split vizModel to a separate file (#5094)

vision.go was super long, and half of it was unrelated to the other half. So, it's now 2 files. This will make it easier to think about fixing RDSK-11093, which is about updating `vision.NewService()` to not use the deprecated constructor.

No changes to functionality are intended: I just took a file and split it in half.

Author: penguinland

services/vision/deprecated_vision_service_builder.go

@@ -0,0 +1,269 @@
+package vision
+
+import (
+	"context"
+	"image"
+
+	"github.com/pkg/errors"
+	"go.opencensus.io/trace"
+
+	"go.viam.com/rdk/components/camera"
+	"go.viam.com/rdk/resource"
+	"go.viam.com/rdk/robot"
+	viz "go.viam.com/rdk/vision"
+	"go.viam.com/rdk/vision/classification"
+	"go.viam.com/rdk/vision/objectdetection"
+	"go.viam.com/rdk/vision/segmentation"
+	"go.viam.com/rdk/vision/viscapture"
+)
+
+// vizModel wraps the vision model with all the service interface methods.
+type vizModel struct {
+	resource.Named
+	resource.AlwaysRebuild
+	r               robot.Robot // in order to get access to all cameras
+	properties      Properties
+	closerFunc      func(ctx context.Context) error // close the underlying model
+	classifierFunc  classification.Classifier
+	detectorFunc    objectdetection.Detector
+	segmenter3DFunc segmentation.Segmenter
+	defaultCamera   string
+}
+
+// NewService wraps the vision model in the struct that fulfills the vision service interface.
+func NewService(
+	name resource.Name,
+	r robot.Robot,
+	c func(ctx context.Context) error,
+	cf classification.Classifier,
+	df objectdetection.Detector,
+	s3f segmentation.Segmenter,
+	defaultCamera string,
+) (Service, error) {
+	if cf == nil && df == nil && s3f == nil {
+		return nil, errors.Errorf(
+			"model %q does not fulfill any method of the vision service. It is neither a detector, nor classifier, nor 3D segmenter", name)
+	}
+
+	p := Properties{false, false, false}
+	if cf != nil {
+		p.ClassificationSupported = true
+	}
+	if df != nil {
+		p.DetectionSupported = true
+	}
+	if s3f != nil {
+		p.ObjectPCDsSupported = true
+	}
+
+	return &vizModel{
+		Named:           name.AsNamed(),
+		r:               r,
+		properties:      p,
+		closerFunc:      c,
+		classifierFunc:  cf,
+		detectorFunc:    df,
+		segmenter3DFunc: s3f,
+		defaultCamera:   defaultCamera,
+	}, nil
+}
+
+// Detections returns the detections of given image if the model implements objectdetector.Detector.
+func (vm *vizModel) Detections(
+	ctx context.Context,
+	img image.Image,
+	extra map[string]interface{},
+) ([]objectdetection.Detection, error) {
+	ctx, span := trace.StartSpan(ctx, "service::vision::Detections::"+vm.Named.Name().String())
+	defer span.End()
+	if vm.detectorFunc == nil {
+		return nil, errors.Errorf("vision model %q does not implement a Detector", vm.Named.Name())
+	}
+	return vm.detectorFunc(ctx, img)
+}
+
+// DetectionsFromCamera returns the detections of the next image from the given camera.
+func (vm *vizModel) DetectionsFromCamera(
+	ctx context.Context,
+	cameraName string,
+	extra map[string]interface{},
+) ([]objectdetection.Detection, error) {
+	ctx, span := trace.StartSpan(ctx, "service::vision::DetectionsFromCamera::"+vm.Named.Name().String())
+	defer span.End()
+	if cameraName == "" && vm.defaultCamera == "" {
+		return nil, errors.New("no camera name provided and no default camera found")
+	} else if cameraName == "" {
+		cameraName = vm.defaultCamera
+	}
+	if vm.detectorFunc == nil {
+		return nil, errors.Errorf("vision model %q does not implement a Detector", vm.Named.Name())
+	}
+	cam, err := camera.FromRobot(vm.r, cameraName)
+	if err != nil {
+		return nil, errors.Wrapf(err, "could not find camera named %s", cameraName)
+	}
+	img, err := camera.DecodeImageFromCamera(ctx, "", extra, cam)
+	if err != nil {
+		return nil, errors.Wrapf(err, "could not get image from %s", cameraName)
+	}
+	return vm.detectorFunc(ctx, img)
+}
+
+// Classifications returns the classifications of given image if the model implements classifications.Classifier.
+func (vm *vizModel) Classifications(
+	ctx context.Context,
+	img image.Image,
+	n int,
+	extra map[string]interface{},
+) (classification.Classifications, error) {
+	ctx, span := trace.StartSpan(ctx, "service::vision::Classifications::"+vm.Named.Name().String())
+	defer span.End()
+	if vm.classifierFunc == nil {
+		return nil, errors.Errorf("vision model %q does not implement a Classifier", vm.Named.Name())
+	}
+	fullClassifications, err := vm.classifierFunc(ctx, img)
+	if err != nil {
+		return nil, errors.Wrap(err, "could not get classifications from image")
+	}
+	return fullClassifications.TopN(n)
+}
+
+// ClassificationsFromCamera returns the classifications of the next image from the given camera.
+func (vm *vizModel) ClassificationsFromCamera(
+	ctx context.Context,
+	cameraName string,
+	n int,
+	extra map[string]interface{},
+) (classification.Classifications, error) {
+	ctx, span := trace.StartSpan(ctx, "service::vision::ClassificationsFromCamera::"+vm.Named.Name().String())
+	defer span.End()
+	if cameraName == "" && vm.defaultCamera == "" {
+		return nil, errors.New("no camera name provided and no default camera found")
+	} else if cameraName == "" {
+		cameraName = vm.defaultCamera
+	}
+	if vm.classifierFunc == nil {
+		return nil, errors.Errorf("vision model %q does not implement a Classifier", vm.Named.Name())
+	}
+	cam, err := camera.FromRobot(vm.r, cameraName)
+	if err != nil {
+		return nil, errors.Wrapf(err, "could not find camera named %s", cameraName)
+	}
+	img, err := camera.DecodeImageFromCamera(ctx, "", extra, cam)
+	if err != nil {
+		return nil, errors.Wrapf(err, "could not get image from %s", cameraName)
+	}
+	fullClassifications, err := vm.classifierFunc(ctx, img)
+	if err != nil {
+		return nil, errors.Wrap(err, "could not get classifications from image")
+	}
+	return fullClassifications.TopN(n)
+}
+
+// GetObjectPointClouds returns all the found objects in a 3D image if the model implements Segmenter3D.
+func (vm *vizModel) GetObjectPointClouds(
+	ctx context.Context,
+	cameraName string,
+	extra map[string]interface{},
+) ([]*viz.Object, error) {
+	if vm.segmenter3DFunc == nil {
+		return nil, errors.Errorf("vision model %q does not implement a 3D segmenter", vm.Named.Name().String())
+	}
+	ctx, span := trace.StartSpan(ctx, "service::vision::GetObjectPointClouds::"+vm.Named.Name().String())
+	defer span.End()
+	if cameraName == "" && vm.defaultCamera == "" {
+		return nil, errors.New("no camera name provided and no default camera found")
+	} else if cameraName == "" {
+		cameraName = vm.defaultCamera
+	}
+	cam, err := camera.FromRobot(vm.r, cameraName)
+	if err != nil {
+		return nil, err
+	}
+	return vm.segmenter3DFunc(ctx, cam)
+}
+
+// GetProperties returns a Properties object that details the vision capabilities of the model.
+func (vm *vizModel) GetProperties(ctx context.Context, extra map[string]interface{}) (*Properties, error) {
+	_, span := trace.StartSpan(ctx, "service::vision::GetProperties::"+vm.Named.Name().String())
+	defer span.End()
+
+	return &vm.properties, nil
+}
+
+func (vm *vizModel) CaptureAllFromCamera(
+	ctx context.Context,
+	cameraName string,
+	opt viscapture.CaptureOptions,
+	extra map[string]interface{},
+) (viscapture.VisCapture, error) {
+	ctx, span := trace.StartSpan(ctx, "service::vision::ClassificationsFromCamera::"+vm.Named.Name().String())
+	defer span.End()
+	if cameraName == "" && vm.defaultCamera == "" {
+		return viscapture.VisCapture{}, errors.New("no camera name provided and no default camera found")
+	} else if cameraName == "" {
+		cameraName = vm.defaultCamera
+	}
+	cam, err := camera.FromRobot(vm.r, cameraName)
+	if err != nil {
+		return viscapture.VisCapture{}, errors.Wrapf(err, "could not find camera named %s", cameraName)
+	}
+	img, err := camera.DecodeImageFromCamera(ctx, "", extra, cam)
+	if err != nil {
+		return viscapture.VisCapture{}, errors.Wrapf(err, "could not get image from %s", cameraName)
+	}
+	logger := vm.r.Logger()
+	var detections []objectdetection.Detection
+	if opt.ReturnDetections {
+		if !vm.properties.DetectionSupported {
+			logger.Debugf("detections requested but vision model %q does not implement a Detector", vm.Named.Name())
+		} else {
+			detections, err = vm.Detections(ctx, img, extra)
+			if err != nil {
+				return viscapture.VisCapture{}, err
+			}
+		}
+	}
+	var classifications classification.Classifications
+	if opt.ReturnClassifications {
+		logger := vm.r.Logger()
+		if !vm.properties.ClassificationSupported {
+			logger.Debugf("classifications requested in CaptureAll but vision model %q does not implement a Classifier",
+				vm.Named.Name())
+		} else {
+			classifications, err = vm.Classifications(ctx, img, 0, extra)
+			if err != nil {
+				return viscapture.VisCapture{}, err
+			}
+		}
+	}
+
+	var objPCD []*viz.Object
+	if opt.ReturnObject {
+		if !vm.properties.ObjectPCDsSupported {
+			logger := vm.r.Logger()
+			logger.Debugf("object point cloud requested in CaptureAll but vision model %q does not implement a 3D Segmenter", vm.Named.Name())
+		} else {
+			objPCD, err = vm.GetObjectPointClouds(ctx, cameraName, extra)
+			if err != nil {
+				return viscapture.VisCapture{}, err
+			}
+		}
+	}
+	if !opt.ReturnImage {
+		img = nil
+	}
+	return viscapture.VisCapture{
+		Image:           img,
+		Detections:      detections,
+		Classifications: classifications,
+		Objects:         objPCD,
+	}, nil
+}
+
+func (vm *vizModel) Close(ctx context.Context) error {
+	if vm.closerFunc == nil {
+		return nil
+	}
+	return vm.closerFunc(ctx)
+}