Add automatic saliency cropping

.gitattributes

@@ -0,0 +1 @@
+resources/models/*.onnx filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -1,4 +1,6 @@
 /vendor/
+/.transformers-cache/
+/examples/focus-crop/
 /.vscode/
 .phpunit.result.cache
 .idea

README.md

@@ -29,6 +29,11 @@ $target = 'image_100x100.jpg';
 $image->crop(100, 100, Image::GRAVITY_TOP_LEFT);
 $image->save($target, 'jpg', 100);
 
+//automatically keep salient subjects in frame
+$image = new Image(\file_get_contents('image.jpg'));
+$image->crop(400, 300, Image::GRAVITY_AUTO);
+$image->save('automatic.jpg', 'jpg', 100);
+
 $image = new Image(\file_get_contents('image.jpg'));
 $target = 'image_border.jpg';
 $image->setBorder(2, "#ff0000"); //add border 2 px, red
@@ -43,9 +48,52 @@ $image->save($target, 'png', 100);
 
 ```
 
+### Automatic Cropping
+
+Use `Image::GRAVITY_AUTO` to position the crop around the most visually salient parts of an image:
+
+```php
+$image->crop(400, 300, Image::GRAVITY_AUTO);
+```
+
+Automatic cropping uses the bundled full U2NET saliency model. Empty or uniform saliency maps fall back to a centered crop. Applications do not need to download or configure a model.
+
+Detection can run separately in a worker and be stored as JSON. The result contains the normalized saliency mask and its dimensions. Passing it to `crop()` skips model inference in the image worker:
+
+```php
+// Detection worker
+$image = new Image(\file_get_contents('image.jpg'));
+$detectionJson = json_encode($image->detect(), JSON_THROW_ON_ERROR);
+// Store $detectionJson in the database.
+
+// Image worker
+$image = new Image(\file_get_contents('image.jpg'));
+$detection = json_decode($detectionJson, true, flags: JSON_THROW_ON_ERROR);
+$image->crop(400, 300, Image::GRAVITY_AUTO, $detection);
+```
+
+ONNX Runtime is installed per platform. Add its verified download hook to the root `composer.json` of the application using this library:
+
+```json
+{
+    "scripts": {
+        "post-install-cmd": "OnnxRuntime\\Vendor::check",
+        "post-update-cmd": "OnnxRuntime\\Vendor::check"
+    }
+}
+```
+
+Then run:
+
+```bash
+composer install
+```
+
+The provided Linux runtime targets glibc. Alpine and other musl-based systems require a compatible custom ONNX Runtime library.
+
 ## System requirements
 
-Utopia Image requires PHP 8.1 or later. We recommend using the latest PHP version whenever possible.
+Utopia Image requires PHP 8.1 or later with the Imagick, GD, and FFI extensions. We recommend using the latest PHP version whenever possible.
 
 ## Testing
 

composer.json

@@ -16,12 +16,24 @@
         }
     },
     "scripts": {
-        "test": "phpunit --testsuite unit"
+        "lint": "./vendor/bin/pint --test",
+        "format": "./vendor/bin/pint",
+        "check": "./vendor/bin/phpstan analyse --level max src tests --memory-limit=512M",
+        "test": "phpunit --testsuite unit",
+        "post-install-cmd": "OnnxRuntime\\Vendor::check",
+        "post-update-cmd": "OnnxRuntime\\Vendor::check"
     },
     "require": {
         "php": ">=8.1",
+        "ext-ffi": "*",
         "ext-imagick": "*",
-        "ext-gd": "*"
+        "ext-gd": "*",
+        "ankane/onnxruntime": "^0.2.9"
+    },
+    "require-dev": {
+        "phpunit/phpunit": "10.5.*",
+        "phpstan/phpstan": "2.1.*",
+        "laravel/pint": "1.24.*"
     },
     "suggest": {
         "ext-imagick": "Imagick extension is required for Imagick adapter"

resources/models/NOTICE.md

@@ -0,0 +1,14 @@
+# U2NET Model
+
+`u2net.onnx` is an ONNX export of the full U2NET model from the U-2-Net project:
+
+- Source: https://github.com/xuebinqin/U-2-Net
+- ONNX distribution: https://github.com/danielgatis/rembg/releases/download/v0.0.0/u2net.onnx
+- MD5: `60024c5c889badc19c04ad937298a77b`
+- SHA-256: `8d10d2f3bb75ae3b6d527c77944fc5e7dcd94b29809d47a739a7a728a912b491`
+- License: Apache License 2.0
+
+Copyright 2020 Xuebin Qin.
+
+Licensed under the Apache License, Version 2.0. You may obtain a copy at
+https://www.apache.org/licenses/LICENSE-2.0.