Deep Learning with OpenCV DNN Module | Full Course | 3 hours

Опубликовано: 12 Июнь 2026
на канале: Bleed AI Academy
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This is the most detailed course on Deep Learning using OpenCV’s DNN module out there, yes a complete 3-hour course that takes you from no background in DNN module, and teaches you all about it, including how to train custom classifiers and custom object detectors in TensorFlow and then deploy it in OpenCV module. You’ll also learn all the nitty-gritty details about this module in the course.

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00:00 Intro

01:08 Introduction to OpenCV's Deep Neural Network Module

01:45 What are the Benefits

03:39 A Bummer that You Must Know About

04:01 So Which Frameworks can be Used to Train Neural Networks?

05:22 Section 1 - Image Classification with DenseNet121

06:04 Import the Libraries

06:15 Load the Class Labels

08:05 Extract the Label

08:36 Initialize the DNN Module

11:48 Read an Image

12:19 Pre-process an Image

18:53 Input the Blob Image to the Network

19:12 Forward Pass

21:48 Apply Softmax Function to get Probabilities

25:27 Create Functions

26:57 Initialization Function

28:05 Classification Function

29:31 Initialize the Classifier

29:34 Classify Images Using the Function

30:12 Perform Real-Time Image Classification

32:55 Important Details Regarding the DNN Module

37:49 Section 2 - Training Custom Image Classifier with Tensorflow, Converting to ONNX and using it in OpenCV DNN module

38:48 (Part 1) Training a Custom Image Classifier with Tensorflow

38:51 Import the Libraries

42:07 Download and Unzip the Dataset folder

43:52 Check the number of images in each class

45:19 Generate Images

01:01:10 Visualize Images

01:04:11 Create the model

01:11:11 compile the model

01:11:13 Model Summary

01:19:28 Train The Model

01:23:22 Visualize Training Results

01:24:15 Test on new Examples

01:28:33 Save your model to Disk

01:29:29 (Part2) Converting Our Classifier to ONNX format

01:33:16 (Part 3) Using the ONNX model in the OpenCV DNN module

01:38:26 Create Functions

01:38:26 Initialization Function

01:38:36 Classification Function

01:42:32 Section 3 - Training Object Detector with Tensorflow Object Detection API

01:52:02 (Part 1) Environmental Setup

01:52:32 (Part 2) Installation & TFOD API Setup

01:55:11 Import Required Libraries

01:55:29 Clone Tensorflow Object Detection Model Repository

01:57:25 Install Tensorflow Object Detection API & Compile Protos

02:01:16 You can Check your installation of TFOD API by Running model_builder_test.py

02:02:06 Download the Support Folder required to run this Notebook

02:03:05 (Part 3) Data Collection & Annotation

02:04:41 Step 1: Download Youtube Video

02:05:49 Step 2: Split Video Frames and store it

02:12:55 Step 3: Annotate Images with labelImg

02:19:26 Step 4: Create a label Map file

02:21:04 Step 5: Generate TFrecords

02:39:09 (Part 4) Downloading Model & Configure it

02:39:09 (Part 5) Training and Exporting Inference Graph

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#imageclassification #objectdetection #deeplearning #crashcourse #opencv #tensorflow