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1. Fun camera apps for computer how to#
2. Fun camera apps for computer software#
3. Fun camera apps for computer download#

Detect Colours in Imagesĭetecting colors in images is a crucial part of computer vision.

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This way, you’d have a working software solution that can perform image classification on desired datasets. You should be familiar with Python’s Tkinter library to build the GUI. The GUI (graphical user interface) would allow a user to feed images into the model’s test dataset for analysis. To make this project more challenging, you can add a GUI to your solution.

Fun camera apps for computer how to#

Working on this project will help you explore their features and functionalities.įYI: Free nlp course ! How to Make the Project More Challenging You’d also get to use TensorFlow and Keras, two of the industry’s most prominent AI tools. That’s because it is present in the datasets module.īy working on this project, you’ll learn a lot about image classification.

Fun camera apps for computer download#

You won’t have to download the CIFAR-10 dataset separately if you have Keras already.

You’d have to build a convolutional neural network through Keras for completing this project. Image classification focuses on separating the pixels of a picture according to the classes they belong to. The photos present in this dataset are of relatively low resolution, so you can test out multiple algorithms without facing technical issues. It has more than 60,000 pictures with ten target classes.Įvery target class has 6,000 images. You can use the CIFAR-10 dataset to perform image classification. To work on this project, you should be familiar with Python, Keras, and TensorFlow. Image classification is a prominent deep learning application of computer vision. Learn: Tensorflow 2.0 Image Classification 4. You can train your models with the Open Images Dataset. It has object bounding boxes, visual relationships, labels annotations, and many things that make it perfect for any computer vision enthusiast. The photos are of various types, and many even have complex scenes of multiple objects. It’s a collection of around nine million different images containing rich annotations. If you are a beginner and haven’t worked on image processing projects before, you should get familiar with Google’s Open Images Dataset. Practice Object Recognition with the Open Images Dataset Join the ML Course online from the World’s top Universities – Masters, Executive Post Graduate Programs, and Advanced Certificate Program in ML & AI to fast-track your career. There would be a certain quantity of people beyond which it would be improbable to have proper social distancing followed. For example, create a solution that counts the number of people present in a public place to enforce social distancing rules. If you want to make this project more complicated or advanced, you can add more functionalities. As a beginner, you should first start with a simple people measuring model that can count the number of people present in a picture. You can use OpenCV and Python to build a model for calculating the total number of people present in a picture.Ī people counting solution can be instrumental in the current world where social distancing is vital for survival. With the recent pandemic, the value of people counting solutions increased substantially. People counting is a prominent application of computer vision technology.

For that, you’d have to train the model with a custom dataset of the people’s images you want the model to recognize. This means the model should recognize the person present in the picture. On the other hand, you can teach your model to recognize people in group photos. You can develop a model that identifies faces in videos.