Python Computer Vision Bootcamp: Object Detection with YOLO

Install Python on Windows by downloading from the official Python site, running the installer, and verifying with a hello world program.

Learn to install Jupyter Notebook on Windows using Anaconda, set up the Anaconda environment, launch Jupyter through Anaconda Navigator, and run a hello world Python snippet.

Master Python variable rules: names cannot start with a number, are case sensitive, and use underscores for multiword names.

Create a list with mixed data types (string, float, integer), access and print elements by index, modify values, and use list methods such as append and clear; lists are changeable.

Learn about boolean logical data types in Python, creating boolean variables, true and false values, and using the bool function to test truth with non-empty vs empty lists.

Explore conditional structures in Python, learning how the if condition controls statement execution based on a true condition, using indentation and basic syntax.

Return multiple data from a single function by using comma-separated values, returning the addition and multiplication results from two parameters.

Master image resizing with the cv2 resize function by loading an image with imread, applying a width-height tuple, and viewing results in original and resized windows via imshow and waitKey.

Convert an image to gray using the cvtColor function in Python OpenCV, reading with imread, converting BGR to gray, and displaying the original and gray images with imshow and waitKey.

Learn how to convert an image to HSV color format using OpenCV, enabling color tracking and saturation analysis with cv2.cvtColor and COLOR_BGR2HSV.

Learn how to convert a color image to grayscale and then to binary using cv2 threshold, highlighting single channel, 8-bit images, and the display of original and binary results.

Learn how the canny edge algorithm detects edges in images using OpenCV, including grayscale conversion, threshold tuning, and displaying original and canny images.

Apply a Gaussian filter with OpenCV to blur images using the GaussianBlur function, selecting odd kernel sizes and sigma values, and compare the original with the blurred result.

Learn how to reduce image noise with the median filter in Python using OpenCV, applying a kernel size and displaying original and filtered images with imshow.

Create a put text function that draws an optional border around a rectangle and overlays text on an image using OpenCV. Return the updated image and the rectangle coordinates.

Learn to create training, validation, and test folders using the OS module, with structured YOLO and Pascal VOC formats, including images and labels.

Save images and labels only when a set number of objects are detected, using time-based filenames and YOLO-formatted labels with OpenCV.

Implement a while true loop to continuously capture camera frames, apply YOLO car detection, compute parking occupancy, overlay available spaces, and display results until ESC is pressed.