Course Overview
- Course Title: Complete Object Detection Using YOLOv7 Project From Scratch
- Instructor: ARUNNACHALAM SHANMUGARAAJAN
- Target Audience:
- Students and professionals interested in computer vision and object detection
- Data scientists and machine learning practitioners
- Individuals wanting hands-on experience with YOLOv7, Roboflow, and Google Colab
- Prerequisites:
- Basic programming skills in Python
- Familiarity with machine learning concepts
- A Google account for accessing Google Colab
- Account In Roboflow Website and Google Colab Website
Curriculum Highlights
- Key Topics Covered:
- Introduction to YOLOv7 and Roboflow
- Setting Up Roboflow Account
- Uploading and Annotating Datasets
- Generating YOLO-Compatible Dataset
- Exporting Datasets to Google Colab
- Installing YOLOv7 on Colab
- Custom Configuration for YOLOv7
- Training YOLOv7 on GPU
- Model Evaluation and Export
- Inference and Object Detection Testing
- Fine-Tuning and Iterative Training
- Project Deployment
- Key Skills Learned:
- Understanding the basics of Roboflow website and Google Colab
- Understanding the basics of object detection
- Training the YOLOv7 model on the custom dataset
- Learning about hyperparameters and monitoring the training process
- Understanding the importance of labeled datasets
- Learning how to annotate images to train a YOLOv7 model
Course Format
- Duration:
- 1 hour on-demand video
- 1 article
- Format: Self-paced online course
- Resources:
- Access on mobile and TV
- Certificate of completion