Reimplement new laser point detection method

README.md

@@ -12,25 +12,6 @@ This module is already included in [`biigle/biigle`](https://github.com/biigle/b
 2. Add `Biigle\Modules\Laserpoints\LaserpointsServiceProvider::class` to the `providers` array in `config/app.php`.
 3. Run `php artisan vendor:publish --tag=public` to publish the public assets of this module.
 4. Run `pip install -r vendor/biigle/laserpoints/requirements.txt` to install the Python requirements.
-5. Configure a storage disk for the temporary laserpoints files `LASERPOINTS_DISK` variable to the name of this storage disk in the `.env` file. Example for a local disk:
-    ```php
-    'laserpoints' => [
-        'driver' => 'local',
-        'root' => storage_path('framework/cache/laserpoints'),
-    ],
-    ```
-
-## References
-
-Reference publications that you should cite if you use the laser point detection for one of your studies.
-
-- **BIIGLE 2.0**
-    [Langenkämper, D., Zurowietz, M., Schoening, T., & Nattkemper, T. W. (2017). Biigle 2.0-browsing and annotating large marine image collections.](https://doi.org/10.3389/fmars.2017.00083)
-    Frontiers in Marine Science, 4, 83. doi: `10.3389/fmars.2017.00083`
-
-- **Laser Point Detection**
-    [Schoening, T., Kuhn, T., Bergmann, M., & Nattkemper, T. W. (2015). DELPHI—fast and adaptive computational laser point detection and visual footprint quantification for arbitrary underwater image collections.](https://doi.org/10.3389/fmars.2015.00020)
-    Frontiers in Marine Science, 2, 20. doi: `10.3389/fmars.2015.00020`
 
 ## Developing
 

requirements.txt

@@ -1,3 +1,3 @@
-numpy==1.22.0
-scipy==1.10.0
-Pillow==10.3.0
+numpy==2.1.*
+scipy==1.13.*
+opencv-contrib-python-headless==4.11.0.*

src/Http/Controllers/Api/LaserpointsController.php

@@ -4,96 +4,194 @@
 
 use Biigle\Http\Controllers\Api\Controller;
 use Biigle\Label;
-use Biigle\Modules\Laserpoints\Http\Requests\ComputeImage;
-use Biigle\Modules\Laserpoints\Http\Requests\ComputeVolume;
 use Biigle\Modules\Laserpoints\Image;
-use Biigle\Modules\Laserpoints\Jobs\ProcessImageDelphiJob;
+use Biigle\Modules\Laserpoints\Jobs\ProcessImageAutomaticJob;
 use Biigle\Modules\Laserpoints\Jobs\ProcessImageManualJob;
-use Biigle\Modules\Laserpoints\Jobs\ProcessVolumeDelphiJob;
+use Biigle\Modules\Laserpoints\Jobs\ProcessVolumeAutomaticJob;
+use Biigle\Modules\Laserpoints\Jobs\ProcessVolumeManualJob;
 use Biigle\Modules\Laserpoints\Volume;
-use Biigle\Volume as BaseVolume;
 use Exception;
+use Illuminate\Http\Request;
 use Illuminate\Validation\ValidationException;
 
 class LaserpointsController extends Controller
 {
     /**
-     * Compute distance between laser points for an image.
+     * Compute distance between laser points for an image with manual annotations.
      *
-     * @api {post} images/:id/laserpoints/area Compute image area
+     * @api {post} images/:id/laserpoints/manual Compute image area with manual annotations
      * @apiGroup Images
-     * @apiName ImagesComputeArea
+     * @apiName ImagesComputeAreaManual
      * @apiPermission projectEditor
-     * @apiDescription This feature is not available for very large images.
      *
      * @apiParam {Number} id The image ID.
      * @apiParam (Required arguments) {Number} label_id ID of the laser point label that was used.
      * @apiParam (Required arguments) {Number} distance The distance between two laser points in cm.
      *
-     * @param ComputeImage $request
+     * @param Request $request
+     * @param int $id
      *
      * @return \Illuminate\Http\Response
      */
-    public function computeImage(ComputeImage $request)
+    public function imageManual(Request $request, $id)
     {
-        $image = Image::convert($request->image);
+        $image = Image::with('volume')->findOrFail($id);
+        $this->authorize('edit-in', $image->volume);
+        // TODO manual is possible for tiled images? how does the script get the dimensions? do we need a python script for this at all?
+        if ($image->tiled) {
+            throw ValidationException::withMessages([
+                'id' => 'Laser point detection is not available for very large images.',
+            ]);
+        }
+        $request->validate([
+            'distance' => 'required|numeric|min:1',
+            'label_id' => 'required|integer|exists:labels,id',
+        ]);
+
         $label = Label::find($request->input('label_id'));
 
         try {
-            $manual = $image->readyForManualDetection($label);
+            $image->readyForManualDetection($label);
         } catch (Exception $e) {
             throw ValidationException::withMessages([
                 'id' => 'Laser point detection can\'t be performed. '.$e->getMessage(),
             ]);
         }
 
-        if ($manual) {
-            ProcessImageManualJob::dispatch($image, $request->input('distance'), $label->id)
-                ->onQueue(config('laserpoints.process_manual_queue'));
-        } else {
-            try {
-                Volume::convert($image->volume)->readyForDelphiDetection($label);
-            } catch (Exception $e) {
-                throw ValidationException::withMessages([
-                    'id' => 'Delphi laser point detection can\'t be performed. '.$e->getMessage(),
-                ]);
-            }
-
-            ProcessImageDelphiJob::dispatch($image, $request->input('distance'), $label->id)
-                ->onQueue(config('laserpoints.process_delphi_queue'));
+        ProcessImageManualJob::dispatch($image, $label, $request->input('distance'))
+            ->onQueue(config('laserpoints.process_manual_queue'));
+    }
+
+    /**
+     * Compute distance between laser points for an image with automatic detection.
+     *
+     * @api {post} images/:id/laserpoints/automatic Compute image area with automatic detection
+     * @apiGroup Images
+     * @apiName ImagesComputeAreaAutomatic
+     * @apiPermission projectEditor
+     * @apiDescription This feature is not available for very large images.
+     *
+     * @apiParam {Number} id The image ID.
+     * @apiParam (Required arguments) {Number} distance The distance between two laser points in cm.
+     *
+     * @param Request $request
+     * @param int $id
+     *
+     * @return \Illuminate\Http\Response
+     */
+    public function imageAutomatic(Request $request, $id)
+    {
+        $image = Image::with('volume')->findOrFail($id);
+        $this->authorize('edit-in', $image->volume);
+        if ($image->tiled) {
+            throw ValidationException::withMessages([
+                'id' => 'Laser point detection is not available for very large images.',
+            ]);
         }
+        $request->validate([
+            'distance' => 'required|numeric|min:1',
+        ]);
+
+        ProcessImageAutomaticJob::dispatch($image, $request->input('distance'))
+            ->onQueue(config('laserpoints.process_automatic_queue'));
     }
 
     /**
-     * Compute distance between laser points for a volume.
+     * Compute distance between laser points for a volume with manual annotations.
      *
-     * @api {post} volumes/:id/laserpoints/area Compute image footprint for all images
+     * @api {post} volumes/:id/laserpoints/manual Compute image area with manual annotations
      * @apiGroup Volumes
-     * @apiName VolumesComputeImageArea
+     * @apiName VolumesComputeAreaManual
      * @apiPermission projectEditor
-     * @apiDescription This feature is not available for video volumes and volumes with very large images.
      *
      * @apiParam {Number} id The volume ID.
      * @apiParam (Required arguments) {Number} label_id ID of the laser point label that was used.
      * @apiParam (Required arguments) {Number} distance The distance between two laser points in cm.
      *
-     * @param ComputeVolume $request
+     * @param Request $request
+     * @param int $id
+     *
      * @return \Illuminate\Http\Response
      */
-    public function computeVolume(ComputeVolume $request)
+    public function volumeManual(Request $request, $id)
     {
-        $volume = Volume::convert($request->volume);
+        // TODO use cache key to prevent users from submitting multiple jobs at the same
+        // time
+        $volume = Volume::findOrFail($id);
+        $this->authorize('edit-in', $volume);
+        if (!$volume->isImageVolume()) {
+            throw ValidationException::withMessages([
+                'id' => 'Laser point detection is only available for image volumes.',
+            ]);
+        }
+        // TODO manual is possible for tiled images? how does the script get the dimensions? do we need a python script for this at all?
+        if ($volume->hasTiledImages()) {
+            throw ValidationException::withMessages([
+                'id' => 'Laser point detection is not available for volumes with very large images.',
+            ]);
+        }
+        $request->validate([
+            'distance' => 'required|numeric|min:1',
+            'label_id' => 'required|integer|exists:labels,id',
+        ]);
+
         $label = Label::find($request->input('label_id'));
 
         try {
-            $volume->readyForDelphiDetection($label);
+            $volume->readyForManualDetection($label);
         } catch (Exception $e) {
             throw ValidationException::withMessages([
-                'id' => 'Delphi laser point detection can\'t be performed. '.$e->getMessage(),
+                'id' => 'Laser point detection can\'t be performed. '.$e->getMessage(),
             ]);
         }
 
-        ProcessVolumeDelphiJob::dispatch($volume, $request->input('distance'), $label->id)
-            ->onQueue(config('laserpoints.process_delphi_queue'));
+        ProcessVolumeManualJob::dispatch($volume, $label, $request->input('distance'))
+            ->onQueue(config('laserpoints.process_manual_queue'));
+    }
+
+    /**
+     * Compute distance between laser points for a volume with automatic detection.
+     *
+     * @api {post} volumes/:id/laserpoints/automatic Compute image area with automatic detection
+     * @apiGroup Volumes
+     * @apiName VolumesComputeAreaAutomatic
+     * @apiPermission projectEditor
+     * @apiDescription This feature is not available for video volumes and volumes with very large images.
+     *
+     * @apiParam {Number} id The image ID.
+     * @apiParam (Required arguments) {Number} distance The distance between two laser points in cm.
+     * @apiParam (Optional arguments) {boolean} disable_line_detection Set to true if the laser pointers can move relative to the camera (e.g. laser points could move even if the vehicle does not move).
+     *
+     * @param Request $request
+     * @param int $id
+     *
+     * @return \Illuminate\Http\Response
+     */
+    public function volumeAutomatic(Request $request, $id)
+    {
+        // TODO use cache key to track which image job should delete cache data
+        // and to prevent users from submitting multiple jobs at the same time
+        $volume = Volume::findOrFail($id);
+        $this->authorize('edit-in', $volume);
+
+        if (!$volume->isImageVolume()) {
+            throw ValidationException::withMessages([
+                'id' => 'Laser point detection is only available for image volumes.',
+            ]);
+        }
+
+        if ($volume->hasTiledImages()) {
+            throw ValidationException::withMessages([
+                'id' => 'Laser point detection is not available for volumes with very large images.',
+            ]);
+        }
+
+        $request->validate([
+            'distance' => 'required|numeric|min:1',
+            'disable_line_detection' => 'boolean',
+        ]);
+
+        ProcessVolumeAutomaticJob::dispatch($volume, $request->input('distance'), $request->input('disable_line_detection', false))
+            ->onQueue(config('laserpoints.process_automatic_queue'));
     }
 }