Update inference.py

inference.py

@@ -424,11 +424,11 @@ def non_max_suppression(
     width = prediction[..., 2]*pix2w
     wc = width < max_length
 
-    print(0.1, sum(sum(width*pix2w < 0.1)))
-    print(0.8, sum(sum(width*pix2w < 0.8)))
-    print(1.5, sum(sum(width*pix2w < 1.5)))
-    print(10,  sum(sum(width*pix2w < 10 )))
-    print(10,  sum(sum(width*pix2w < 10 )))
+    print(0.1, sum(sum(width < 0.1)))
+    print(0.8, sum(sum(width < 0.8)))
+    print(1.5, sum(sum(width < 1.5)))
+    print(10,  sum(sum(width < 10 )))
+    print(10,  sum(sum(width < 10 )))
     print(prediction[1,512,:])
     print("mean", torch.mean(width))