detect_objects.rb

require "onnxruntime"
require "mini_magick"

img = MiniMagick::Image.open("bears.jpg")
pixels = img.get_pixels

model = OnnxRuntime::Model.new("model.onnx")
result = model.predict({"inputs" => [pixels]})

p result["num_detections"]
p result["detection_classes"]

coco_labels = {
  23 => "bear",
  88 => "teddy bear"
}

def draw_box(img, label, box)
  width, height = img.dimensions

  thickness = 2
  top = (box[0] * height).round - thickness
  left = (box[1] * width).round - thickness
  bottom = (box[2] * height).round + thickness
  right = (box[3] * width).round + thickness

  # draw box
  img.combine_options do |c|
    c.draw "rectangle #{left},#{top} #{right},#{bottom}"
    c.fill "none"
    c.stroke "red"
    c.strokewidth thickness
  end

  # draw text
  img.combine_options do |c|
    c.draw "text #{left},#{top - 5} \"#{label}\""
    c.fill "red"
    c.pointsize 18
  end
end

result["num_detections"].each_with_index do |n, idx|
  n.to_i.times do |i|
    label = result["detection_classes"][idx][i].to_i
    label = coco_labels[label] || label
    box = result["detection_boxes"][idx][i]
    draw_box(img, label, box)
  end
end

img.write("labeled.jpg")

This code snippet isn't working properly as of October 2021. It keeps throwing this error:

in 'predict' : wrong number of arguments (given 0, expected 1) (ArgumentError)

Hey @Ashvith, thanks for reporting! I've updated the gist and post for Ruby 3 and tf2onnx 1.9.

Hey @ankane , I was wondering if this Python code is unneeded, and is it possible to convert the model through Ruby?

python -m tf2onnx.convert --opset 10 --fold_const \
  --saved-model ssd_mobilenet_v1_coco_2018_01_28/saved_model \
  --output model.onnx

I'm not aware of any Ruby libraries that can convert TensorFlow models to ONNX.

Hello @ankane and @Ashvith

I am trying to run this code and getting the following error while running "result = model.predict({"inputs" => [pixels]})"

`block in create_input_tensor': Unknown input: inputs (OnnxRuntime::Error)

Please let me know what am I doing wrong.

Make sure you're using the latest version of tf2onnx to convert the model. Also, the blog post has info on how to check the input names.

great work

Where can I find tf2onnx.convert to create model.onnx?

https://github.com/onnx/tensorflow-onnx