EFRS-885 Add age/gender recognition as an independent plugin

embedding-calculator/Dockerfile

@@ -27,7 +27,9 @@ ENV JOBLIB_MULTIPROCESSING=0
 # download ML models
 ARG DETECTION_MODEL="retinaface_r50_v1"
 ARG CALCULATION_MODEL="arcface_r100_v1"
-ENV DETECTION_MODEL=$DETECTION_MODEL CALCULATION_MODEL=$CALCULATION_MODEL
+ARG GENDERAGE_MODEL="genderage_v1"
+ENV DETECTION_MODEL=$DETECTION_MODEL CALCULATION_MODEL=$CALCULATION_MODEL \
+    GENDERAGE_MODEL=$GENDERAGE_MODEL
 COPY srcext srcext
 COPY pytest.ini .
 COPY *.sh ./

embedding-calculator/prepare_scanners.sh

@@ -3,7 +3,7 @@
 if [[ "$SCANNER" == "InsightFace" ]]; then
   MODELS_PATH=~/.insightface/models
   mkdir -p $MODELS_PATH
-  for MODEL in $DETECTION_MODEL $CALCULATION_MODEL
+  for MODEL in $DETECTION_MODEL $CALCULATION_MODEL $GENDERAGE_MODEL
   do
     # trying to find a pre-downloaded model
     DIR=~/srcext/insightface/models/$MODEL
@@ -19,12 +19,8 @@ if [[ "$SCANNER" == "InsightFace" ]]; then
     # https://github.com/deepinsight/insightface/issues/764
     sed -i 's/limited_workspace/None/g' $MODELS_PATH/$MODEL/*.json
   done
-else
-  echo "  --ignore=src/services/facescan/scanner/insightface" >> pytest.ini
 fi
 
 if [[ "$SCANNER" == "Facenet2018" ]]; then
   pip install --no-cache-dir tensorflow~=1.15.4
-else
-  echo "  --ignore=src/services/facescan/scanner/facenet" >> pytest.ini
 fi

embedding-calculator/sample_images/annotations.py

@@ -7,20 +7,22 @@
 class Row:
     img_name: str
     noses: List[Tuple[int, int]]
+    is_male: bool = None
+    age: int = None
     include_to_tests: bool = True
 
 
 SAMPLE_IMAGES = [
     Row('000_5.jpg', [(219, 105), (300, 252), (392, 220), (469, 309), (600, 294)]),
-    Row('001_A.jpg', [(2109, 2261)]),
-    Row('002_A.jpg', [(2146, 2424)]),
-    Row('003_A.jpg', [(3210, 1382)]),
-    Row('004_A.jpg', [(1312, 1969)]),
-    Row('005_A.jpg', [(2092, 2871)]),
-    Row('006_A.jpg', [(1864, 3041)]),
-    Row('007_B.jpg', [(210, 292)]),
-    Row('008_B.jpg', [(225, 256)]),
-    Row('009_C.jpg', [(166, 236)]),
+    Row('001_A.jpg', [(2109, 2261)]), # wrong gender recognition
+    Row('002_A.jpg', [(2146, 2424)]), # wrong gender recognition
+    Row('003_A.jpg', [(3210, 1382)], False, 30),
+    Row('004_A.jpg', [(1312, 1969)], False, 30),
+    Row('005_A.jpg', [(2092, 2871)], False, 30),
+    Row('006_A.jpg', [(1864, 3041)], False, 30),
+    Row('007_B.jpg', [(210, 292)], False, 23),
+    Row('008_B.jpg', [(225, 256)]), # wrong gender recognition
+    Row('009_C.jpg', [(166, 236)], True, 32),
     Row('010_2.jpg', [(354, 232), (505, 258)]),
     Row('011_3.jpg', [(295, 266), (484, 245), (385, 216)]),
     Row('012_4.jpg', [(208, 205), (318, 241), (454, 228), (641, 240)]),

embedding-calculator/src/_endpoints.py

@@ -11,14 +11,16 @@
 #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
 #  or implied. See the License for the specific language governing
 #  permissions and limitations under the License.
-from typing import List
+from typing import List, Optional
 
 from flask import request
 from flask.json import jsonify
 from werkzeug.exceptions import BadRequest
 
 from src.constants import ENV
 from src.exceptions import NoFaceFoundError
+from src.services.facescan import helpers
+from src.services.facescan.scanner import facescanner as scanners
 from src.services.facescan.scanner.facescanners import scanner
 from src.services.flask_.constants import ARG
 from src.services.flask_.needs_attached_file import needs_attached_file
@@ -28,31 +30,37 @@
 def endpoints(app):
     @app.route('/status')
     def status_get():
+        availiable_plugins = {p.name: p.backend for p in helpers.get_plugins()}
         return jsonify(status='OK', build_version=ENV.BUILD_VERSION,
-                       calculator_version=ENV.SCANNER)
+                       calculator_version=scanner.ID,
+                       availiable_plugins=availiable_plugins)
 
     @app.route('/find_faces', methods=['POST'])
     @needs_attached_file
     def find_faces_post():
-        faces = scanner.find_faces(
+        detector = helpers.get_detector(_get_det_plugin_name())
+        face_plugins = helpers.get_plugins(_get_face_plugin_names())
+
+        faces = detector(
             img=read_img(request.files['file']),
-            det_prob_threshold=_get_det_prob_threshold(request),
+            det_prob_threshold=_get_det_prob_threshold(),
+            face_plugins=face_plugins
         )
-        faces = _limit(faces, request.values.get(ARG.LIMIT))
-        return jsonify(calculator_version=scanner.ID, result=faces)
+        plugins_versions = {p.name: p.backend for p in [detector] + face_plugins}
+        return jsonify(results=faces, plugins_versions=plugins_versions)
 
     @app.route('/scan_faces', methods=['POST'])
     @needs_attached_file
     def scan_faces_post():
         faces = scanner.scan(
             img=read_img(request.files['file']),
-            det_prob_threshold=_get_det_prob_threshold(request)
+            det_prob_threshold=_get_det_prob_threshold()
         )
         faces = _limit(faces, request.values.get(ARG.LIMIT))
         return jsonify(calculator_version=scanner.ID, result=faces)
 
 
-def _get_det_prob_threshold(request):
+def _get_det_prob_threshold():
     det_prob_threshold_val = request.values.get(ARG.DET_PROB_THRESHOLD)
     if det_prob_threshold_val is None:
         return None
@@ -62,6 +70,20 @@ def _get_det_prob_threshold(request):
     return det_prob_threshold
 
 
+def _get_det_plugin_name() -> Optional[str]:
+    if ARG.DET_PLUGIN not in request.values:
+        return
+    return request.values.get(ARG.DET_PLUGIN)
+
+
+def _get_face_plugin_names() -> Optional[List[str]]:
+    if ARG.FACE_PLUGINS not in request.values:
+        return
+    return [
+        name for name in request.values[ARG.FACE_PLUGINS].split(',') if name
+    ]
+
+
 def _limit(faces: List, limit: str = None) -> List:
     """
     >>> _limit([1, 2, 3], None)

embedding-calculator/src/constants.py

@@ -32,7 +32,30 @@ class ENV(Constants):
     GPU_ID = int(get_env('GPU_ID', '-1'))
     DETECTION_MODEL = get_env('DETECTION_MODEL', 'retinaface_r50_v1')
     CALCULATION_MODEL = get_env('CALCULATION_MODEL', 'arcface_r100_v1')
+    GENDERAGE_MODEL = get_env('GENDERAGE_MODEL', 'genderage_v1')
 
 
 LOGGING_LEVEL = logging._nameToLevel[ENV.LOGGING_LEVEL_NAME]
 ENV_MAIN = ENV
+
+
+MXNET_FACE_DETECTORS = (
+    '.plugins.insightface.FaceDetector',
+)
+MXNET_FACE_PLUGINS = (
+    '.plugins.insightface.Calculator',
+    'src.services.facescan.plugins.insightface.GenderAgeDetector',
+)
+
+TF_FACE_DETECTORS = (
+    '.plugins.facenet.FaceDetector',
+)
+TF_FACE_PLUGINS = (
+    '.plugins.facenet.Calculator',
+    '.plugins.rude_carnie.AgeDetector',
+    '.plugins.rude_carnie.GenderDetector',
+    # '.plugins.insightface.GenderAgeDetector',
+)
+
+FACE_DETECTORS = TF_FACE_DETECTORS
+FACE_PLUGINS = TF_FACE_PLUGINS

embedding-calculator/src/docs/find_faces_post.yml

@@ -2,7 +2,7 @@ tags:
   - Core
 summary: 'Find faces in the given image and return their bounding boxes.'
 description: 'Returns bounding boxes of detected faces on the image.'
-operationId: scanFacesPost
+operationId: findFacesPost
 consumes:
   - multipart/form-data
 produces:

embedding-calculator/src/exceptions.py

@@ -37,10 +37,6 @@ class OneDimensionalImageIsGivenError(BadRequest):
     description = "Given image has only one dimension"
 
 
-class MoreThanOneFaceFoundError(BadRequest):
-    description = "Found more than one face in the given image"
-
-
 class ClassifierIsAlreadyTrainingError(Locked):
     description = "Classifier training is already in progress"
 
@@ -74,3 +70,6 @@ class CouldNotConnectToDatabase(InternalServerError):
 class NotEnoughUniqueFacesError(BadRequest):
     description = "Not enough unique faces to start training a new classifier model. " \
                   "Deleting existing classifiers, if any."
+
+class InvalidFaceDetectorPlugin(BadRequest):
+    description = "Invalid face detector plugin"

embedding-calculator/src/services/dto/plugin_result.py

@@ -0,0 +1,44 @@
+import attr
+from typing import Tuple, List, Optional, Dict
+
+from src.services.dto.bounding_box import BoundingBoxDTO
+from src.services.dto.json_encodable import JSONEncodable
+from src.services.imgtools.types import Array1D, Array3D
+
+
+class PluginResultDTO(JSONEncodable):
+    def to_json(self) -> dict:
+        """ Serialize only public properties """
+        return {k: v for k, v in self.__dict__.items() if not k.startswith('_')}
+
+
+@attr.s(auto_attribs=True, frozen=True)
+class EmbeddingDTO(PluginResultDTO):
+    embedding: Array1D
+
+
+@attr.s(auto_attribs=True, frozen=True)
+class GenderDTO(PluginResultDTO):
+    gender: str
+    gender_probability: float = attr.ib(converter=float, default=None)
+
+
+@attr.s(auto_attribs=True, frozen=True)
+class AgeDTO(PluginResultDTO):
+    age: Tuple[int, int]
+    age_probability: float = attr.ib(converter=float, default=None)
+
+
+@attr.s(auto_attribs=True)
+class FaceDTO(PluginResultDTO):
+    box: BoundingBoxDTO
+    _img: Optional[Array3D]
+    _face_img: Optional[Array3D]
+    _plugins_dto: List[PluginResultDTO] = attr.Factory(list)
+    execution_time: Dict[str, float] = attr.Factory(dict)
+
+    def to_json(self):
+        data = super().to_json()
+        for plugin_dto in self._plugins_dto:
+            data.update(plugin_dto.to_json())
+        return data

embedding-calculator/src/services/dto/scanned_face.py

@@ -12,7 +12,7 @@
 #  or implied. See the License for the specific language governing
 #  permissions and limitations under the License.
 
-from typing import Union
+from typing import Union, Optional
 
 import attr
 
@@ -22,23 +22,27 @@
 from src.services.imgtools.types import Array1D, Array3D
 
 
+@attr.s(auto_attribs=True)
+class Face(JSONEncodable):
+    _img: Optional[Array3D]
+    _face_img: Optional[Array3D]
+    box: BoundingBoxDTO
+
+
 @attr.s(auto_attribs=True, frozen=True)
 class ScannedFaceDTO(JSONEncodable):
     box: BoundingBoxDTO
     embedding: Array1D
 
 
-class ScannedFace(JSONEncodable):
-    def __init__(self, box: BoundingBoxDTO, embedding: Array1D, img: Union[Array3D, None], face_img: Array3D = None):
-        self.box = box
-        self.embedding = embedding
-        self.img = img
-        self._face_img = face_img
+@attr.s(auto_attribs=True)
+class ScannedFace(Face):
+    embedding: Array1D
 
     @property
     def face_img(self):
         if not self._face_img:
-            self._face_img = crop_img(self.img, self.box)
+            self._face_img = crop_img(self._img, self.box)
         return self._face_img
 
     @property
@@ -53,4 +57,5 @@ def from_request(cls, result):
                                               y_min=box_result['y_min'],
                                               y_max=box_result['y_max'],
                                               probability=box_result['probability']),
-                           embedding=result['embedding'], img=None)
+                           embedding=result['embedding'],
+                           img=None, face_img=None)

embedding-calculator/src/services/facescan/conftest.py

@@ -0,0 +1,32 @@
+#  Copyright (c) 2020 the original author or authors
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#       https://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
+#  or implied. See the License for the specific language governing
+#  permissions and limitations under the License.
+
+import os
+from importlib.util import find_spec
+
+modules_by_lib = {
+    'tensorflow': ('facenet', 'rude_carnie'),
+    'mexnet': ('insightface',)
+}
+modules_to_skip = []
+for lib, modules in modules_by_lib.items():
+    if find_spec(lib) is None:
+        modules_to_skip.extend(modules)
+
+
+def pytest_ignore_collect(path):
+    _, last_path = os.path.split(path)
+    for module in modules:
+        if last_path.startswith(module):
+            return True