Here is easy steps to try Windows 10 on ARM or Ubuntu for ARM64 on your Apple Silicon Mac. Enjoy!
NOTE: that this is current, 10/1/2021 state.
- Install Xcode from App Store or install Command Line Tools on your Mac
| # .bashrc | |
| # Source global definitions | |
| if [ -f /etc/bashrc ]; then | |
| . /etc/bashrc | |
| fi | |
| # Uncomment the following line if you don't like systemctl's auto-paging feature: | |
| # export SYSTEMD_PAGER= |
Here is easy steps to try Windows 10 on ARM or Ubuntu for ARM64 on your Apple Silicon Mac. Enjoy!
NOTE: that this is current, 10/1/2021 state.
| #!/usr/bin/env bash | |
| # | |
| # Certbot Nginx Reload | |
| # | |
| # Let's Encrypt Certbot post hook command for Nginx which checks the updated | |
| # configuration files and reloads the server if everything validates. | |
| # | |
| # Author : Justin Hartman <[email protected]> | |
| # Version : 1.0.1 | |
| # License : MIT <https://opensource.org/licenses/MIT> |
| /***************************************************************************************** | |
| * Accesses a variable inside of .env file and cache for later usage; throws an error if its not found. | |
| * | |
| * caching the values to improve the performance. | |
| * | |
| * Usage: | |
| * | |
| * import accessEnv from "helpers/accessEnv"; | |
| * | |
| * const redirectionHost = accessEnv("MAJOR_VERSION", 1); |
Lima (Linux virtual machines, on macOS) installation guide for M1 Mac.
Sep. 27th 2021 UPDATED
Now we can install patched version of QEMU via Homebrew (thank you everyone for the info!). Here is the updated instruction with it:
Used M1 Mac mini 2020 with macOS Big Sur Version 11.6.
This Python script leverages the OpenCV library for face detection and the PIL (Pillow) library for image processing to detect and crop a human head in an image. The detect_and_crop_head function takes an input image file, detects the face using a pre-trained Haar Cascade classifier, and crops the image to include the entire head with a 1:1 aspect ratio. The cropping is achieved by specifying a factor that determines the size of the cropped region around the detected face. Adjust the factor parameter based on the specific requirements of your images.
input_image_path = "path/to/your/input/image.jpg"
output_image_path = "path/to/save/cropped/head.jpg"
detect_and_crop_head(input_image_path, output_image_path, factor=1.5)