Build your OBJECT DETECTION project, even though you're starting from scratch.

Let me introduce you to the Object Detection (Opencv + Deep learning) course,

the videocourse which will help you to build your Object detection project.

You need to work on an

Object Detection project and

you don't know where to start ...

I know how it feels! When you look for "Object detection" on Google you get simply overwhelmed by the amount of information you find: Yolo, tensorflow, keras, Opencv. And then Pytorch, caffe, SSD, R-CNN just to name a few.

If you are lucky, someone else before you did a really similar project to what you want to develop, but ... when you download the source code simply you are not able to run it, and now the search of a solution for your project turns into disperate attempts to solve the countless errors that the terminal is printing.

If you're able to finally run it, then how to make the small changes that you need to adapt that code for your project when the source code is hundreds of lines which make no sense to you and you have no clue of how it even works?

Does "Object detection" really need to be that complicated?

The biggest goal of this videocourse is to get your hands on Object Detection as quickly as possible to work on your project, no matter what's your experience.

it doesn't need to be that complicated

When you're working on a project and you have a deadline, there is nothing worse than spending a lot of time solving a specific task, just to find out at the end that it doesn't work. And it gets even worse if you have no idea how to move on from there.

Do you need to keep trying or is it better to look for another solution?

On the internet there are a lot of great resources about "Object detection". Many of them are written by researchers and qualified developers who explain pros, cons and progresses of certain algorithms. If you know the bigger picture, these articles are awesome resources, but if you don't, you'll most likely feel lost.

How do you know which one is the right approach for you?

What if your project does require a different solution?

You can MASTER object detection

What if you knew right away which "Object detection" method is right for your project?

What if you could simply install the libraries and focus on your project instead of debugging errors?

What if you knew how it works and you could adjust the project for your need?

What if you had a solution to finally complete your project?

How this course can help you?

This course is focused to teach you the proper way to implement Object Detection on your project.

You will learn 4 different Object Detection methods
You will learn how to choose the right method for you
You will learn how to build a project from scratch
You will learn the basic concepts of Object detection with Deep Learning
You will learn how easily install the libraries

Yo will learn to use Deep learning with YOLO v4
You will learn the fastest way to create a dataset of 1000+ images
You will learn how to train your own custom object detector
You will learn how to train YOLO to detect multiple objects
You will learn how to use Deep Learnign with your GPU

And much more ...

Course Modules

Object Detection with OPENCV´╗┐


On the first module you learn 4 different object detection methods using the Opencv library.

You will learn:

  • How to detect objects from a stable camera
  • How to Detect objects by their color
  • How to Detect similar Objects by comparing their features

Object Detection with

Deep Learning (YOLO v4)

*Available from 10th of October 2020


The second module introduces you to deep learning with YOLO.

You will learn:

  • What is yolo and how it works
  • The fastest way to run YOLO
  • How to train yolo to detect Multiple custom objects
  • How to run YOLO on your GPU
  • How to create your own dataset with 1000+ images
  • How to solve the most common errors (cuda out of memory, you can't detect your objects, ...)
  • and more ...

2 Projects: Object Counter and Object Tracker*

*Available from 30th of October 2020


In this module we will develop 2 projects. A car counter on the High way, and a billard ball tracker.

You will learn:

  • How to count moving objects
  • How to calculate and draw the trajectory of an object

You will get also 2 BONUSES*:

*Available from 20 October 2020

#1 Deploy Tiny YOLO on Raspberry Pi

  • Quick way to install Python, Opencv and Tiny Yolo
  • Run TINY YOLO on your Raspberry PI
  • and more ...

#2 Deploy YOLO v4 on Jetson Nano

Run YOLO v4 on Nvidia Jetson Nano with GPU

  • Low FPS? How to increase the speed
  • and more ...
  • $299.00
  • 7+ hours of content
  • Step by step instructions
  • BONUS: deploy YOLO on Raspberry Pi and Jetson Nano
  • Source Code and Google Colab Notebooks
  • 30 Day Money Back Guarantee

Who am I?

Hi there,

I'm Sergio and I'm the instructor in this course.

In the past 3 years I've been teaching and working on different Computer Vision projects.

You can get a proof of my dedication by taking a look at my youtube channel (Pysource) where you'll find more than 100 free video tutorials with related blog post and source code.

My videos are watched by tens of thousands of people each month.

The idea to build this course came from the need to help as many students as possible with their Object Detection projects.


This course is for you if:

You are a student and you need to develop a project for your studies
You need a pratical approach to Object Detection
You want to build an Object Detection prototype

This course is NOT for you if:

You're just looking for a quick solution and you want to copy/paste the source code without putting the work.
You want to develop an advanced object detection/tracking system for industrial use.

What does happen once I buy this course?

You will get an email with the access details to the videocourse.
You pay just once but you will have lifetime access to the course.

Do I need to know programming?

A basic knowledge of Python programming is required, so you need at least to be familiar with variables, comparison operators and while and for loops.

*** Important Notes ***:

  • Module 2 is going to be fully released the 10th of October, the Bonuses the 20th of October and Module 3 the 30th of October.

  • If you want to work with Deep learning to create custom object detectors, a PC/Laptop with a GPU Nvidia GTX 1050 (with 4gb of ram) or above is recommended. As an alternative you can use external services like Google Colab.

Have you got any question?

Feel free to email me at [email protected]

30 Day Money back Guarantee

I'm so confident about the quality of this videocourse and that you'll be able to get advantage from it that I offer you a 30 day full money back guarantee.

Go through the course, follow all the steps and put in the work. If you think that you're not improving your skills and not getting any benefit from it, then you can send me an email and I'll refund you immediately.


  • $299.00
  • 7+ hours of content
  • Step by step instructions
  • BONUS: deploy YOLO on Raspberry Pi and Jetson Nano
  • Source Code and Google Colab Notebooks
  • 30 Day Money Back Guarantee