CV Hands On

 

Computer Vision (CV) Hands On

  1. Object Detection with YOLO: Use a pre-trained YOLO (You Only Look Once) model to detect multiple objects in a single image or a video stream.

  2. Lane Line Detection: Create a program that can detect lane lines in a video feed, a foundational task for self-driving cars.

  3. Face Detection and Recognition: Build an app that can detect faces in an image and then recognize them based on a pre-trained face dataset.

  4. Image Segmentation: Develop a model that can classify each pixel in an image to belong to a certain class (e.g., car, pedestrian, road).

  5. Real-Time Object Counter: Create a program that counts the number of specific objects (e.g., cars, people) in a video.

  6. Image Captioning: Combine a CNN with an RNN to generate a natural language description for a given image.

  7. Simple Augmented Reality (AR) App: Use a library like OpenCV to overlay a 3D object onto a specific marker in a video feed.

  8. Visual Search Engine: Create a system where a user can upload an image and the program will find other similar images from a database.

  9. Pose Estimation: Use a pre-trained model (like OpenPose or MediaPipe) to detect and track the body posture of a person in an image or video.

  10. Optical Character Recognition (OCR): Build a model to read and convert text from images into machine-encoded text.

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