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machine-learning-road-damaged-detection's Introduction

Road-Damage-Detection

How to Run

  1. Set up the CUDA Toolkit and CUDNN versions that support TensorFlow-GPU version 2.7.0. You can find the installation instructions and tested build configuration at https://www.tensorflow.org/install/source#gpu.
  2. Open main.pynb
  3. Install the requirement:
!pip install -r requirements.txt 
  1. Run:
from pipeline_func import *
  1. Modify the input_video with the desired input video path, and change out_folder with the desired output folder name.
print("Start") # To see the progress (if running in VSCode)

input_video = "input/1.mp4"
out_folder = "video_output"

# function definition located in pipeline_func.py file (line 498)
road_damage_detection(input_video, out_folder)
  1. Wait

Pothole Detection

Pothole Detection

Aligator Crack Detection

Aligator Crack Detection

CSV Damaged Detail

CSV Detail

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