more sample images for testing

app.py

@@ -45,7 +45,10 @@ import gradio as gr
 # model created from: https://www.kaggle.com/code/zachwormgoor/stock-photo-recognizer
 learn = load_learner('model.pkl')
 
-categories = ('stock', 'amateur')
+categories = ('amateur', 'stock')
+
+#may have categories swapped?
+#add probs to UI somewhere
 
 def classify_image(img):
     pred,idx,probs = learn.predict(img)
@@ -54,7 +57,7 @@ def classify_image(img):
     
 image = gr.inputs.Image(shape=(192, 192))
 label = gr.outputs.Label()
-examples = ['stock.jpg', 'amateur.jpg', 'unsure.jpg']
+examples = ['stock.jpg', 'stock-easy.jpg', 'stock-easy2.jpg', 'amateur.jpg', 'amateur-easy.jpg', 'amateur-easy2.jpg', 'unsure.jpg']
 # stock: https://image.shutterstock.com/image-photo/industrial-interior-storage-tank-rusty-260nw-132762554.jpg
 # amateur: https://cimg3.ibsrv.net/cimg/www.honda-tech.com/1024x768_85/479/AAApril-2-Control-Arms-01-58479.jpg
 # unsure: https://en.wikipedia.org/wiki/Joshua_Bean