lightweight video detection
Project description
SocialDistance
Keep safe social distance is considered as an effective way of avoiding spreading of coronavirus. Our SocialDistance module SDD is a lightweight package which provides an implementation of utlizing deep learning models for monitoring safe social distance.
Demo
Dataset
We use the video clip collected from OXFORD TOWN CENTRE dataset and made the above demo video.
Supported Models
We have tested our model using YOLO-v3 and SSD, based on the performance of each model, we have chosen YOLO-v3 as our default model
All our pretrained models are selected from Gluno CV Tookit
Installation
You may be able to obtain the latest version our model from:
pip install SDD
How to Use
After Successfully installed SocialDistance, you can use it for detection by:
import SDD
import mxnet as mx
from SDD.utils.Run import Detect
detect = Detect(pretrained_models = 'yolo_v3')
detector = detect(save_path = output_path_image, video = False, device = mx.cpu())
_ = detector(file_path)
Parameters
- pretrained_models: str, Currently, we provided two pretrained models: 'yolo_v3' and 'ssd'
- save_path: str, Path where you want to save the output video/ images
- video: boolean, If your input is a video, set this parameter as True, if your input is a set of images, set this parameter as False
- device: mx.cpu() or mx.gpu()
- file_path: str, Input path of your video or image folder
Reference
- Landing AI 16 April 2020, Landing AI Creates an AI Tool to Help Customers Monitor Social Distancing in the Workplace, accessed 19 April 2020, https://landing.ai/landing-ai-creates-an-ai-tool-to-help-customers-monitor-social-distancing-in-the-workplace/
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