├── Copy_of_PotholeDetectionUsingYOLO.ipynb
├── LICENSE
├── PotholeDetectionUsingYOLO.ipynb
├── Potholes.ipynb
└── README.md
/LICENSE:
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1 | MIT License
2 |
3 | Copyright (c) 2023 Mounish Vatti
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
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9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
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12 | The above copyright notice and this permission notice shall be included in all
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15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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21 | SOFTWARE.
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/README.md:
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1 | 
2 |
3 | Image Segmentation & Pothole Detection
4 |
5 | ## Google Colab File Link (A Single Click Solution)
6 | The google colab file link for yolov8 segmentation and tracking is provided below, you can check the implementation in Google Colab, and its a single click implementation
7 | ,you just need to select the Run Time as GPU, and click on Run All.
8 |
9 | [`Google Colab File`](https://colab.research.google.com/drive/17SLXw-wdHG2syQhLSHH5r5_rkZx5poo0)
10 |
11 | ## Tech stack
12 |
13 | 
14 |
15 | ## Object Segmentation and Tracking (ID + Trails) using YOLOv8 on Custom Data
16 |
17 | Clone the repository
18 |
19 | ```bash
20 | !git clone https://github.com/mounishvatti/pothole_detection_yolov8.git
21 | ```
22 | Goto the cloned folder
23 |
24 | ```bash
25 | cd pothole_detection_yolov8
26 | ```
27 | Install the Dependencies
28 |
29 | ```bash
30 | !pip install ultralytics
31 | ```
32 | ```bash
33 | !pip install roboflow
34 | ```
35 | ```bash
36 | !pip install fastapi kaleido python_multipart uvicorn
37 | ```
38 | Importing YOLO and a roboflow workspace for Image Segmentation
39 |
40 | ```python
41 | from roboflow import Roboflow
42 | rf = Roboflow(api_key="{the api key}")
43 | project = rf.workspace("{name of workspace}").project("name-of-project")
44 | dataset = project.version(1).download("yolov8")
45 | ```
46 |
47 | > [!NOTE]
48 | > If you are unable to perform the commands after importing the dataset from roboflow, you can access the same dataset by downloading it, upload it to your personal drive and mount the drive to your Google Colab
49 |
50 | My roboflow workspace containing the pothole dataset
51 |
52 | [`Roboflow Workspace`](https://app.roboflow.com/vit-76kid/pothole-detection-project-3yiqt/1)
53 |
54 | Run the code with mentioned command below.
55 | - For training the data
56 | ```python
57 | !yolo task=detect mode=train model=yolov8m.pt data={dataset.location}/data.yaml epochs={number of epochs} imgsz=640
58 | ```
59 | - For yolov8 segmentation + Tracking & prediction
60 | ```python
61 | !yolo task=detect mode=predict model={HOME}/runs/detect/train/weights/best.pt conf=0.25 source='/content/drive/MyDrive/demo.mp4'
62 | ```
63 |
64 |
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