Car-Crash-Detection 0.0.5

Car Crash Detection From Surveillance Cameras and Video Streams

Car Crash Detection Package

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Abstract

Car Crash Detection can be seen as the Detection of Accident or Not in a video according to the actions occurring in it. It has become one of the most challenging and attractive problems in video classification and detection fields. The problem itself is difficult to solve by traditional video processing methods because of several challenges such as the background noise, sizes of subjects in different videos, and the speed of Cars.Derived from the progress of deep learning methods, several directions are developed for video detection, such as the long-short-term memory (LSTM)-based model, two-stream convolutional neural network (CNN) model, and the convolutional 3D model. Car Crash Detection is used in some surveillance systems and video processing tools. Our main problem is Accident Detection which we achieved to solve by using transfer learning on pretrained convolutional 3D models that aim to recognize the motions and actions of Cars. All models use Kinetics-400 dataset for the pretrained part and Vision-based Accident Detection From Surveillance Cameras dataset for the finetuned part.

Pytorch Pretrained Models

All pretrained models can be found in this link. lhttps://pytorch.org/vision/stable/models.html

Instructions to Install our Car Crash Detection Package

1. Install:

pip install Car-Crash-Detection
pip install pytube

2. Download the Finetunned Model Weights

import gdown
url = 'https://drive.google.com/uc?id=1-8TyT7MkAS7LLsRTbO03tDsuuoBM6q1D'
model = 'model_ft.pth'
gdown.download(url, model, quiet=False)

3. Detect Accident or Not by Pass your Local Video:

from car_crash_detection import CrashUtils
# Run the Below Function by Input your Test Video Path to get the outPut Video with Accident Detection or Not
CrashUtils.crashDetection(inputPath,seq,skip,outputPath,showInfo=False,thresholding=0.85)

4. Show the Output Video with Detection:

from moviepy.editor import *
VideoFileClip(outputPath, audio=False, target_resolution=(300,None)).ipython_display()

5. To Start Detect the Accident on Streaming

CrashUtils.start_streaming(streamingURL,thresholding=0.85)