RMagick
ONNX-YOLOv7-Object-Detection
RMagick | ONNX-YOLOv7-Object-Detection | |
---|---|---|
6 | 2 | |
693 | 182 | |
0.4% | - | |
9.3 | 0.0 | |
4 days ago | about 1 year ago | |
C++ | Python | |
MIT License | MIT License |
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RMagick
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How to use ImageMagick in AWS Lambda (ruby 2.7) with WebP support
require 'rmagick' include Magick module LambdaFunction class Handler def self.process(event:, context:) image_url = event['image_url'] my_image = ImageList.new(image_url) # TODO: Use rmagick to make your image transformations # Docs: https://rmagick.github.io { "success": true } end end end
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YOLOv7 object detection in Ruby in 10 minutes
mini_magick is much slower than YOLO. I hear that rmagick is well maintained these days, so you may want to use that.
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Building a Dot Matrix Animator
To accomplish this project, I knew I would need some way to process the input images. Resizing the images was the easy bit. The more complex (and more important) task was to find the best way to relate a pixel's color in the source image to a dot's size in final animation. I felt that the relative luminance as described in this W3 accessibility document was a logical property to use in this case, and can be easily calculated with a color's RGB components. After determining what tasks I needed to fulfill, I determined that the RMagick library would be a good choice for this project.
- API to create an image (with text/details) and display it
- Is there a gem/way to edit an image with custom text
ONNX-YOLOv7-Object-Detection
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[D] Extracting the class labels and bounding boxes for objects, from a YOLO7 model after converting to an ONNX model
Finally, I tried to look if someone has done similar work for the ONNX model and I found this repo which links the same repo I am trying to use, and I believe this function is doing exactly what I want to do, but I could not understand what it is doing (I don't understand how it knows exactly where the number of detections is, and where the bounding boxes are and the class labels, etc.) furthermore, I am not sure if removing end2end and the changing the version from 12 to 9 has any effect on the output shape or it has to do with the internal layers.
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YOLOv7 object detection in Ruby in 10 minutes
git clone https://github.com/ibaiGorordo/ONNX-YOLOv7-Object-Detection.git cd ONNX-YOLOv7-Object-Detection pip install -r requirements.txt
What are some alternatives?
MiniMagick - mini replacement for RMagick
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
ruby-vips - Ruby extension for the libvips image processing library.
netron - Visualizer for neural network, deep learning and machine learning models
IMGKit - Uses wkhtmltoimage to create JPGs and PNGs from HTML
onnxruntime-ruby - Run ONNX models in Ruby
PSD.rb - Parse Photoshop files in Ruby with ease
models - A collection of pre-trained, state-of-the-art models in the ONNX format
Phashion - Ruby wrapper around pHash, the perceptual hash library for detecting duplicate multimedia files
AS-One - Easy & Modular Computer Vision Detectors and Trackers - Run YOLO-NAS,v8,v7,v6,v5,R,X in under 20 lines of code.
Skeptick - Better ImageMagick for Ruby
blink-morse - Computer vision application to type based on detection of eyes blinking morse code.