You will get Car scratch and damage detection using Yolov8
Project details
Through the implementation of the car scratch and damage detection project using YOLOv8, I acquired valuable hands-on experience and insights that significantly enriched my skill set in computer vision and deep learning. Here are some of the key learnings:
YOLOv8 Implementation: I gained proficiency in implementing the YOLOv8 object detection algorithm, which is renowned for its speed and accuracy in detecting objects in images and videos. Understanding the architecture and workflow of YOLOv8 was instrumental in developing an efficient solution for detecting scratches and damages on cars.
Data Labeling: One of the critical aspects of this project was manually labeling the data for training the YOLOv8 model. Through this process, I learned how to accurately annotate images or video frames by marking bounding boxes around areas of interest, such as scratches and damages on different parts of the car. This hands-on experience enhanced my understanding of data preparation and annotation techniques, crucial for training robust deep-learning models
YOLOv8 Implementation: I gained proficiency in implementing the YOLOv8 object detection algorithm, which is renowned for its speed and accuracy in detecting objects in images and videos. Understanding the architecture and workflow of YOLOv8 was instrumental in developing an efficient solution for detecting scratches and damages on cars.
Data Labeling: One of the critical aspects of this project was manually labeling the data for training the YOLOv8 model. Through this process, I learned how to accurately annotate images or video frames by marking bounding boxes around areas of interest, such as scratches and damages on different parts of the car. This hands-on experience enhanced my understanding of data preparation and annotation techniques, crucial for training robust deep-learning models
AI Development Type
Deep LearningAI Tools
Keras, OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$60
|
Standard
$120
|
Advanced
$150
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 6 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | |||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | - |
Model Documentation | - | - | |
Ontology | - | - | - |
Source Code | |||
Taxonomy | - | - | - |
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Fast Delivery
+$10 - $30About Muhammad
Web Scrapping and Data Visualization in Python
Multan, Pakistan - 12:53 pm local time
I am passionate about using data to solve complex problems, and I believe that data-driven insights can have a significant impact on decision-making.
As a data scientist, I bring a combination of technical skills and business acumen to the table. I am proficient in programming languages such as Python and the framework of Python like, tensorflow , pandas , numpy , matplotlib , keras, beautifulsoup, and selenium. In addition to I have experience with a range of data analysis and visualization tools. Additionally, I have excellent communication skills and am comfortable working with cross-functional teams to translate technical findings into actionable insights.
I am excited about the opportunity to leverage my skills and experience to help businesses and organizations make data-driven decisions and achieve their goals.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Data gathering or understanding
First step will be to analyze the data and find the pattern in it to make a deep learning model. Then after that data will be pre-processed and split into training and validation parts. In last the model will be defined and training will begin.