- We recommend you to use Anaconda to create a conda environment:
conda create -n imagenet python=3.6
- Then, activate the environment:
pip install -r requirements.txt
PyTorch >= 1.9.1 and Torchvision >= 0.10.1
Model |
Epoch |
size |
acc@1 |
GFLOPs |
Params |
Weight |
DarkNet-19 |
90 |
224 |
72.9 |
5.4 |
20.8 M |
ckpt |
DarkNet-53-SiLU |
100 |
224 |
74.4 |
14.3 |
41.6 M |
ckpt |
CSP-DarkNet-53-SiLU |
100 |
224 |
75.0 |
9.4 |
27.3 M |
ckpt |
DarkNet-Tiny |
100 |
224 |
60.1 |
0.5 |
1.6 M |
ckpt |
CSPDarkNet-Tiny |
100 |
224 |
61.1 |
0.4 |
1.3 M |
ckpt |
Model |
Epoch |
size |
acc@1 |
GFLOPs |
Params |
Weight |
CSPDarkNet-Nano |
100 |
224 |
60.6 |
0.3 |
1.3 M |
ckpt |
CSPDarkNet-Small |
100 |
224 |
69.8 |
1.3 |
4.6 M |
ckpt |
CSPDarkNet-Medium |
100 |
224 |
72.9 |
3.8 |
12.8 M |
ckpt |
CSPDarkNet-Large |
100 |
224 |
75.1 |
8.6 |
27.5 M |
ckpt |
CSPDarkNet-Huge |
100 |
224 |
|
16.3 |
50.5 M |
|
Model |
Epoch |
size |
acc@1 |
GFLOPs |
Params |
Weight |
ELANNet-Nano |
100 |
224 |
48.7 |
0.03 |
0.4 M |
ckpt |
ELANNet-Tiny |
100 |
224 |
64.8 |
0.3 |
1.4 M |
ckpt |
ELANNet-Large |
100 |
224 |
75.1 |
4.1 |
14.4 M |
ckpt |
ELANNet-Huge |
100 |
224 |
76.2 |
7.5 |
26.4 M |
ckpt |
Model |
Epoch |
size |
acc@1 |
GFLOPs |
Params |
Weight |
ELANNetv2-Pico |
100 |
224 |
59.8 |
0.2 |
0.6 M |
ckpt |
ELANNetv2-Nano |
100 |
224 |
60.8 |
0.4 |
0.9 M |
ckpt |
ELANNetv2-Tiny |
100 |
224 |
67.1 |
0.9 |
1.9 M |
ckpt |
ELANNetv2-Small |
100 |
224 |
70.4 |
1.7 |
3.3 M |
ckpt |
- RTCNet (Yolov8's backbone)
Model |
Epoch |
size |
acc@1 |
GFLOPs |
Params |
Weight |
RTCNet-P |
90 |
224 |
|
|
|
|
RTCNet-N |
90 |
224 |
60.7 |
0.38 |
1.36 M |
|
RTCNet-S |
90 |
224 |
|
1.47 |
4.94 M |
|
RTCNet-M |
90 |
224 |
|
|
|
|
RTCNet-L |
90 |
224 |
|
|
|
|
RTCNet-X |
90 |
224 |
|
|
|
|