new examples

app.py

@@ -18,11 +18,17 @@ def predict(im, threshold=0.50):
     return output_image
 
 title = "YOLOv5 - Auction sale catalogues layout analysis"
+
 description = "<p style='text-align: center'>YOLOv5 Gradio demo for auction sales catalogues layout analysis. Detecting titles and catalogues entries.</p>"
+
 article = "<p style='text-align: center'>YOLOv5 source code : <a href='https://github.com/ultralytics/yolov5'>Source code</a> | <a href='https://pytorch.org/hub/ultralytics_yolov5'>PyTorch Hub</a></p>"
+
 examples = [['./img_examples/12148-bpt6k1240127r.pdf_page_20.png', 0.50],
- ['./img_examples/12148-bpt6k1240127r.pdf_page_21.png', 0.50],
-  ['./img_examples/12148-bpt6k1240127r.pdf_page_27.png', 0.50]]
+            ['./img_examples/12148-bpt6k1240127r.pdf_page_21.png', 0.50],
+            ['./img_examples/12148-bpt6k1240127r.pdf_page_27.png', 0.50],
+            ['./img_examples/12148-bpt6k1240127r.pdf_page_37.png', 0.50],
+            ['./img_examples/12148-bpt6k1240127r.pdf_page_83.png', 0.50],
+            ['./img_examples/12148-bpt6k1240127r_BpE9Wd0.pdf_page_74.png', 0.50]]
 
 demo=gr.Interface(fn=predict,
             inputs=[gr.Image(type="pil", label="document image"), gr.Slider(maximum=1, step=0.01, value=0.50)],