add description

.gitattributes

@@ -30,3 +30,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
+*.PNG filter=lfs diff=lfs merge=lfs -text

app.py

@@ -169,7 +169,9 @@ def detect_logo(img, model, confidence):
 
 examples1 = [["exemple1.jpg", "Yologo", 0.60], ["exemple2.jpg", "Yologo", 0.60],
              ["exemple3.jpg", "Yologo", 0.60 ], ["exemple4.jpg", "Yologo", 0.60],
-             ["exemple5.jpg", "Yologo", 0.60], ["exemple6.jpg", "Yologo", 0.60]]
+             ["exemple5.PNG", "Yologo", 0.60], ["exemple6.jpg", "Yologo", 0.60],
+             ["exemple7.jpg", "Yologo", 0.60], ["exemple8.jpg", "Yologo", 0.60],
+             ["exemple9.jpg", "Yologo", 0.60], ["exemple10.jpg", "Yologo", 0.60]]
 
 Top_Title = "<center>Yolov7 🚀 Custom Trained by ISAI Team (Capgemini) </center> Logo detection model"
 Custom_description="Yologo can detect 44 brands : A.P.C, Abercrombie, Acne Studio, Adidas, Aigle, Airness, Armarni, Balenciaga, Bulgari, Cacharel, Calvin Klein, Carhatt, Champion, Columbia, Converse, Gap, Chanel, Lacoste, Levis, Louis vuitton, Moncler, Mossimo, New Balance, Obey, Pepe jeans, Ralph Lauren, Prada, Rolex, Seiko, Stussy, The North Face, Timberland, Tom Ford, Tommy Hilfiger, Uniqlo, Valentino, Versace, Zara, Asics, Le coq, Oakley, Nike, Puma, Reebok "