Master ImageNet Models for Classification in TensorFlow & Keras

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In this computer vision tutorial video, we will teach you how to perform image classification using pre-trained ImageNet models. While we previously learned how to train a basic neural network to classify images from the CIFAR-10 dataset, that was a relatively easy task as there were only ten classes.

On the contrary, classifying a larger number of object types will necessitate much larger networks with millions of parameters. Fortunately, pre-trained models are accessible in Keras via the ImageNet project, which have been trained to recognize objects from 1,000 different classes. With just a few lines of code, we can employ these pre-trained models for image classification without any training.

Topics Covered
✅ImageNet and ILSVRC
✅Pre-Trained Models in Keras
✅Read and Display Sample Images
✅Pre-Trained Model Setup
✅Make Predictions using the Pre-Trained Models

❓FAQ on Keras/TensorFlow
What are pre-trained ImageNet models in TensorFlow and Keras?
How do I install TensorFlow and Keras for image classification tasks?
What are the popular pre-trained models available for image classification?
How can I load a pre-trained ImageNet model using TensorFlow and Keras?
How do I preprocess input images for the pre-trained ImageNet models?
Can I fine-tune a pre-trained ImageNet model for my specific classification task?
How do I replace the top layers of a pre-trained model to adapt it to my dataset?
What is transfer learning and how does it relate to pre-trained ImageNet models?
How do I train a fine-tuned model with my custom dataset?
How can I evaluate the performance of my image classifier using pre-trained ImageNet models?
What are some common issues and solutions when working with pre-trained ImageNet models?
How can I optimize my image classifier for better performance and efficiency?
Are there any limitations or drawbacks of using pre-trained ImageNet models for image classification tasks?
How do I save and load my fine-tuned model for future use?
Can I use pre-trained ImageNet models for tasks other than image classification, like object detection or segmentation?

⭐️ Time Stamps:⭐️
00:00-00:48: Introduction
00:48-01:36: ImageNet & ILSVRC
01:36-02:11: Keras 2.11
02:11-03:25: API in Keras
03:25-04:10: Preprocess
04:10-05:15: Batch Dimension
05:15-06:00: Predict Method
06:00-07:02: Reading & Displaying Images
07:02-07:20: Loading Models
07:20-10:01: Convenience Functions
10:01-11:23: Making Predictions
11:23-11:50: Resnet-50
11:50-13:57: Inception-V3
13:57-14:18: Conclusion

Resources:
🖥️ On our blog - https://learnopencv.com we also share tutorials and code on topics like Image
Processing, Image Classification, Object Detection, Face Detection, Face Recognition, YOLO, Segmentation, Pose Estimation, and many more using OpenCV(Python/C++), PyTorch, and TensorFlow.

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