foobar167 / junkyard

Collection of test files, probes, hacks and ideas

Python collection of tests, probes, hacks and ideas

1. PyTorch Tutorial
2. Object tracking
3. Python notes and links to interesting places
4. Image Processing with Python
5. General object classifier
6. OpenCV Filtering GUI
7. Sending emails with Python
8. Manual image annotation with polygons
9. Manual image annotation with rectangles
10. Image viewer
11. Advanced zoom
12. C extension for Python
13. OpenCV + Tkinter snapshot GUI
14. OpenCV features
15. Multilanguage for Python
16. Dynamic menu
17. Rolling window on NumPy arrays
18. Tkinter progressbar

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Coral TPU

Python scripts for Google Coral USB Accelerator.

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PyTorch Tutorial

PyTorch tutorial with Aladdin Persson in Google CoLab. In this folder are Jupyter *.ipynb copies. Here is the online CoLab replica of this original course.

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Object tracking

Object tracking using OpenCV feature detectors (detectors) and descriptor extractors (descriptors) algorithms with GUI for fun, tests and education.

Previous simple script is here SIFT object tracking. SIFT algorithm became free since March 2020.

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Python notes and links to interesting places

Bookmarks to remember and re-visit.

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Image Processing with Python

My replica of this original course: Image Processing with Python.

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General object classifier

Classifies 3 types of bears: bronw, black and teddy bear.

Object classifier is based on:

• Python and fast.ai for model training through deep learning;
• Render cloud provider to deploy your code in web.
• Flutter mobile development framework with a single code base for Android and iOS applications;
• Firebase for Google Analytics.

And consists of 3 components:

1. model training script - Jupyter (Colab) script to train a classification model.
2. web app - starter project to deploy a trained classification model to the web.
3. mobile app - mobile application which connect your web app with mobile phone (tested for Android).

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OpenCV Filtering GUI

OpenCV Filtering GUI is a set of various realtime filters to process images from the webcam. This GUI is based on the previous OpenCV features demo with enhanced Tkinter controls for user-friendly OpenCV real-time filters demonstration.

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Sending emails with Python

Sending emails with Python.

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Manual image annotation with polygons

Manual image annotation opens image where user can select polygon areas around the objects of interest. After selecting region of interest user presses menu button and program cuts rectangular images from selected polygons with a scanning window.

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Manual image annotation with rectangles

Manual image annotation creates rectangular images with selected areas of interest (ROI). User opens image and selects rectangular areas of interest. After selecting rectangles and pressing menu button program cuts rectangle images from the bigger image.

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Image viewer

Image viewer shows image and prints coordinates of the rectangular area in the console.

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Advanced zoom

Advanced zoom for images of various formats and sizes from small to huge up to several GB.

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C extension for Python

C language extension for Python language by example of co-occurrence matrix calculation.

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OpenCV + Tkinter snapshot GUI

Take shapshot using webcamera, OpenCV and Tkinter. Example is well documented and has many comments inside.

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OpenCV features

Demo of various OpenCV features. Application is tested for Windows OS and requires webcam. There is a newer version with GUI.

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Multilanguage for Python

How-to implement multilanguage for Python.

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Dynamic menu

Example of the dynamic menu for Tkinter GUI.

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Rolling window on NumPy arrays

General examples for 1D, 2D, 3D and MD rolling window arrays in the on-line CoLab notebook.

It has zero Python cycles inside, so the speed is the same as in C programming language.

My previous examples of the rolling window for 2D array are here and here.

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Tkinter progressbar

Example of the Tkinter progressbar GUI.

junkyard's Issues

Will this be able to handle images of 10-15 GB?

Hi there,

The codes you have provided for zooming are extremely educational for a newbie like me. Thanks for uploading them.

I'm trying to work on a flexible zoom viewer on python 2.7 for reading TIFF images around the size of 15GB. Can your code (zoom_huge_python2.7.py) be able to handle such huge images?

How to initialize the image size with the outer frame.

Creating a new rectangle on the Canvas, if image is resized, the rectangle gets drawn in the wrong position

I'm basically trying to draw a new rectangle on top of the CanvasImage class, the coordinates of the rectangle are coming from a cv2.selectROI of the same image, if I don't zoom in/out, the rectangle is done correctly.

Is there any chance this could be implemented?