+size 102886559