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Title: Custom Object Detection Using YOLOv7 with Roboflow and Google Colab

Course Description:

This practical course is designed for individuals eager to dive into the world of custom object detection using YOLOv7. We’ll guide you through the process of creating and training a YOLOv7 model using the Roboflow platform for dataset management and Google Colab for GPU-accelerated model training.

Key Learning Objectives:

  1. Introduction to YOLOv7 and Roboflow:

  2. Setting Up Roboflow Account:

  3. Uploading and Annotating Datasets:

  4. Generating YOLO-Compatible Dataset:

  5. Exporting Datasets to Google Colab:

  6. Installing YOLOv7 on Colab:

  7. Custom Configuration for YOLOv7:

  8. Training YOLOv7 on GPU:

  9. Model Evaluation and Export:

  10. Inference and Object Detection Testing:

  11. Fine-Tuning and Iterative Training:

  12. Project Deployment:


Participants are expected to have:

  • Basic programming skills in Python.

  • Familiarity with machine learning concepts.

  • A Google account for accessing Google Colab.

Who Should Attend:

  • 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.

Materials Needed:

  • A computer with internet access.

  • Google account for Colab access.

  • Roboflow account (free tier available).


Participants will be assessed based on the successful completion of hands-on assignments, including dataset preparation, model training, and inference tasks.

Join us on this practical journey and empower yourself to create custom object detection solutions using YOLOv7 with the help of Roboflow and Google Colab

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