How to do machine vision development in PHP?

Machine vision is one of the popular technical fields in recent years, covering many directions such as image processing, computer vision and deep learning. In PHP, we can use some open source libraries and tools to develop machine vision. Here are some basic methods and tools for reference.

1. Image processing

Image processing is the basis of machine vision, which covers many aspects such as image reading, conversion, processing and saving. In PHP, we can use the GD library for image processing. The GD library is a PHP extension with many common functions that can be used to create images in JPEG, PNG, and GIF formats, as well as process and convert these images.

Using the GD library, we can perform operations such as image scaling, cropping, filtering, rotation, watermarking, and text addition. For example, the following code can scale a PNG format image to a specified size and save it as a JPEG format:

$img = imagecreatefrompng('example.png');
$width = imagesx($img);
$height = imagesy($img);
$newImg = imagecreatetruecolor(200, 200);
imagecopyresampled($newImg, $img, 0, 0, 0, 0, 200, 200, $width, $height);
imagejpeg($newImg, 'example.jpg', 90);
imagedestroy($img);
imagedestroy($newImg);

2. Computer Vision

Computer vision is the advancement of machine vision It covers multiple directions such as image recognition, target detection, face recognition, text recognition and image segmentation. In PHP, we can use the OpenCV library for computer vision development. OpenCV is a cross-platform computer vision library that supports multiple programming languages ​​such as C, Python and Java, and can also be called through PHP extensions.

Using the OpenCV library, we can perform image filtering, edge detection, histogram equalization, color space conversion, feature extraction and other operations. For example, the following code can read a JPEG format image, perform grayscale processing, and display the original image and the processed image:

$img = cvimread('example.jpg', cvIMREAD_COLOR);
$grayImg = cvcvtColor($img, $grayImg, cvCOLOR_BGR2GRAY);
cvimshow('Original Image', $img);
cvimshow('Grayscale Image', $grayImg);
cvwaitKey();
cvdestroyAllWindows();

3. deep learning

Deep learning is the cutting-edge field of machine vision, which covers various models such as neural networks, convolutional neural networks and recurrent neural networks. In PHP, we can use deep learning frameworks such as TensorFlow or Keras for deep learning development. These frameworks usually support programming languages ​​​​such as Python and C, and can also be called through PHP extensions.

Using the deep learning framework, we can perform operations such as image classification, target detection, face recognition, and image generation. For example, the following code can read a JPEG format picture, use the Keras framework for target detection, detect and display the position of the face:

$model = kerasmodelsload_model('model.h5');
$img = cvimread('example.jpg', cvIMREAD_COLOR);
$width = imagesx($img);
$height = imagesy($img);
$blob = new cvMat(cvdnnlobFromImage($img, 1/255, new cvSize(300, 300), new cvScalar(), true, false));
$model->setInput($blob, 'data');
$result = $model->predict([])['detection_out'][0][0];
$x1 = $result[3] * $width;
$y1 = $result[4] * $height;
$x2 = $result[5] * $width;
$y2 = $result[6] * $height;
img = cvectangle($img, new cvPoint($x1, $y1), new cvPoint($x2, $y2), new cvScalar(0, 0, 255), 2);
cvimshow('Detected Faces', $img);
cvwaitKey();
cvdestroyAllWindows();

In summary, the development of machine vision in PHP involves to image processing, computer vision and deep learning. By using relevant tools and libraries, we can read, convert, process and save images, and perform various operations such as image recognition, target detection, face recognition and image generation. With the further development of machine vision technology, I believe that machine vision development in PHP will become more and more convenient and abundant.

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