Merge remote-tracking branch 'upstream/main'

api/config/models.py

@@ -644,7 +644,7 @@ class TaskQueue(BaseModel):
 
 class FaceSpecBQAT(str, Enum):
     ipd = "Inter-pupillary distance."
-    confidence = "Confidence level of face dectection (not quality score)."
+    face_detection = "Confidence level of face dectection (not quality score)."
     bbox_left = "Left border of the face bounding box coordinates in pixels."
     bbox_right = "Right border of the face bounding box coordinates in pixels."
     bbox_upper = "Upper border of the face bounding box coordinates in pixels."
@@ -662,7 +662,37 @@ class FaceSpecBQAT(str, Enum):
     roll_pose = "Roll in head pose direction."
     roll_degree = "Roll in head pose degree."
     smile = "Smile detected or not."
-    glassed = "Glasses detected or not."
+    glasses = "Eyeglasses/Spectacles detected or not."
+    face_ratio = "Ratio of face area to whole image."
+    brightness = "Average brightness of the image."
+    dynamic_range = "Dynamic range of the image."
+    sharpness = "Shaphness of the image."
+    contrast = "Contrast of the image."
+    face_offset_x = "Horizontal offset of the face from image centre."
+    face_offset_y = "Vertical offset of the face from image centre."
+    background_colour_name = "Background colour name."
+    background_colour_rgb = "Background colour rgb values."
+    background_uniformity = "Background colour uniformity."
+    hair_coverage = "Ratio of detected hair area to whole face bounding box."
+    blur_lap_var = "Laplacian variance of image as a indicator of blurriness"
+    blurriness = "Blur effect metric. A estimate strength of perceptual blurriness."
+    gaze_right_x = "Right eyeball gazing direction offset percentage horizontal."
+    gaze_right_y = "Right eyeball gazing direction offset percentage vertical."
+    gaze_left_x = "Left eyeball gazing direction offset percentage horizontal."
+    gaze_left_y = "Left eyeball gazing direction offset percentage vertical."
+    pupil_colour_right_name = "Right pupil colour name."
+    pupil_colour_right_rgb = "Right pupil colour rgb values."
+    pupil_colour_left_name = "Left pupil colour name."
+    pupil_colour_left_rgb = "Left pupil colour rgb values."
+    brisque_quality = "Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) no-reference image quality score"
+    age = "Estimation of age."
+    gender = "Estimation of gender."
+    ethnicity = "Estimation of ethnicity."
+    emotion = "Estimation of emotions."
+    is_hologram = "Hologram effect detected or not."
+    holograms = "Hologram area detected."
+    is_glare = "Glare/Reflection on the image detected or not."
+    glares = "Glare area detected."
 
 
 class FaceSpecOFIQ(str, Enum):

api/routes/index.py

@@ -17,7 +17,16 @@
 from PIL import Image as PILImage
 
 from api.config import Settings
-from api.config.models import ImageRequest
+from api.config.models import (
+    FaceSpecBIQT,
+    FaceSpecBQAT,
+    FaceSpecOFIQ,
+    FingerprintSpecDefault,
+    ImageRequest,
+    IrisSpecDefault,
+    Modality,
+    SpeechSpecDefault,
+)
 from api.utils import ensure_base64_padding, extend, get_info
 
 router = APIRouter()
@@ -216,3 +225,57 @@ async def delete_dataset(
 )
 async def get_version_info():
     return JSONResponse(status_code=status.HTTP_200_OK, content=get_info())
+
+
+@router.get(
+    "/specification",
+    response_description="Output descriptions retrieved",
+    description="Fetches output columns descriptions.",
+)
+async def get_description(modality: Modality, engine: str = "default"):
+    match modality:
+        case Modality.face:
+            match engine:
+                case "bqat" | "default":
+                    return {item.name: item.value for item in FaceSpecBQAT}
+                case "ofiq":
+                    return {item.name: item.value for item in FaceSpecOFIQ}
+                case "biqt":
+                    return {item.name: item.value for item in FaceSpecBIQT}
+                case _:
+                    raise HTTPException(
+                        status_code=status.HTTP_400_BAD_REQUEST,
+                        detail="Invalid engine specified.",
+                    )
+        case Modality.fingerprint:
+            match engine:
+                case "default":
+                    return {item.name: item.value for item in FingerprintSpecDefault}
+                case _:
+                    raise HTTPException(
+                        status_code=status.HTTP_400_BAD_REQUEST,
+                        detail="Invalid engine specified.",
+                    )
+        case Modality.iris:
+            match engine:
+                case "default":
+                    return {item.name: item.value for item in IrisSpecDefault}
+                case _:
+                    raise HTTPException(
+                        status_code=status.HTTP_400_BAD_REQUEST,
+                        detail="Invalid engine specified.",
+                    )
+        case Modality.speech:
+            match engine:
+                case "default":
+                    return {item.name: item.value for item in SpeechSpecDefault}
+                case _:
+                    raise HTTPException(
+                        status_code=status.HTTP_400_BAD_REQUEST,
+                        detail="Invalid engine specified.",
+                    )
+        case _:
+            raise HTTPException(
+                status_code=status.HTTP_400_BAD_REQUEST,
+                detail="Invalid modality specified.",
+            )

api/utils.py

@@ -897,6 +897,7 @@ async def run_report_tasks(
                 {
                     "mode": dataset_log["options"].get("mode"),
                     "engine": dataset_log["options"].get("engine"),
+                    "fusion": dataset_log["options"].get("fusion"),
                 }
             )
 
@@ -1581,6 +1582,28 @@ def generate_report(data, **options):
                         metadata = {
                             "description": "Face image dataset, processed by BIQT engine."
                         }
+                    case "fusion":
+                        descriptions = {}
+                        engines = []
+                        fusion_code = options.get("fusion", 0)
+                        if fusion_code & 4 == 4:
+                            descriptions.update(
+                                {item.name: item.value for item in FaceSpecBQAT}
+                            )
+                            engines.append("BQAT")
+                        if fusion_code & 2 == 2:
+                            descriptions.update(
+                                {item.name: item.value for item in FaceSpecOFIQ}
+                            )
+                            engines.append("OFIQ")
+                        if fusion_code & 1 == 1:
+                            descriptions.update(
+                                {item.name: item.value for item in FaceSpecBIQT}
+                            )
+                            engines.append("BIQT")
+                        metadata = {
+                            "description": f"Folder of face images, processed by fusion engine{' (' + ', '.join(engines) + ')' if engines else ''}."
+                        }
                     case _:
                         descriptions = {}
                         metadata = {"description": "Face image dataset."}