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object_detection_nanodet

Nanodet

Nanodet: NanoDet is a FCOS-style one-stage anchor-free object detection model which using Generalized Focal Loss as classification and regression loss.In NanoDet-Plus, we propose a novel label assignment strategy with a simple assign guidance module (AGM) and a dynamic soft label assigner (DSLA) to solve the optimal label assignment problem in lightweight model training.

Note:

  • This version of nanodet: Nanodet-m-plus-1.5x_416

Demo

Run the following command to try the demo:

# detect on camera input
python demo.py
# detect on an image
python demo.py --input /path/to/image -v

Note:

  • image result saved as "result.jpg"

Results

Here are some of the sample results that were observed using the model,

test1_res.jpg test2_res.jpg

Check benchmark/download_data.py for the original images.

Video inference result, WebCamR.gif

Model metrics:

The model is evaluated on COCO 2017 val. Results are showed below:

Average Precision Average Recall
area IoU Average Precision(AP)
all 0.50:0.95 0.304
all 0.50 0.459
all 0.75 0.317
small 0.50:0.95 0.107
medium 0.50:0.95 0.322
large 0.50:0.95 0.478
area IoU Average Recall
all 0.50:0.95 0.278
all 0.50:0.95 0.434
all 0.50:0.95 0.462
small 0.50:0.95 0.198
medium 0.50:0.95 0.510
large 0.50:0.95 0.702
class AP50 mAP class AP50 mAP
person 67.5 41.8 bicycle 35.4 18.8
car 45.0 25.4 motorcycle 58.9 33.1
airplane 77.3 58.9 bus 68.8 56.4
train 81.1 60.5 truck 38.6 24.7
boat 35.5 16.7 traffic light 30.5 14.0
fire hydrant 69.8 54.5 stop sign 60.9 54.6
parking meter 55.1 38.5 bench 26.8 15.9
bird 38.3 23.6 cat 82.5 62.1
dog 67.0 51.4 horse 64.3 44.2
sheep 57.7 35.8 cow 61.2 39.9
elephant 79.9 56.2 bear 81.8 63.0
zebra 85.4 59.5 giraffe 84.1 59.9
backpack 12.4 5.9 umbrella 46.5 28.8
handbag 8.4 3.7 tie 35.2 19.6
suitcase 38.1 23.8 frisbee 60.7 43.9
skis 30.5 14.5 snowboard 32.3 18.2
sports ball 37.6 24.5 kite 51.1 30.4
baseball bat 28.9 13.6 baseball glove 40.1 21.6
skateboard 59.4 35.2 surfboard 47.9 26.6
tennis racket 55.2 30.5 bottle 34.7 20.2
wine glass 27.8 16.3 cup 35.5 23.7
fork 25.9 14.8 knife 10.9 5.6
spoon 8.7 4.1 bowl 42.8 29.4
banana 35.5 18.5 apple 19.4 12.9
sandwich 46.7 33.4 orange 35.2 25.9
broccoli 36.4 19.1 carrot 30.9 17.8
hot dog 42.7 29.3 pizza 61.0 44.9
donut 47.3 34.0 cake 39.9 24.4
chair 28.8 16.1 couch 60.5 42.6
potted plant 29.0 15.3 bed 63.3 46.0
dining table 39.6 27.5 toilet 71.3 55.3
tv 66.5 48.1 laptop 62.6 46.9
mouse 63.5 44.1 remote 19.8 10.3
keyboard 62.1 41.5 cell phone 33.7 22.8
microwave 54.9 39.6 oven 48.1 30.4
toaster 30.0 16.4 sink 44.5 27.8
refrigerator 63.2 46.1 book 18.4 7.3
clock 57.8 35.8 vase 33.7 22.1
scissors 27.8 17.8 teddy bear 54.1 35.4
hair drier 2.9 1.1 toothbrush 13.1 8.2

License

All files in this directory are licensed under Apache 2.0 License.

Contributor Details

  • Google Summer of Code'22
  • Contributor: Sri Siddarth Chakaravarthy
  • Github Profile: https://github.com/Sidd1609
  • Organisation: OpenCV
  • Project: Lightweight object detection models using OpenCV

Reference