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  1. .gitattributes +4 -0
  2. coco.names +80 -0
  3. obj.names +7 -0
  4. yolov3.cfg +789 -0
  5. yolov3.weights +3 -0
  6. yolov4-csp.cfg +1279 -0
  7. yolov4-csp.weights +3 -0
  8. yolov4-tiny.cfg +294 -0
  9. yolov4-tiny.weights +3 -0
  10. yolov4.cfg +1158 -0
  11. yolov4.weights +3 -0
.gitattributes CHANGED
@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ yolov3.weights filter=lfs diff=lfs merge=lfs -text
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+ yolov4-csp.weights filter=lfs diff=lfs merge=lfs -text
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+ yolov4-tiny.weights filter=lfs diff=lfs merge=lfs -text
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+ yolov4.weights filter=lfs diff=lfs merge=lfs -text
coco.names ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ person
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+ bicycle
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+ car
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+ motorbike
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+ aeroplane
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+ bus
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+ train
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+ truck
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+ boat
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+ traffic light
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+ fire hydrant
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+ stop sign
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+ parking meter
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+ bench
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+ bird
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+ cat
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+ dog
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+ horse
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+ sheep
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+ cow
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+ elephant
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+ bear
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+ zebra
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+ giraffe
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+ backpack
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+ umbrella
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+ handbag
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+ tie
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+ suitcase
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+ frisbee
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+ skis
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+ snowboard
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+ sports ball
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+ kite
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+ baseball bat
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+ baseball glove
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+ skateboard
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+ surfboard
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+ tennis racket
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+ bottle
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+ wine glass
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+ cup
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+ fork
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+ knife
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+ spoon
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+ bowl
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+ banana
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+ apple
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+ sandwich
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+ orange
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+ broccoli
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+ carrot
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+ hot dog
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+ pizza
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+ donut
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+ cake
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+ chair
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+ sofa
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+ pottedplant
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+ bed
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+ diningtable
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+ toilet
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+ tvmonitor
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+ laptop
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+ mouse
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+ remote
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+ keyboard
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+ cell phone
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+ microwave
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+ oven
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+ toaster
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+ sink
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+ refrigerator
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+ book
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+ clock
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+ vase
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+ scissors
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+ teddy bear
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+ hair drier
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+ toothbrush
obj.names ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
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+ ball
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yolov3.cfg ADDED
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+ [net]
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+ height=416
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+ stride=1
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+ pad=1
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+ activation=leaky
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+
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+ # Downsample
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+
35
+ [convolutional]
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+ activation=leaky
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+
59
+ [shortcut]
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+ from=-3
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+
109
+ [shortcut]
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+ from=-3
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+
113
+ # Downsample
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+
115
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+ pad=1
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+ activation=leaky
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+
280
+ [shortcut]
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+ from=-3
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+ activation=linear
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+
284
+ # Downsample
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+
286
+ [convolutional]
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+ batch_normalize=1
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+ filters=512
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+ size=3
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+ ######################
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588
+ size=1
589
+ stride=1
590
+ pad=1
591
+ activation=mish
592
+
593
+ [convolutional]
594
+ batch_normalize=1
595
+ filters=256
596
+ size=3
597
+ stride=1
598
+ pad=1
599
+ activation=mish
600
+
601
+ [shortcut]
602
+ from=-3
603
+ activation=linear
604
+
605
+ [convolutional]
606
+ batch_normalize=1
607
+ filters=256
608
+ size=1
609
+ stride=1
610
+ pad=1
611
+ activation=mish
612
+
613
+ [route]
614
+ layers = -1,-28
615
+
616
+ [convolutional]
617
+ batch_normalize=1
618
+ filters=512
619
+ size=1
620
+ stride=1
621
+ pad=1
622
+ activation=mish
623
+
624
+ # Downsample
625
+
626
+ [convolutional]
627
+ batch_normalize=1
628
+ filters=1024
629
+ size=3
630
+ stride=2
631
+ pad=1
632
+ activation=mish
633
+
634
+ [convolutional]
635
+ batch_normalize=1
636
+ filters=512
637
+ size=1
638
+ stride=1
639
+ pad=1
640
+ activation=mish
641
+
642
+ [route]
643
+ layers = -2
644
+
645
+ [convolutional]
646
+ batch_normalize=1
647
+ filters=512
648
+ size=1
649
+ stride=1
650
+ pad=1
651
+ activation=mish
652
+
653
+ [convolutional]
654
+ batch_normalize=1
655
+ filters=512
656
+ size=1
657
+ stride=1
658
+ pad=1
659
+ activation=mish
660
+
661
+ [convolutional]
662
+ batch_normalize=1
663
+ filters=512
664
+ size=3
665
+ stride=1
666
+ pad=1
667
+ activation=mish
668
+
669
+ [shortcut]
670
+ from=-3
671
+ activation=linear
672
+
673
+ [convolutional]
674
+ batch_normalize=1
675
+ filters=512
676
+ size=1
677
+ stride=1
678
+ pad=1
679
+ activation=mish
680
+
681
+ [convolutional]
682
+ batch_normalize=1
683
+ filters=512
684
+ size=3
685
+ stride=1
686
+ pad=1
687
+ activation=mish
688
+
689
+ [shortcut]
690
+ from=-3
691
+ activation=linear
692
+
693
+ [convolutional]
694
+ batch_normalize=1
695
+ filters=512
696
+ size=1
697
+ stride=1
698
+ pad=1
699
+ activation=mish
700
+
701
+ [convolutional]
702
+ batch_normalize=1
703
+ filters=512
704
+ size=3
705
+ stride=1
706
+ pad=1
707
+ activation=mish
708
+
709
+ [shortcut]
710
+ from=-3
711
+ activation=linear
712
+
713
+ [convolutional]
714
+ batch_normalize=1
715
+ filters=512
716
+ size=1
717
+ stride=1
718
+ pad=1
719
+ activation=mish
720
+
721
+ [convolutional]
722
+ batch_normalize=1
723
+ filters=512
724
+ size=3
725
+ stride=1
726
+ pad=1
727
+ activation=mish
728
+
729
+ [shortcut]
730
+ from=-3
731
+ activation=linear
732
+
733
+ [convolutional]
734
+ batch_normalize=1
735
+ filters=512
736
+ size=1
737
+ stride=1
738
+ pad=1
739
+ activation=mish
740
+
741
+ [route]
742
+ layers = -1,-16
743
+
744
+ [convolutional]
745
+ batch_normalize=1
746
+ filters=1024
747
+ size=1
748
+ stride=1
749
+ pad=1
750
+ activation=mish
751
+
752
+ ##########################
753
+
754
+ [convolutional]
755
+ batch_normalize=1
756
+ filters=512
757
+ size=1
758
+ stride=1
759
+ pad=1
760
+ activation=mish
761
+
762
+ [route]
763
+ layers = -2
764
+
765
+ [convolutional]
766
+ batch_normalize=1
767
+ filters=512
768
+ size=1
769
+ stride=1
770
+ pad=1
771
+ activation=mish
772
+
773
+ [convolutional]
774
+ batch_normalize=1
775
+ size=3
776
+ stride=1
777
+ pad=1
778
+ filters=512
779
+ activation=mish
780
+
781
+ [convolutional]
782
+ batch_normalize=1
783
+ filters=512
784
+ size=1
785
+ stride=1
786
+ pad=1
787
+ activation=mish
788
+
789
+ ### SPP ###
790
+ [maxpool]
791
+ stride=1
792
+ size=5
793
+
794
+ [route]
795
+ layers=-2
796
+
797
+ [maxpool]
798
+ stride=1
799
+ size=9
800
+
801
+ [route]
802
+ layers=-4
803
+
804
+ [maxpool]
805
+ stride=1
806
+ size=13
807
+
808
+ [route]
809
+ layers=-1,-3,-5,-6
810
+ ### End SPP ###
811
+
812
+ [convolutional]
813
+ batch_normalize=1
814
+ filters=512
815
+ size=1
816
+ stride=1
817
+ pad=1
818
+ activation=mish
819
+
820
+ [convolutional]
821
+ batch_normalize=1
822
+ size=3
823
+ stride=1
824
+ pad=1
825
+ filters=512
826
+ activation=mish
827
+
828
+ [route]
829
+ layers = -1, -13
830
+
831
+ [convolutional]
832
+ batch_normalize=1
833
+ filters=512
834
+ size=1
835
+ stride=1
836
+ pad=1
837
+ activation=mish
838
+
839
+ [convolutional]
840
+ batch_normalize=1
841
+ filters=256
842
+ size=1
843
+ stride=1
844
+ pad=1
845
+ activation=mish
846
+
847
+ [upsample]
848
+ stride=2
849
+
850
+ [route]
851
+ layers = 79
852
+
853
+ [convolutional]
854
+ batch_normalize=1
855
+ filters=256
856
+ size=1
857
+ stride=1
858
+ pad=1
859
+ activation=mish
860
+
861
+ [route]
862
+ layers = -1, -3
863
+
864
+ [convolutional]
865
+ batch_normalize=1
866
+ filters=256
867
+ size=1
868
+ stride=1
869
+ pad=1
870
+ activation=mish
871
+
872
+ [convolutional]
873
+ batch_normalize=1
874
+ filters=256
875
+ size=1
876
+ stride=1
877
+ pad=1
878
+ activation=mish
879
+
880
+ [route]
881
+ layers = -2
882
+
883
+ [convolutional]
884
+ batch_normalize=1
885
+ filters=256
886
+ size=1
887
+ stride=1
888
+ pad=1
889
+ activation=mish
890
+
891
+ [convolutional]
892
+ batch_normalize=1
893
+ size=3
894
+ stride=1
895
+ pad=1
896
+ filters=256
897
+ activation=mish
898
+
899
+ [convolutional]
900
+ batch_normalize=1
901
+ filters=256
902
+ size=1
903
+ stride=1
904
+ pad=1
905
+ activation=mish
906
+
907
+ [convolutional]
908
+ batch_normalize=1
909
+ size=3
910
+ stride=1
911
+ pad=1
912
+ filters=256
913
+ activation=mish
914
+
915
+ [route]
916
+ layers = -1, -6
917
+
918
+ [convolutional]
919
+ batch_normalize=1
920
+ filters=256
921
+ size=1
922
+ stride=1
923
+ pad=1
924
+ activation=mish
925
+
926
+ [convolutional]
927
+ batch_normalize=1
928
+ filters=128
929
+ size=1
930
+ stride=1
931
+ pad=1
932
+ activation=mish
933
+
934
+ [upsample]
935
+ stride=2
936
+
937
+ [route]
938
+ layers = 48
939
+
940
+ [convolutional]
941
+ batch_normalize=1
942
+ filters=128
943
+ size=1
944
+ stride=1
945
+ pad=1
946
+ activation=mish
947
+
948
+ [route]
949
+ layers = -1, -3
950
+
951
+ [convolutional]
952
+ batch_normalize=1
953
+ filters=128
954
+ size=1
955
+ stride=1
956
+ pad=1
957
+ activation=mish
958
+
959
+ [convolutional]
960
+ batch_normalize=1
961
+ filters=128
962
+ size=1
963
+ stride=1
964
+ pad=1
965
+ activation=mish
966
+
967
+ [route]
968
+ layers = -2
969
+
970
+ [convolutional]
971
+ batch_normalize=1
972
+ filters=128
973
+ size=1
974
+ stride=1
975
+ pad=1
976
+ activation=mish
977
+
978
+ [convolutional]
979
+ batch_normalize=1
980
+ size=3
981
+ stride=1
982
+ pad=1
983
+ filters=128
984
+ activation=mish
985
+
986
+ [convolutional]
987
+ batch_normalize=1
988
+ filters=128
989
+ size=1
990
+ stride=1
991
+ pad=1
992
+ activation=mish
993
+
994
+ [convolutional]
995
+ batch_normalize=1
996
+ size=3
997
+ stride=1
998
+ pad=1
999
+ filters=128
1000
+ activation=mish
1001
+
1002
+ [route]
1003
+ layers = -1, -6
1004
+
1005
+ [convolutional]
1006
+ batch_normalize=1
1007
+ filters=128
1008
+ size=1
1009
+ stride=1
1010
+ pad=1
1011
+ activation=mish
1012
+
1013
+ ##########################
1014
+
1015
+ [convolutional]
1016
+ batch_normalize=1
1017
+ size=3
1018
+ stride=1
1019
+ pad=1
1020
+ filters=256
1021
+ activation=mish
1022
+
1023
+ [convolutional]
1024
+ size=1
1025
+ stride=1
1026
+ pad=1
1027
+ filters=255
1028
+ activation=logistic
1029
+
1030
+
1031
+ [yolo]
1032
+ mask = 0,1,2
1033
+ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
1034
+ classes=80
1035
+ num=9
1036
+ jitter=.1
1037
+ scale_x_y = 2.0
1038
+ objectness_smooth=0
1039
+ ignore_thresh = .7
1040
+ truth_thresh = 1
1041
+ #random=1
1042
+ resize=1.5
1043
+ iou_thresh=0.2
1044
+ iou_normalizer=0.05
1045
+ cls_normalizer=0.5
1046
+ obj_normalizer=4.0
1047
+ iou_loss=ciou
1048
+ nms_kind=diounms
1049
+ beta_nms=0.6
1050
+ new_coords=1
1051
+ max_delta=5
1052
+
1053
+ [route]
1054
+ layers = -4
1055
+
1056
+ [convolutional]
1057
+ batch_normalize=1
1058
+ size=3
1059
+ stride=2
1060
+ pad=1
1061
+ filters=256
1062
+ activation=mish
1063
+
1064
+ [route]
1065
+ layers = -1, -20
1066
+
1067
+ [convolutional]
1068
+ batch_normalize=1
1069
+ filters=256
1070
+ size=1
1071
+ stride=1
1072
+ pad=1
1073
+ activation=mish
1074
+
1075
+ [convolutional]
1076
+ batch_normalize=1
1077
+ filters=256
1078
+ size=1
1079
+ stride=1
1080
+ pad=1
1081
+ activation=mish
1082
+
1083
+ [route]
1084
+ layers = -2
1085
+
1086
+ [convolutional]
1087
+ batch_normalize=1
1088
+ filters=256
1089
+ size=1
1090
+ stride=1
1091
+ pad=1
1092
+ activation=mish
1093
+
1094
+ [convolutional]
1095
+ batch_normalize=1
1096
+ size=3
1097
+ stride=1
1098
+ pad=1
1099
+ filters=256
1100
+ activation=mish
1101
+
1102
+ [convolutional]
1103
+ batch_normalize=1
1104
+ filters=256
1105
+ size=1
1106
+ stride=1
1107
+ pad=1
1108
+ activation=mish
1109
+
1110
+ [convolutional]
1111
+ batch_normalize=1
1112
+ size=3
1113
+ stride=1
1114
+ pad=1
1115
+ filters=256
1116
+ activation=mish
1117
+
1118
+ [route]
1119
+ layers = -1,-6
1120
+
1121
+ [convolutional]
1122
+ batch_normalize=1
1123
+ filters=256
1124
+ size=1
1125
+ stride=1
1126
+ pad=1
1127
+ activation=mish
1128
+
1129
+ [convolutional]
1130
+ batch_normalize=1
1131
+ size=3
1132
+ stride=1
1133
+ pad=1
1134
+ filters=512
1135
+ activation=mish
1136
+
1137
+ [convolutional]
1138
+ size=1
1139
+ stride=1
1140
+ pad=1
1141
+ filters=255
1142
+ activation=logistic
1143
+
1144
+
1145
+ [yolo]
1146
+ mask = 3,4,5
1147
+ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
1148
+ classes=80
1149
+ num=9
1150
+ jitter=.1
1151
+ scale_x_y = 2.0
1152
+ objectness_smooth=1
1153
+ ignore_thresh = .7
1154
+ truth_thresh = 1
1155
+ #random=1
1156
+ resize=1.5
1157
+ iou_thresh=0.2
1158
+ iou_normalizer=0.05
1159
+ cls_normalizer=0.5
1160
+ obj_normalizer=1.0
1161
+ iou_loss=ciou
1162
+ nms_kind=diounms
1163
+ beta_nms=0.6
1164
+ new_coords=1
1165
+ max_delta=5
1166
+
1167
+ [route]
1168
+ layers = -4
1169
+
1170
+ [convolutional]
1171
+ batch_normalize=1
1172
+ size=3
1173
+ stride=2
1174
+ pad=1
1175
+ filters=512
1176
+ activation=mish
1177
+
1178
+ [route]
1179
+ layers = -1, -49
1180
+
1181
+ [convolutional]
1182
+ batch_normalize=1
1183
+ filters=512
1184
+ size=1
1185
+ stride=1
1186
+ pad=1
1187
+ activation=mish
1188
+
1189
+ [convolutional]
1190
+ batch_normalize=1
1191
+ filters=512
1192
+ size=1
1193
+ stride=1
1194
+ pad=1
1195
+ activation=mish
1196
+
1197
+ [route]
1198
+ layers = -2
1199
+
1200
+ [convolutional]
1201
+ batch_normalize=1
1202
+ filters=512
1203
+ size=1
1204
+ stride=1
1205
+ pad=1
1206
+ activation=mish
1207
+
1208
+ [convolutional]
1209
+ batch_normalize=1
1210
+ size=3
1211
+ stride=1
1212
+ pad=1
1213
+ filters=512
1214
+ activation=mish
1215
+
1216
+ [convolutional]
1217
+ batch_normalize=1
1218
+ filters=512
1219
+ size=1
1220
+ stride=1
1221
+ pad=1
1222
+ activation=mish
1223
+
1224
+ [convolutional]
1225
+ batch_normalize=1
1226
+ size=3
1227
+ stride=1
1228
+ pad=1
1229
+ filters=512
1230
+ activation=mish
1231
+
1232
+ [route]
1233
+ layers = -1,-6
1234
+
1235
+ [convolutional]
1236
+ batch_normalize=1
1237
+ filters=512
1238
+ size=1
1239
+ stride=1
1240
+ pad=1
1241
+ activation=mish
1242
+
1243
+ [convolutional]
1244
+ batch_normalize=1
1245
+ size=3
1246
+ stride=1
1247
+ pad=1
1248
+ filters=1024
1249
+ activation=mish
1250
+
1251
+ [convolutional]
1252
+ size=1
1253
+ stride=1
1254
+ pad=1
1255
+ filters=255
1256
+ activation=logistic
1257
+
1258
+
1259
+ [yolo]
1260
+ mask = 6,7,8
1261
+ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
1262
+ classes=80
1263
+ num=9
1264
+ jitter=.1
1265
+ scale_x_y = 2.0
1266
+ objectness_smooth=1
1267
+ ignore_thresh = .7
1268
+ truth_thresh = 1
1269
+ #random=1
1270
+ resize=1.5
1271
+ iou_thresh=0.2
1272
+ iou_normalizer=0.05
1273
+ cls_normalizer=0.5
1274
+ obj_normalizer=0.4
1275
+ iou_loss=ciou
1276
+ nms_kind=diounms
1277
+ beta_nms=0.6
1278
+ new_coords=1
1279
+ max_delta=2
yolov4-csp.weights ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:019496affba568f7439e54797a1772657bb01126b707fbd93407c0b20c20dca1
3
+ size 211944840
yolov4-tiny.cfg ADDED
@@ -0,0 +1,294 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [net]
2
+ # Testing
3
+ #batch=1
4
+ #subdivisions=1
5
+ # Training
6
+ batch=64
7
+ subdivisions=1
8
+ width=416
9
+ height=416
10
+ channels=3
11
+ momentum=0.9
12
+ decay=0.0005
13
+ angle=0
14
+ saturation = 1.5
15
+ exposure = 1.5
16
+ hue=.1
17
+
18
+ learning_rate=0.00261
19
+ burn_in=1000
20
+
21
+ max_batches = 2000200
22
+ policy=steps
23
+ steps=1600000,1800000
24
+ scales=.1,.1
25
+
26
+
27
+ #weights_reject_freq=1001
28
+ #ema_alpha=0.9998
29
+ #equidistant_point=1000
30
+ #num_sigmas_reject_badlabels=3
31
+ #badlabels_rejection_percentage=0.2
32
+
33
+
34
+ [convolutional]
35
+ batch_normalize=1
36
+ filters=32
37
+ size=3
38
+ stride=2
39
+ pad=1
40
+ activation=leaky
41
+
42
+ [convolutional]
43
+ batch_normalize=1
44
+ filters=64
45
+ size=3
46
+ stride=2
47
+ pad=1
48
+ activation=leaky
49
+
50
+ [convolutional]
51
+ batch_normalize=1
52
+ filters=64
53
+ size=3
54
+ stride=1
55
+ pad=1
56
+ activation=leaky
57
+
58
+ [route]
59
+ layers=-1
60
+ groups=2
61
+ group_id=1
62
+
63
+ [convolutional]
64
+ batch_normalize=1
65
+ filters=32
66
+ size=3
67
+ stride=1
68
+ pad=1
69
+ activation=leaky
70
+
71
+ [convolutional]
72
+ batch_normalize=1
73
+ filters=32
74
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513
+
514
+
515
+ [convolutional]
516
+ batch_normalize=1
517
+ filters=256
518
+ size=1
519
+ stride=1
520
+ pad=1
521
+ activation=mish
522
+
523
+ [convolutional]
524
+ batch_normalize=1
525
+ filters=256
526
+ size=3
527
+ stride=1
528
+ pad=1
529
+ activation=mish
530
+
531
+ [shortcut]
532
+ from=-3
533
+ activation=linear
534
+
535
+
536
+ [convolutional]
537
+ batch_normalize=1
538
+ filters=256
539
+ size=1
540
+ stride=1
541
+ pad=1
542
+ activation=mish
543
+
544
+ [convolutional]
545
+ batch_normalize=1
546
+ filters=256
547
+ size=3
548
+ stride=1
549
+ pad=1
550
+ activation=mish
551
+
552
+ [shortcut]
553
+ from=-3
554
+ activation=linear
555
+
556
+
557
+ [convolutional]
558
+ batch_normalize=1
559
+ filters=256
560
+ size=1
561
+ stride=1
562
+ pad=1
563
+ activation=mish
564
+
565
+ [convolutional]
566
+ batch_normalize=1
567
+ filters=256
568
+ size=3
569
+ stride=1
570
+ pad=1
571
+ activation=mish
572
+
573
+ [shortcut]
574
+ from=-3
575
+ activation=linear
576
+
577
+ [convolutional]
578
+ batch_normalize=1
579
+ filters=256
580
+ size=1
581
+ stride=1
582
+ pad=1
583
+ activation=mish
584
+
585
+ [convolutional]
586
+ batch_normalize=1
587
+ filters=256
588
+ size=3
589
+ stride=1
590
+ pad=1
591
+ activation=mish
592
+
593
+ [shortcut]
594
+ from=-3
595
+ activation=linear
596
+
597
+ [convolutional]
598
+ batch_normalize=1
599
+ filters=256
600
+ size=1
601
+ stride=1
602
+ pad=1
603
+ activation=mish
604
+
605
+ [route]
606
+ layers = -1,-28
607
+
608
+ [convolutional]
609
+ batch_normalize=1
610
+ filters=512
611
+ size=1
612
+ stride=1
613
+ pad=1
614
+ activation=mish
615
+
616
+ # Downsample
617
+
618
+ [convolutional]
619
+ batch_normalize=1
620
+ filters=1024
621
+ size=3
622
+ stride=2
623
+ pad=1
624
+ activation=mish
625
+
626
+ [convolutional]
627
+ batch_normalize=1
628
+ filters=512
629
+ size=1
630
+ stride=1
631
+ pad=1
632
+ activation=mish
633
+
634
+ [route]
635
+ layers = -2
636
+
637
+ [convolutional]
638
+ batch_normalize=1
639
+ filters=512
640
+ size=1
641
+ stride=1
642
+ pad=1
643
+ activation=mish
644
+
645
+ [convolutional]
646
+ batch_normalize=1
647
+ filters=512
648
+ size=1
649
+ stride=1
650
+ pad=1
651
+ activation=mish
652
+
653
+ [convolutional]
654
+ batch_normalize=1
655
+ filters=512
656
+ size=3
657
+ stride=1
658
+ pad=1
659
+ activation=mish
660
+
661
+ [shortcut]
662
+ from=-3
663
+ activation=linear
664
+
665
+ [convolutional]
666
+ batch_normalize=1
667
+ filters=512
668
+ size=1
669
+ stride=1
670
+ pad=1
671
+ activation=mish
672
+
673
+ [convolutional]
674
+ batch_normalize=1
675
+ filters=512
676
+ size=3
677
+ stride=1
678
+ pad=1
679
+ activation=mish
680
+
681
+ [shortcut]
682
+ from=-3
683
+ activation=linear
684
+
685
+ [convolutional]
686
+ batch_normalize=1
687
+ filters=512
688
+ size=1
689
+ stride=1
690
+ pad=1
691
+ activation=mish
692
+
693
+ [convolutional]
694
+ batch_normalize=1
695
+ filters=512
696
+ size=3
697
+ stride=1
698
+ pad=1
699
+ activation=mish
700
+
701
+ [shortcut]
702
+ from=-3
703
+ activation=linear
704
+
705
+ [convolutional]
706
+ batch_normalize=1
707
+ filters=512
708
+ size=1
709
+ stride=1
710
+ pad=1
711
+ activation=mish
712
+
713
+ [convolutional]
714
+ batch_normalize=1
715
+ filters=512
716
+ size=3
717
+ stride=1
718
+ pad=1
719
+ activation=mish
720
+
721
+ [shortcut]
722
+ from=-3
723
+ activation=linear
724
+
725
+ [convolutional]
726
+ batch_normalize=1
727
+ filters=512
728
+ size=1
729
+ stride=1
730
+ pad=1
731
+ activation=mish
732
+
733
+ [route]
734
+ layers = -1,-16
735
+
736
+ [convolutional]
737
+ batch_normalize=1
738
+ filters=1024
739
+ size=1
740
+ stride=1
741
+ pad=1
742
+ activation=mish
743
+
744
+ ##########################
745
+
746
+ [convolutional]
747
+ batch_normalize=1
748
+ filters=512
749
+ size=1
750
+ stride=1
751
+ pad=1
752
+ activation=leaky
753
+
754
+ [convolutional]
755
+ batch_normalize=1
756
+ size=3
757
+ stride=1
758
+ pad=1
759
+ filters=1024
760
+ activation=leaky
761
+
762
+ [convolutional]
763
+ batch_normalize=1
764
+ filters=512
765
+ size=1
766
+ stride=1
767
+ pad=1
768
+ activation=leaky
769
+
770
+ ### SPP ###
771
+ [maxpool]
772
+ stride=1
773
+ size=5
774
+
775
+ [route]
776
+ layers=-2
777
+
778
+ [maxpool]
779
+ stride=1
780
+ size=9
781
+
782
+ [route]
783
+ layers=-4
784
+
785
+ [maxpool]
786
+ stride=1
787
+ size=13
788
+
789
+ [route]
790
+ layers=-1,-3,-5,-6
791
+ ### End SPP ###
792
+
793
+ [convolutional]
794
+ batch_normalize=1
795
+ filters=512
796
+ size=1
797
+ stride=1
798
+ pad=1
799
+ activation=leaky
800
+
801
+ [convolutional]
802
+ batch_normalize=1
803
+ size=3
804
+ stride=1
805
+ pad=1
806
+ filters=1024
807
+ activation=leaky
808
+
809
+ [convolutional]
810
+ batch_normalize=1
811
+ filters=512
812
+ size=1
813
+ stride=1
814
+ pad=1
815
+ activation=leaky
816
+
817
+ [convolutional]
818
+ batch_normalize=1
819
+ filters=256
820
+ size=1
821
+ stride=1
822
+ pad=1
823
+ activation=leaky
824
+
825
+ [upsample]
826
+ stride=2
827
+
828
+ [route]
829
+ layers = 85
830
+
831
+ [convolutional]
832
+ batch_normalize=1
833
+ filters=256
834
+ size=1
835
+ stride=1
836
+ pad=1
837
+ activation=leaky
838
+
839
+ [route]
840
+ layers = -1, -3
841
+
842
+ [convolutional]
843
+ batch_normalize=1
844
+ filters=256
845
+ size=1
846
+ stride=1
847
+ pad=1
848
+ activation=leaky
849
+
850
+ [convolutional]
851
+ batch_normalize=1
852
+ size=3
853
+ stride=1
854
+ pad=1
855
+ filters=512
856
+ activation=leaky
857
+
858
+ [convolutional]
859
+ batch_normalize=1
860
+ filters=256
861
+ size=1
862
+ stride=1
863
+ pad=1
864
+ activation=leaky
865
+
866
+ [convolutional]
867
+ batch_normalize=1
868
+ size=3
869
+ stride=1
870
+ pad=1
871
+ filters=512
872
+ activation=leaky
873
+
874
+ [convolutional]
875
+ batch_normalize=1
876
+ filters=256
877
+ size=1
878
+ stride=1
879
+ pad=1
880
+ activation=leaky
881
+
882
+ [convolutional]
883
+ batch_normalize=1
884
+ filters=128
885
+ size=1
886
+ stride=1
887
+ pad=1
888
+ activation=leaky
889
+
890
+ [upsample]
891
+ stride=2
892
+
893
+ [route]
894
+ layers = 54
895
+
896
+ [convolutional]
897
+ batch_normalize=1
898
+ filters=128
899
+ size=1
900
+ stride=1
901
+ pad=1
902
+ activation=leaky
903
+
904
+ [route]
905
+ layers = -1, -3
906
+
907
+ [convolutional]
908
+ batch_normalize=1
909
+ filters=128
910
+ size=1
911
+ stride=1
912
+ pad=1
913
+ activation=leaky
914
+
915
+ [convolutional]
916
+ batch_normalize=1
917
+ size=3
918
+ stride=1
919
+ pad=1
920
+ filters=256
921
+ activation=leaky
922
+
923
+ [convolutional]
924
+ batch_normalize=1
925
+ filters=128
926
+ size=1
927
+ stride=1
928
+ pad=1
929
+ activation=leaky
930
+
931
+ [convolutional]
932
+ batch_normalize=1
933
+ size=3
934
+ stride=1
935
+ pad=1
936
+ filters=256
937
+ activation=leaky
938
+
939
+ [convolutional]
940
+ batch_normalize=1
941
+ filters=128
942
+ size=1
943
+ stride=1
944
+ pad=1
945
+ activation=leaky
946
+
947
+ ##########################
948
+
949
+ [convolutional]
950
+ batch_normalize=1
951
+ size=3
952
+ stride=1
953
+ pad=1
954
+ filters=256
955
+ activation=leaky
956
+
957
+ [convolutional]
958
+ size=1
959
+ stride=1
960
+ pad=1
961
+ filters=255
962
+ activation=linear
963
+
964
+
965
+ [yolo]
966
+ mask = 0,1,2
967
+ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
968
+ classes=80
969
+ num=9
970
+ jitter=.3
971
+ ignore_thresh = .7
972
+ truth_thresh = 1
973
+ scale_x_y = 1.2
974
+ iou_thresh=0.213
975
+ cls_normalizer=1.0
976
+ iou_normalizer=0.07
977
+ iou_loss=ciou
978
+ nms_kind=greedynms
979
+ beta_nms=0.6
980
+ max_delta=5
981
+
982
+
983
+ [route]
984
+ layers = -4
985
+
986
+ [convolutional]
987
+ batch_normalize=1
988
+ size=3
989
+ stride=2
990
+ pad=1
991
+ filters=256
992
+ activation=leaky
993
+
994
+ [route]
995
+ layers = -1, -16
996
+
997
+ [convolutional]
998
+ batch_normalize=1
999
+ filters=256
1000
+ size=1
1001
+ stride=1
1002
+ pad=1
1003
+ activation=leaky
1004
+
1005
+ [convolutional]
1006
+ batch_normalize=1
1007
+ size=3
1008
+ stride=1
1009
+ pad=1
1010
+ filters=512
1011
+ activation=leaky
1012
+
1013
+ [convolutional]
1014
+ batch_normalize=1
1015
+ filters=256
1016
+ size=1
1017
+ stride=1
1018
+ pad=1
1019
+ activation=leaky
1020
+
1021
+ [convolutional]
1022
+ batch_normalize=1
1023
+ size=3
1024
+ stride=1
1025
+ pad=1
1026
+ filters=512
1027
+ activation=leaky
1028
+
1029
+ [convolutional]
1030
+ batch_normalize=1
1031
+ filters=256
1032
+ size=1
1033
+ stride=1
1034
+ pad=1
1035
+ activation=leaky
1036
+
1037
+ [convolutional]
1038
+ batch_normalize=1
1039
+ size=3
1040
+ stride=1
1041
+ pad=1
1042
+ filters=512
1043
+ activation=leaky
1044
+
1045
+ [convolutional]
1046
+ size=1
1047
+ stride=1
1048
+ pad=1
1049
+ filters=255
1050
+ activation=linear
1051
+
1052
+
1053
+ [yolo]
1054
+ mask = 3,4,5
1055
+ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
1056
+ classes=80
1057
+ num=9
1058
+ jitter=.3
1059
+ ignore_thresh = .7
1060
+ truth_thresh = 1
1061
+ scale_x_y = 1.1
1062
+ iou_thresh=0.213
1063
+ cls_normalizer=1.0
1064
+ iou_normalizer=0.07
1065
+ iou_loss=ciou
1066
+ nms_kind=greedynms
1067
+ beta_nms=0.6
1068
+ max_delta=5
1069
+
1070
+
1071
+ [route]
1072
+ layers = -4
1073
+
1074
+ [convolutional]
1075
+ batch_normalize=1
1076
+ size=3
1077
+ stride=2
1078
+ pad=1
1079
+ filters=512
1080
+ activation=leaky
1081
+
1082
+ [route]
1083
+ layers = -1, -37
1084
+
1085
+ [convolutional]
1086
+ batch_normalize=1
1087
+ filters=512
1088
+ size=1
1089
+ stride=1
1090
+ pad=1
1091
+ activation=leaky
1092
+
1093
+ [convolutional]
1094
+ batch_normalize=1
1095
+ size=3
1096
+ stride=1
1097
+ pad=1
1098
+ filters=1024
1099
+ activation=leaky
1100
+
1101
+ [convolutional]
1102
+ batch_normalize=1
1103
+ filters=512
1104
+ size=1
1105
+ stride=1
1106
+ pad=1
1107
+ activation=leaky
1108
+
1109
+ [convolutional]
1110
+ batch_normalize=1
1111
+ size=3
1112
+ stride=1
1113
+ pad=1
1114
+ filters=1024
1115
+ activation=leaky
1116
+
1117
+ [convolutional]
1118
+ batch_normalize=1
1119
+ filters=512
1120
+ size=1
1121
+ stride=1
1122
+ pad=1
1123
+ activation=leaky
1124
+
1125
+ [convolutional]
1126
+ batch_normalize=1
1127
+ size=3
1128
+ stride=1
1129
+ pad=1
1130
+ filters=1024
1131
+ activation=leaky
1132
+
1133
+ [convolutional]
1134
+ size=1
1135
+ stride=1
1136
+ pad=1
1137
+ filters=255
1138
+ activation=linear
1139
+
1140
+
1141
+ [yolo]
1142
+ mask = 6,7,8
1143
+ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
1144
+ classes=80
1145
+ num=9
1146
+ jitter=.3
1147
+ ignore_thresh = .7
1148
+ truth_thresh = 1
1149
+ random=1
1150
+ scale_x_y = 1.05
1151
+ iou_thresh=0.213
1152
+ cls_normalizer=1.0
1153
+ iou_normalizer=0.07
1154
+ iou_loss=ciou
1155
+ nms_kind=greedynms
1156
+ beta_nms=0.6
1157
+ max_delta=5
1158
+
yolov4.weights ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e8a4f6c62188738d86dc6898d82724ec0964d0eb9d2ae0f0a9d53d65d108d562
3
+ size 257717640