fix examples attempt 3

app.py

@@ -8,7 +8,7 @@ plt = platform.system()
 if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
 
 learn = load_learner('model.pkl')
-examples = [os.path.join(os.path.dirname(__file__), str(x)) for x in get_image_files('./images')]
+examples = [PILImage.create(str(x)) for x in get_image_files('images')]
 
 labels = learn.dls.vocab
 def predict(img):
@@ -19,11 +19,10 @@ def predict(img):
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
 title = "Northern EU Mushroom Classifier"
-description = "<h4 style='text-align: center'>A North EU mushroom image classifier trained on a kaggle dataset with fastai. The dataset consist of 9 different folders that contains from 300 to 1500 selected images of mushrooms genuses.</h4>"
-article="<h4 style='text-align: center'><a href='https://www.kaggle.com/datasets/maysee/mushrooms-classification-common-genuss-images' target='_blank'>Data Source</a></h4>"
+description = "<p style='text-align: center, font-size:14px'>A North EU mushroom image classifier trained on a kaggle dataset with fastai. The dataset consist of 9 different folders that contains from 300 to 1500 selected images of mushrooms genuses.</p>"
+article="<p style='text-align: center, font-size:14px'><a href='https://www.kaggle.com/datasets/maysee/mushrooms-classification-common-genuss-images' target='_blank'>Data Source</a></h4>"
 interpretation='default'
 enable_queue=True
 inputs = gr.Image(shape=(224, 224))
-examples = gr.Examples(examples=examples, inputs=inputs)
 
 gr.Interface(fn=predict, inputs=inputs, outputs=gr.Label(num_top_classes=3), title=title, description=description, article=article, interpretation=interpretation, examples=examples).launch(share=True, enable_queue=enable_queue)