feat(WIP): create a dataset.

common/vision/lasr_face_recognition/CMakeLists.txt

@@ -160,6 +160,7 @@ include_directories(
 ## Mark executable scripts (Python etc.) for installation
 ## in contrast to setup.py, you can choose the destination
 catkin_install_python(PROGRAMS
+  scripts/create_dataset
   examples/relay
   examples/greet
   nodes/service

common/vision/lasr_face_recognition/examples/greet

@@ -0,0 +1,57 @@
+#!/usr/bin/env python3
+
+import sys
+import rospy
+from copy import deepcopy
+
+from sensor_msgs.msg import Image
+
+from lasr_vision_msgs.srv import Recognise, RecogniseRequest
+
+if len(sys.argv) < 3:
+    print('Usage: rosrun lase_recognition greet <source_topic> <dataset>')
+    exit()
+
+listen_topic = sys.argv[1]
+dataset = sys.argv[2]
+people_in_frame = []
+last_received_time = None
+
+
+def detect(image):
+    rospy.loginfo("Received image message")
+    global people_in_frame
+    people_in_frame = []
+    try:
+        detect_service = rospy.ServiceProxy('/recognise', Recognise)
+        req = RecogniseRequest()
+        req.image_raw = image
+        req.dataset = dataset
+        req.confidence = 0.5
+        resp = detect_service(req)
+        for detection in resp.detections:
+            people_in_frame.append(detection.name)
+        print(resp)
+    except rospy.ServiceException as e:
+        rospy.logerr("Service call failed: %s" % e)
+
+def greet():
+    print(f"Hello, {' '.join(people_in_frame)}")
+
+def image_callback(image):
+    global last_received_time
+    if last_received_time is None or rospy.Time.now() - last_received_time >= rospy.Duration(5.0):
+        prev_people_in_frame = deepcopy(people_in_frame)
+        detect(image)
+        if people_in_frame != prev_people_in_frame:
+            greet()
+        last_received_time = rospy.Time.now()
+
+def listener():
+    rospy.init_node('image_listener', anonymous=True)
+    rospy.wait_for_service('/recognise')
+    rospy.Subscriber(listen_topic, Image, image_callback)
+    rospy.spin()
+
+if __name__ == '__main__':
+    listener()

common/vision/lasr_face_recognition/launch/camera.launch

@@ -11,7 +11,7 @@
     </include>
 
     <!-- show debug topic -->
-    <node name="image_view" pkg="rqt_image_view" type="rqt_image_view" respawn="false" output="screen" args="/yolov8/debug" />
+    <node name="image_view" pkg="rqt_image_view" type="rqt_image_view" respawn="false" output="screen" args="/recognise/debug" />
 
     <!-- start relay service -->
     <node name="relay" pkg="lasr_face_recognition" type="relay" respawn="false" output="screen" args="/camera/image_raw $(arg dataset)" />

common/vision/lasr_face_recognition/requirements.in

@@ -1 +1,2 @@
 deepface==0.0.81
+numpy>=1.2.1

common/vision/lasr_face_recognition/scripts/create_dataset

@@ -1,9 +1,10 @@
 #!/usr/bin/env python3
 
 import sys
+import lasr_face_recognition as face_recognition
 
 if len(sys.argv) < 3:
-    print("usage: rosrun lasr_face_recognition create_dataset.py <dataset> <name> [size=20]")
+    print("usage: rosrun lasr_face_recognition create_dataset.py <dataset> <name> [size=50]")
     exit(0)
 
 dataset = sys.argv[1]
@@ -12,7 +13,7 @@ name = sys.argv[2]
 if len(sys.argv) > 3:
     size = sys.argv[3]
 else:
-    size = 20
+    size = 50
 
 import rospy
 import rospkg
@@ -32,6 +33,8 @@ rospy.loginfo(f"Taking {size} pictures of {name} and saving to {DATASET_PATH}")
 for i in range(size):
     img_msg = rospy.wait_for_message("/xtion/rgb/image_raw", Image)
     cv_im = cv2_img.msg_to_cv2_img(img_msg)
-    cv2.imwrite(os.path.join(DATASET_PATH), f"{name}_{i+1}.png", cv_im)
-    rospy.loginfo(f"Took picutre {i+1}")
-    rospy.sleep(rospy.Duration(1.0))
+    face_cropped_cv_im = face_recognition.detect_face(cv_im)
+    if face_cropped_cv_im is None:
+        continue
+    cv2.imwrite(os.path.join(DATASET_PATH, f"{name}_{i+1}.png"), face_cropped_cv_im)
+    rospy.loginfo(f"Took picture {i+1}")

common/vision/lasr_face_recognition/src/lasr_face_recognition/__init__.py

@@ -1 +1 @@
-from .deepface import detect
+from .deepface import detect, detect_face

common/vision/lasr_face_recognition/src/lasr_face_recognition/deepface.py

@@ -4,12 +4,23 @@
 import rospkg
 import rospy
 import os
+import numpy as np
 
 from lasr_vision_msgs.msg import Detection
 from lasr_vision_msgs.srv import RecogniseRequest, RecogniseResponse
 
 DATASET_ROOT = os.path.join(rospkg.RosPack().get_path("lasr_face_recognition"), "datasets")
 
+Mat = int#np.typing.NDArray[np.uint8]
+
+def detect_face(cv_im : Mat) -> Mat | None:
+    faces = DeepFace.extract_faces(cv_im, target_size=(224, 244), detector_backend="mtcnn", enforce_detection = False)
+    if not faces:
+        return None
+    facial_area = faces[0]["facial_area"]
+    x,y,w,h = facial_area["x"], facial_area["y"], facial_area["w"], facial_area["h"]
+    return cv_im[:][y:y+h, x:x+w]
+
 def detect(request : RecogniseRequest, debug_publisher: rospy.Publisher | None) -> RecogniseResponse:
 
     # Decode the image
@@ -18,7 +29,7 @@ def detect(request : RecogniseRequest, debug_publisher: rospy.Publisher | None)
 
     # Run inference
     rospy.loginfo("Running inference")
-    result = DeepFace.find(cv_im, os.path.join(DATASET_ROOT, request.dataset), enforce_detection=False)
+    result = DeepFace.find(cv_im, os.path.join(DATASET_ROOT, request.dataset), enforce_detection=False, silent=True)
 
     response = RecogniseResponse()
 
@@ -29,11 +40,12 @@ def detect(request : RecogniseRequest, debug_publisher: rospy.Publisher | None)
         detection.name = row["identity"][0].split("/")[-1].split("_")[0]
         x, y, w, h = row["source_x"][0], row["source_y"][0], row["source_w"][0], row["source_h"][0]
         detection.xywh = [x, y, w, h]
+        confidence = row["VGG-Face_cosine"]
         response.detections.append(detection)
 
         # Draw bounding boxes and labels for debugging
         cv2.rectangle(cv_im, (x, y), (x+w, y+h), (0, 0, 255), 2)
-        cv2.putText(cv_im, detection.name, (x,y-5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
+        cv2.putText(cv_im, f"{detection.name} ({confidence})", (x,y-5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
 
     # publish to debug topic
     if debug_publisher is not None: