From 9bd50c9ad615e5eed79447becc96bbe30ae88e56 Mon Sep 17 00:00:00 2001 From: iasonth95 Date: Tue, 5 Mar 2024 21:52:07 +0100 Subject: [PATCH 1/6] (face_recognition) new pkg, contents copied from openface --- .gitmodules | 4 + image_recognition/package.xml | 1 + .../CMakeLists.txt | 20 + image_recognition_face_recognition/README.md | 79 + image_recognition_face_recognition/docs | 1 + .../package.xml | 38 + .../rosdoc.yaml | 3 + .../scripts/face_recognition_node | 271 + .../scripts/get_face_recognition | 47 + .../scripts/train_from_images | 70 + image_recognition_face_recognition/setup.py | 6 + .../facenet_recognition.py | 201 + .../log.txt | 195376 +++++++++++++++ .../requirements.txt | 493 + .../test.py | 154 + 15 files changed, 196764 insertions(+) create mode 100644 image_recognition_face_recognition/CMakeLists.txt create mode 100644 image_recognition_face_recognition/README.md create mode 160000 image_recognition_face_recognition/docs create mode 100644 image_recognition_face_recognition/package.xml create mode 100644 image_recognition_face_recognition/rosdoc.yaml create mode 100755 image_recognition_face_recognition/scripts/face_recognition_node create mode 100755 image_recognition_face_recognition/scripts/get_face_recognition create mode 100755 image_recognition_face_recognition/scripts/train_from_images create mode 100644 image_recognition_face_recognition/setup.py create mode 100644 image_recognition_face_recognition/src/image_recognition_face_recognition/facenet_recognition.py create mode 100644 image_recognition_face_recognition/src/image_recognition_face_recognition/log.txt create mode 100644 image_recognition_face_recognition/src/image_recognition_face_recognition/requirements.txt create mode 100644 image_recognition_face_recognition/src/image_recognition_face_recognition/test.py diff --git a/.gitmodules b/.gitmodules index f4f33b52..3901d549 100644 --- a/.gitmodules +++ b/.gitmodules @@ -38,3 +38,7 @@ path = image_recognition_pose_estimation/docs url = https://github.com/tue-robotics/tue_documentation_python.git branch = master +[submodule "image_recognition_face_recognition/docs"] + path = image_recognition_face_recognition/docs + url = https://github.com/tue-robotics/tue_documentation_python.git + branch = master diff --git a/image_recognition/package.xml b/image_recognition/package.xml index d13f5293..2fd7b345 100644 --- a/image_recognition/package.xml +++ b/image_recognition/package.xml @@ -15,6 +15,7 @@ image_recognition_age_gender image_recognition_analysis image_recognition_color_extractor + image_recognition_face_recognition image_recognition_footwear image_recognition_msgs image_recognition_openface diff --git a/image_recognition_face_recognition/CMakeLists.txt b/image_recognition_face_recognition/CMakeLists.txt new file mode 100644 index 00000000..4319b516 --- /dev/null +++ b/image_recognition_face_recognition/CMakeLists.txt @@ -0,0 +1,20 @@ +cmake_minimum_required(VERSION 3.0.2) +project(image_recognition_face_recognition) + + +find_package(catkin REQUIRED COMPONENTS) + +catkin_python_setup() + +catkin_package() + +install(PROGRAMS + scripts/get_face_recognition + scripts/face_recognition_node + scripts/train_from_images + DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION} +) +if(CATKIN_ENABLE_TESTING) + find_package(catkin_lint_cmake REQUIRED) + catkin_add_catkin_lint_test() +endif() diff --git a/image_recognition_face_recognition/README.md b/image_recognition_face_recognition/README.md new file mode 100644 index 00000000..33e31446 --- /dev/null +++ b/image_recognition_face_recognition/README.md @@ -0,0 +1,79 @@ +# image_recognition_face_recognition + +NEEDS WORK + +Face recognition with use of Openpose (https://cmusatyalab.github.io/openface/) + +## Installation + +See https://github.com/tue-robotics/image_recognition + +Make sure that openface is correctly installed. Installation instructions can be found here: https://cmusatyalab.github.io/openface/setup/. Make sure you have installed **CUDA8**. CUDA10 is not working: https://github.com/torch/torch7/issues/1180 + +```bash +export TORCH_INSTALL_PATH=~/torch +export OPENFACE_INSTALL_PATH=~/openface +git clone https://github.com/torch/distro.git ~/torch --recursive && \ +cd $TORCH_INSTALL_PATH && bash install-deps && ./install.sh && \ +for NAME in dpnn nn optim optnet csvigo cutorch cunn fblualib torchx tds; do $TORCH_INSTALL_PATH/install/bin/luarocks install $NAME; done && \ +sudo -H pip install dlib && \ +git clone https://github.com/cmusatyalab/openface.git $OPENFACE_INSTALL_PATH && \ +cd $OPENFACE_INSTALL_PATH && sudo -H python setup.py install && \ +./models/get-models.sh +``` + +## How-to + +### ROS Node + +Run the image_recognition_openface node in one terminal (Specify the dlib and openface_net path as ROS parameter): + + rosrun image_recognition_openface face_recognition_node + +Run the rqt annotation client (https://github.com/tue-robotics/image_recognition_rqt) + + rosrun image_recognition_rqt annotation_gui + +Setup the service by clicking the gear wheel in the top-right corner. Select the `/annotate` services exposed by the openface ros node. Also don't forget to set-up your labels. + +![Configuration](doc/config.png) + +Now draw a rectangle around the face you would like to learn. The face recognizer will find the biggest face in the image and store a representation for this face. + +![Annotate](doc/annotate.png) + +Now select the label and you will see that the openface ros node stores the face (console output node): + + [INFO] [WallTime: 1478636380.407308] Succesfully learned face of 'rokus' + +Learn as many faces as you want .. + +Next step is starting the image_recognition_Rqt test gui (https://github.com/tue-robotics/image_recognition_rqt) + + rosrun image_recognition_rqt test_gui + +Again configure the service you want to call with the gear-wheel in the top-right corner of the screen. If everything is set-up, draw a rectangle in the image and ask the service for detections: + +![Test](doc/test_face.png) + +You will see that the result of the detection will prompt in a dialog combo box. Also the detections will be drawn on the image. + +### Command line + +Command line interface to test the detection / recognition based on an image: + + usage: get_face_recognition IMAGE [-k ALIGN_PATH] [-s NET_PATH] [-v] + +Run the command on an example image: + + rosrun image_recognition_openface get_face_recognition `rospack find image_recognition_openface`/doc/example.png + +This will lookup this image in the image_recognition_openface/doc folder and perform recognitions + +![Example](doc/example.png) + +Output: + + [RecognizedFace(roi=(374, 188, 108, 123), l2_distances=[]), RecognizedFace(roi=(72, 147, 88, 105), l2_distances=[]), RecognizedFace(roi=(377, 95, 74, 86), l2_distances=[]), RecognizedFace(roi=(149, 26, 74, 86), l2_distances=[]), RecognizedFace(roi=(52, 47, 75, 86), l2_distances=[]), RecognizedFace(roi=(246, 115, 88, 102), l2_distances=[]), RecognizedFace(roi=(0, 0, 42, 60), l2_distances=[]), RecognizedFace(roi=(336, 33, 74, 86), l2_distances=[]), RecognizedFace(roi=(228, 0, 62, 60), l2_distances=[])] + +Since no faces were trained, the l2_distances will not be calculated of-course. diff --git a/image_recognition_face_recognition/docs b/image_recognition_face_recognition/docs new file mode 160000 index 00000000..e81558db --- /dev/null +++ b/image_recognition_face_recognition/docs @@ -0,0 +1 @@ +Subproject commit e81558db940b4e13b67d84919f55e942a5ceec0f diff --git a/image_recognition_face_recognition/package.xml b/image_recognition_face_recognition/package.xml new file mode 100644 index 00000000..97d5ea87 --- /dev/null +++ b/image_recognition_face_recognition/package.xml @@ -0,0 +1,38 @@ + + + + image_recognition_face_recognition + 0.0.1 + The image_recognition_face_recognition package + + iason + + MIT + + catkin + + python3-setuptools + + roscpp + cv_bridge + diagnostic_updater + image_recognition_msgs + image_recognition_util + python-dlib + python3-numpy + python3-opencv + rospy + + catkin_lint_cmake + + python3-sphinx + python-sphinx-autoapi-pip + python-sphinx-rtd-theme-pip + python3-yaml + + + + + diff --git a/image_recognition_face_recognition/rosdoc.yaml b/image_recognition_face_recognition/rosdoc.yaml new file mode 100644 index 00000000..d6daeddf --- /dev/null +++ b/image_recognition_face_recognition/rosdoc.yaml @@ -0,0 +1,3 @@ +- builder: sphinx + sphinx_root_dir: docs + name: Python API diff --git a/image_recognition_face_recognition/scripts/face_recognition_node b/image_recognition_face_recognition/scripts/face_recognition_node new file mode 100755 index 00000000..0248612f --- /dev/null +++ b/image_recognition_face_recognition/scripts/face_recognition_node @@ -0,0 +1,271 @@ +#!/usr/bin/env python + +import os +import sys +import diagnostic_updater +import rospy +from cv_bridge import CvBridge, CvBridgeError +from sensor_msgs.msg import RegionOfInterest, Image +from std_srvs.srv import Empty +from image_recognition_msgs.msg import ( + Recognition, + Recognitions, + CategoryProbability, + CategoricalDistribution, +) +from image_recognition_msgs.srv import Recognize, Annotate +from image_recognition_util import image_writer +from image_recognition_openface.facenet_recognition import Facenet_recognition + + +class OpenfaceROS: + def __init__( + self, + align_path, + net_path, + save_images_folder, + topic_save_images, + service_save_images, + topic_publish_result_image, + service_publish_result_image, + ): + """ + OpenfaceROS class that wraps the FaceRecognizer in a ROS node + + :param align_path: dlib face align path + :param net_path: openface neural net path + :param save_images_folder: path where to store the images + :param topic_save_images: whether to save images originated from image topic callback + :param service_save_images: whether to save images originated from a service call + :param topic_publish_result_image: whether to publish images originated from image topic callback + :param service_publish_result_image: whether to publish images originated from a serice call + """ + + # Openface ROS + self._face_recognizer = Facenet_recognition() + # self._face_recognizer = FaceRecognizer(align_path, net_path) + self._save_images_folder = save_images_folder + self._topic_save_images = topic_save_images + self._service_save_images = service_save_images + self._topic_publish_result_image = topic_publish_result_image + self._service_publish_result_image = service_publish_result_image + + self._bridge = CvBridge() + self._annotate_srv = rospy.Service("annotate", Annotate, self._annotate_srv) + self._recognize_srv = rospy.Service("recognize", Recognize, self._recognize_srv) + self._clear_srv = rospy.Service("clear", Empty, self._clear_srv) + + self._image_subscriber = rospy.Subscriber("image", Image, self._image_callback) + self._recognitions_publisher = rospy.Publisher("recognitions", Recognitions, queue_size=10) + + if not self._save_images_folder and (self._topic_save_images or self._service_save_images): + rospy.logerr("~save_images_folder is not defined but we would like to save images ...") + rospy.signal_shutdown("") + + if self._topic_publish_result_image or self._service_publish_result_image: + self._result_image_publisher = rospy.Publisher("result_image", Image, queue_size=10) + + rospy.loginfo("OpenfaceROS initialized:") + rospy.loginfo(" - dlib_align_path=%s", align_path) + rospy.loginfo(" - openface_net_path=%s", net_path) + rospy.loginfo(" - save_images_folder=%s", save_images_folder) + rospy.loginfo(" - topic_save_images=%s", topic_save_images) + rospy.loginfo(" - service_save_images=%s", service_save_images) + rospy.loginfo(" - topic_publish_result_image=%s", topic_publish_result_image) + rospy.loginfo(" - service_publish_result_image=%s", service_publish_result_image) + + def _annotate_srv(self, req): + # Convert to opencv image + """ + Annotate service callback that trains the face of the user + + :param req: Face annotation request + :return: Empty + """ + try: + bgr_image = self._bridge.imgmsg_to_cv2(req.image, "bgr8") + except CvBridgeError as e: + raise Exception("Could not convert to opencv image: %s" % str(e)) + + for annotation in req.annotations: + roi_image = bgr_image[ + annotation.roi.y_offset: annotation.roi.y_offset + annotation.roi.height, + annotation.roi.x_offset: annotation.roi.x_offset + annotation.roi.width, + ] + + if self._save_images_folder: + image_writer.write_annotated(self._save_images_folder, roi_image, annotation.label, True) + + try: + self._face_recognizer.train(roi_image, annotation.label) + except Exception as e: + raise Exception("Could not get representation of face image: %s" % str(e)) + + rospy.loginfo("Succesfully learned face of '%s'" % annotation.label) + + return {} + + def _clear_srv(self, req): + """ + Service to clear the trained faces + + :param req: Empty + :return: Empty + """ + self._face_recognizer.clear_trained_faces() + return {} + + def _get_recognitions(self, image_msg, save_images, publish_images): + # Convert to opencv image + """ + Recognize service callback + + :param req: The input image + :return: Recognitions + """ + try: + bgr_image = self._bridge.imgmsg_to_cv2(image_msg, "bgr8") + except CvBridgeError as e: + raise Exception("Could not convert to opencv image: %s" % str(e)) + + # Write raw image + if save_images: + image_writer.write_raw(self._save_images_folder, bgr_image) + + images = [] + labels = [] + labels = ["jason", "kona"] + # Call openface + face_recognitions = self._face_recognizer.face_detection(bgr_image) + dist, face_labelling = self._face_recognizer.detection_recognition(bgr_image, labels, train=True) + # Fill recognitions + recognitions = [] + + # rospy.loginfo("Face recognitions: %s", face_recognitions) + + i = 0 + for fr in face_recognitions: + import math + + face_recognition = [math.floor(xi) for xi in fr] + if save_images: + label = face_labelling[i] + roi_image = bgr_image[ + face_recognition[2]: face_recognition[3], + face_recognition[0]: face_recognition[1], + ] + image_writer.write_annotated(self._save_images_folder, roi_image, label, False) + images.append(roi_image) + labels.append(label) + label = face_labelling[i] + disti = dist[i] + recognitions.append( + Recognition( + categorical_distribution=CategoricalDistribution( + unknown_probability=0.0, # TODO: When is it unknown? + probabilities=[ + CategoryProbability(label=label, probability=1.0 / (disti + 0.001)) for l2 in face_recognition + ], + ), + roi=RegionOfInterest( + x_offset=face_recognition[0], + y_offset=face_recognition[1], + width=face_recognition[2] - face_recognition[0], + height=face_recognition[3] - face_recognition[1], + ), + ) + ) + i = i + 1 + + annotated_original_image = image_writer.get_annotated_cv_image(bgr_image, recognitions) + if save_images: + image_writer.write_estimations( + self._save_images_folder, + images, + labels, + annotated_original_image, + suffix="_face_recognition", + ) + + if publish_images: + self._result_image_publisher.publish(self._bridge.cv2_to_imgmsg(annotated_original_image, "bgr8")) + + # Service response + return recognitions + + def _image_callback(self, image_msg): + # UNCOMMENT THOSE LINES NOW ITS COMMENTED FOR DEBUGGING + try: + recognitions = self._get_recognitions( + image_msg, + save_images=self._topic_save_images, + publish_images=self._topic_publish_result_image, + ) + except Exception as e: + rospy.logerr(str(e)) + return + + self._recognitions_publisher.publish(Recognitions(header=image_msg.header, recognitions=recognitions)) + + def _recognize_srv(self, req): + recognitions = self._get_recognitions( + req.image, + save_images=self._service_save_images, + publish_images=self._service_publish_result_image, + ) + + # Service response + return {"recognitions": recognitions} + + def restore_trained_faces(self, file_name): + self._face_recognizer.restore_trained_faces(file_name) + + +if __name__ == "__main__": + rospy.init_node("face_recognition") + try: + dlib_shape_predictor_path = os.path.expanduser( + rospy.get_param( + "~align_path", + "~/openface/models/dlib/shape_predictor_68_face_landmarks.dat", + ) + ) + openface_neural_network_path = os.path.expanduser( + rospy.get_param("~net_path", "~/openface/models/openface/nn4.small2.v1.t7") + ) + save_images = rospy.get_param("~save_images", True) + topic_save_images = rospy.get_param("~topic_save_images", False) + service_save_images = rospy.get_param("~service_save_images", True) + topic_publish_result_image = rospy.get_param("~topic_publish_result_image", True) + service_publish_result_image = rospy.get_param("~service_publish_result_image", True) + + db = rospy.get_param("~db", None) + if db: + db = os.path.expanduser(db) + + save_images_folder = None + if save_images: + save_images_folder = os.path.expanduser(rospy.get_param("~save_images_folder", "/tmp/openface")) + except KeyError as e: + rospy.logerr("Parameter %s not found" % e) + sys.exit(1) + + image_recognition_openface = OpenfaceROS( + dlib_shape_predictor_path, + openface_neural_network_path, + save_images_folder, + topic_save_images, + service_save_images, + topic_publish_result_image, + service_publish_result_image, + ) + if db: + rospy.loginfo("loading face database from %s", db) + image_recognition_openface.restore_trained_faces(db) + + updater = diagnostic_updater.Updater() + updater.setHardwareID("none") + updater.add(diagnostic_updater.Heartbeat()) + rospy.Timer(rospy.Duration(1), lambda event: updater.force_update()) + + rospy.spin() diff --git a/image_recognition_face_recognition/scripts/get_face_recognition b/image_recognition_face_recognition/scripts/get_face_recognition new file mode 100755 index 00000000..c2982e14 --- /dev/null +++ b/image_recognition_face_recognition/scripts/get_face_recognition @@ -0,0 +1,47 @@ +#!/usr/bin/env python +from __future__ import print_function + +import argparse + +import cv2 +from image_recognition_msgs.msg import Recognition +from image_recognition_openface.face_recognizer import FaceRecognizer +# Assign description to the help doc +from sensor_msgs.msg import RegionOfInterest + +from image_recognition_util import image_writer + +parser = argparse.ArgumentParser(description='Get face recognitions') + +# Add arguments +parser.add_argument('image', type=str, help='Image') +parser.add_argument('-k', '--align_path', type=str, help='DLib Align path', required=False, + default="~/openface/models/dlib/shape_predictor_68_face_landmarks.dat") +parser.add_argument('-s', '--net_path', type=str, help='Openface neural network path', required=False, + default='~/openface/models/openface/nn4.small2.v1.t7') +parser.add_argument('-d', '--db', type=argparse.FileType('r'), help='Load already trained faces db from file') +parser.add_argument( + '-v', '--verbose', help="Increase output verbosity", action="store_true") +args = parser.parse_args() + +# Read the image +img = cv2.imread(args.image) + +# Create openface interface +face_recognizer = FaceRecognizer(args.align_path, args.net_path) + +if args.db: + face_recognizer.restore_trained_faces(args.db) + +recognized_faces = face_recognizer.recognize(img) +print(recognized_faces) +annotated_original_image = image_writer.get_annotated_cv_image(img, [Recognition( + roi=RegionOfInterest( + x_offset=f.roi.x_offset, + y_offset=f.roi.y_offset, + width=f.roi.width, + height=f.roi.height + ) +) for f in recognized_faces]) +cv2.imshow("result", annotated_original_image) +cv2.waitKey() diff --git a/image_recognition_face_recognition/scripts/train_from_images b/image_recognition_face_recognition/scripts/train_from_images new file mode 100755 index 00000000..f735a726 --- /dev/null +++ b/image_recognition_face_recognition/scripts/train_from_images @@ -0,0 +1,70 @@ +#!/usr/bin/env python +import os +import cv2 +import logging +from argparse import ArgumentParser, Action, ArgumentTypeError, FileType +from image_recognition_openface.face_recognizer import FaceRecognizer + + +logging.basicConfig() +logger = logging.getLogger(__name__) + + +def main(modeldir, outfile, align_path, net_path, verbose): + if verbose: + logger.setLevel(logging.DEBUG) + else: + logger.setLevel(logging.INFO) + + face_recognizer = FaceRecognizer(align_path, net_path) + + dirs = [o for o in os.listdir(modeldir) if os.path.isdir(os.path.join(modeldir, o))] + for cat in dirs: + logger.info('loading images for %s', cat) + path = os.path.join(modeldir, cat) + + logger.debug('loading images from %s', path) + for fname in os.listdir(path): + f = os.path.join(path, fname) + logger.debug('processing %s', f) + + img = cv2.imread(f, 1) # load as color + + try: + logger.debug('training...') + face_recognizer.train(img, cat) + logger.debug('success!') + except Exception: + logger.exception('face_recognizer failed to process %s', f) + + logger.info('saving database...') + face_recognizer.save_trained_faces(outfile) + logger.info('done!') + + +class ReadableDir(Action): + def __call__(self,parser, namespace, values, option_string=None): + prospective_dir=values + if not os.path.isdir(prospective_dir): + raise ArgumentTypeError("readable_dir:{0} is not a valid path".format(prospective_dir)) + if os.access(prospective_dir, os.R_OK): + setattr(namespace,self.dest,prospective_dir) + else: + raise ArgumentTypeError("readable_dir:{0} is not a readable dir".format(prospective_dir)) + + +if __name__ == '__main__': + parser = ArgumentParser(description='Train openface from a database of images') + + parser.add_argument('modeldir', action=ReadableDir, help='Directory with folders for each category') + parser.add_argument('outfile', type=FileType('w'), help='Where to output the trained faces database') + + parser.add_argument('-k', '--align_path', type=str, help='DLib Align path', required=False, + default="~/openface/models/dlib/shape_predictor_68_face_landmarks.dat") + parser.add_argument('-s', '--net_path', type=str, help='Openface neural network path', required=False, + default='~/openface/models/openface/nn4.small2.v1.t7') + + parser.add_argument('-v', '--verbose', action='store_true') + + args = parser.parse_args() + main(**vars(args)) \ No newline at end of file diff --git a/image_recognition_face_recognition/setup.py b/image_recognition_face_recognition/setup.py new file mode 100644 index 00000000..f849d00f --- /dev/null +++ b/image_recognition_face_recognition/setup.py @@ -0,0 +1,6 @@ +from catkin_pkg.python_setup import generate_distutils_setup +from setuptools import setup + +d = generate_distutils_setup(packages=["image_recognition_face_recognition"], package_dir={"": "src"}) + +setup(**d) diff --git a/image_recognition_face_recognition/src/image_recognition_face_recognition/facenet_recognition.py b/image_recognition_face_recognition/src/image_recognition_face_recognition/facenet_recognition.py new file mode 100644 index 00000000..dfe04c68 --- /dev/null +++ b/image_recognition_face_recognition/src/image_recognition_face_recognition/facenet_recognition.py @@ -0,0 +1,201 @@ +import psutil +import rospy +import torch +from facenet_pytorch import MTCNN, InceptionResnetV1 +from facenet_pytorch.models.mtcnn import MTCNN + + +class TrainedFace: + def __init__(self, label): + """ + A custom struct to store the names and the embedded representations (tensors) of people + """ + self.label = label + self.representations = [] + + def get_label(self) -> str: + """ + A getter for the labels of the struct + """ + return self.label + + def get_representations(self): + """ + A getter for the embeddings of the struct + """ + return self.representations + + +class Facenet_recognition: + def __init__(self): + """ + Constructor for the list which contains the TrainedFace structure + """ + self._trained_faces = [] + + def print_memory_usage(self, label): + """ + Prints the memory usage as a metric + """ + mem_info = psutil.Process().memory_info() + rospy.loginfo( + f"{label: <10}: vms={mem_info.vms / (1024 * 1024)}, rss={mem_info.rss / (1024 * 1024)}" + ) + + def face_detection(self, img): + """ + Returns the index of the trained face + + :param img: inpute image + :return: the bounding boxes of coordinations of the faces it detects + """ + detector = MTCNN(keep_all=True) + # Keep the landmarks for future use + boxes, _, landmarks = detector.detect(img, landmarks=True) + return boxes + + def _get_dists(self, embeddings): + """ + Returns min l2 distance of the identified face (compared with the database of know faces) + + :param embeddings: the embedded representation(s) of a face(s) + :return: the min distance(s) of the embedded vector compared with the database faces + :return: the corresponding label(s) + """ + dist_per_emb_final = [] + dist = [] + dist_per_emb = [] + + min_of_emb_final = [] + + min_index_list_per_emb = [] + min_value_list_per_emb = [] + + for e2 in embeddings: + for e1 in self._trained_faces: + for e3 in e1.representations: + dist_per_emb.append(abs(e3 - e2).norm().item()) + dist.append(dist_per_emb) + rospy.loginfo(f"{dist_per_emb} dist_per_emb") + dist_per_emb = [] + dist_per_emb_final.append(dist) + dist = [] + + rospy.loginfo(f"{dist_per_emb_final} dist_per_emb_final") + for i in dist_per_emb_final: + min_of_emb = [min(j) for j in i] + rospy.loginfo(f"{min_of_emb} min_of_emb") + min_of_emb_final.append(min_of_emb) + rospy.loginfo(f"{min_of_emb_final} min_of_emb_final") + + for idx in min_of_emb_final: + rospy.loginfo(f"{idx} idx") + min_index_list_per_emb.append(idx.index(min(idx))) + min_value_list_per_emb.append(min(idx)) + rospy.loginfo(f"{min_index_list_per_emb}, min_index_list_per_emb") + rospy.loginfo(f"{min_value_list_per_emb}, min_index_list") + + labelling = [self._trained_faces[i].get_label() for i in min_index_list_per_emb] + rospy.loginfo(f"{labelling}, {min_value_list_per_emb}") + + return min_value_list_per_emb, labelling + + def detection_recognition(self, img, labels, train): + """ + Returns min l2 distance of the identified face (compared with the database of know faces) + + :param img: the target image collected from camera + :param images: NA/ a list with all img (why this is needed?) + :param labels: NA/ a list with all labels (this will be used during integration) + :param save_images: NA/ a folder with all saved images (why this is needed?) + :param train: flag to train during inference time + :return: the min distance(s) of the embedded vector compared with the database faces + :return: the corresponding label(s) + """ + device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") + rospy.loginfo(f"Running on device: {device}") + + mtcnn = MTCNN( + keep_all=True, + image_size=160, + margin=0, + min_face_size=20, + thresholds=[0.6, 0.7, 0.7], + factor=0.709, + post_process=True, + device=device, + ) + + resnet = InceptionResnetV1(pretrained="vggface2").eval().to(device) + + x_aligned = mtcnn(img) + print(type(x_aligned)) + print(x_aligned.size(), "x_aligned size (1st NN output)") + x_aligned = x_aligned.cuda() # add this line + embeddings = resnet(x_aligned).detach().cpu() + rospy.loginfo(f"{embeddings.size()}, {type(embeddings)}, embeddings size") + + if not self._trained_faces: + nam = 0 + for emb in embeddings: + index = self._get_trained_face_index(labels[nam]) + if index == -1: + self._trained_faces.append(TrainedFace(labels[nam])) + + self._trained_faces[index].representations.append(emb) + nam = nam + 1 + + # try: + dist, labelling = self._get_dists(embeddings) + # if dist > 1: + # in this case we should ask for a label + rospy.loginfo(f"{labels[0]}, {labelling}, label[0],labelling") + + if train: + idx_label = 0 + for emb in embeddings: + rospy.loginfo(f"{idx_label}, idx_label") + self.train(emb, labelling[idx_label]) + idx_label = idx_label + 1 + # except: + rospy.loginfo(f"{len(self._trained_faces)}") + return dist, labelling + + def _get_trained_face_index(self, label): + """ + Returns the index of the trained face + + :param label: label of the trained face + :return: the index of the face in the self._trained faces list + """ + for i, f in enumerate(self._trained_faces): + if f.label == label: + return i + return -1 + + def train(self, face_representation, name): + """ + Adds a face to the trained faces, creates a vector representation and adds this + + :param image: Embedded representation of the image + :param name: The label of the face + """ + index = self._get_trained_face_index(name) + if index == -1: + rospy.loginfo(f"We do not know this face") + self._trained_faces.append(TrainedFace(name)) + + self._trained_faces[index].representations.append(face_representation) + rospy.loginfo(f"Trained faces:") + for trained_face in self._trained_faces: + rospy.loginfo( + f"Label: {trained_face.get_label()}, Representations: {len(trained_face.get_representations())}" + ) + + +if __name__ == "__main__": + """ + Runs the whole code. It is not needed if it runs from a ros node. + """ + face_detection = Facenet_recognition() + face_detection.detection_recognition() diff --git a/image_recognition_face_recognition/src/image_recognition_face_recognition/log.txt b/image_recognition_face_recognition/src/image_recognition_face_recognition/log.txt new file mode 100644 index 00000000..c39ed83b --- /dev/null +++ b/image_recognition_face_recognition/src/image_recognition_face_recognition/log.txt @@ -0,0 +1,195376 @@ +[INFO] [1709671590.441693]: OpenfaceROS initialized: : 68 +[INFO] [1709671590.443011]: - dlib_align_path=/home/iason/openface/models/dlib/shape_predictor_68_face_landmarks.dat : 69 +[INFO] [1709671590.444208]: - openface_net_path=/home/iason/openface/models/openface/nn4.small2.v1.t7 : 70 +[INFO] [1709671590.445281]: - save_images_folder=/tmp/openface : 71 +[INFO] [1709671590.446391]: - topic_save_images=False : 72 +[INFO] [1709671590.447434]: - service_save_images=True : 73 +[INFO] [1709671590.448538]: - 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dist_per_emb_final : 84 +[INFO] [1709671604.846021]: [0.1577223241329193] min_of_emb : 87 +[INFO] [1709671604.846826]: [[0.1577223241329193]] min_of_emb_final : 89 +[INFO] [1709671604.847670]: [0.1577223241329193] idx : 92 +[INFO] [1709671604.849246]: [0], min_index_list_per_emb : 95 +[INFO] [1709671604.852951]: [0.1577223241329193], min_index_list : 96 +[INFO] [1709671604.855376]: ['jason'], [0.1577223241329193] : 99 +[INFO] [1709671604.857262]: jason, ['jason'], label[0],labelling : 152 +[INFO] [1709671604.858418]: 0, idx_label : 157 +[INFO] [1709671604.859411]: Trained faces: : 189 +[INFO] [1709671604.860345]: Label: jason, Representations: 3 : 191 +[INFO] [1709671604.861136]: 1 : 161 +tensor([[[[-0.4492, -0.4193, -0.3906, ..., -0.6562, -0.6510, -0.6348], + [-0.4310, -0.3911, -0.3659, ..., -0.6120, -0.6220, -0.6263], + [-0.3965, -0.3659, -0.3340, ..., -0.5820, -0.5924, -0.5977], + ..., + [-0.9512, -0.8841, -0.7598, ..., -0.0957, -0.0755, -0.0742], + [-0.9479, -0.9197, -0.8242, ..., 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[1709671611.931761]: [0.1684955656528473] idx : 92 +[INFO] [1709671611.934478]: [0], min_index_list_per_emb : 95 +[INFO] [1709671611.936131]: [0.1684955656528473], min_index_list : 96 +[INFO] [1709671611.937288]: ['jason'], [0.1684955656528473] : 99 +[INFO] [1709671611.938338]: jason, ['jason'], label[0],labelling : 152 +[INFO] [1709671611.939588]: 0, idx_label : 157 +[INFO] [1709671611.940928]: Trained faces: : 189 +[INFO] [1709671611.942152]: Label: jason, Representations: 4 : 191 +[INFO] [1709671611.945514]: 1 : 161 +tensor([[[[-0.3809, -0.3906, -0.3984, ..., -0.6016, -0.5807, -0.5723], + [-0.3776, -0.3928, -0.4049, ..., -0.6185, -0.5907, -0.5794], + [-0.3711, -0.3737, -0.3770, ..., -0.6270, -0.6263, -0.6309], + ..., + [-0.9414, -0.9206, -0.8145, ..., -0.0605, -0.0625, -0.0527], + [-0.9714, -0.9145, -0.7747, ..., -0.0755, -0.0751, -0.0742], + [-0.9883, -0.8763, -0.7129, ..., -0.0977, -0.0872, -0.0820]], + + [[-0.3848, -0.3789, -0.3730, ..., -0.5391, -0.5430, -0.5566], + [-0.3906, 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b/image_recognition_face_recognition/src/image_recognition_face_recognition/requirements.txt @@ -0,0 +1,493 @@ +absl-py==2.0.0 +actionlib==1.14.0 +addict==2.4.0 +angles==1.9.13 +anyio==4.0.0 +apturl==0.5.2 +arabic-reshaper==3.0.0 +argon2-cffi==23.1.0 +argon2-cffi-bindings==21.2.0 +asn1crypto==1.5.1 +asttokens==2.4.1 +astunparse==1.6.3 +async-lru==2.0.4 +atomicwrites==1.1.5 +attrs==23.1.0 +autobahn==17.10.1 +Automat==0.8.0 +Babel==2.13.1 +backcall==0.2.0 +backports.zoneinfo==0.2.1 +base_local_planner==1.17.3 +bcrypt==3.1.7 +beautifulsoup4==4.12.2 +black==24.2.0 +bleach==6.1.0 +blessed==1.20.0 +blinker==1.4 +blosc==1.7.0 +bondpy==1.8.6 +Brlapi==0.7.0 +cachetools==5.3.1 +camera-calibration-parsers==1.12.0 +catkin==0.8.10 +catkin-pkg==1.0.0 +catkin-pkg-modules==1.0.0 +catkin-tools==0.9.2 +cbor==1.0.0 +certifi==2023.7.22 +cffi==1.16.0 +chardet==3.0.4 +charset-normalizer==3.3.2 +click==8.1.7 +cloudpickle==1.3.0 +colorama==0.4.3 +coloredlogs==15.0.1 +comm==0.2.0 +command-not-found==0.3 +configobj==5.0.6 +constantly==15.1.0 +contourpy==1.1.1 +controller-manager==0.19.6 +controller-manager-msgs==0.19.6 +cryptography==41.0.4 +cssselect2==0.7.0 +cupshelpers==1.0 +cv-bridge==1.16.2 +cycler==0.12.1 +Cython==0.29.14 +dask==2.8.1+dfsg +dbus-python==1.2.16 +debugpy==1.8.0 +decorator==5.1.1 +defer==1.0.6 +defusedxml==0.7.1 +diagnostic-analysis==1.11.0 +diagnostic-common-diagnostics==1.11.0 +diagnostic-updater==1.11.0 +distlib==0.3.7 +distro==1.4.0 +distro-info==0.23+ubuntu1.1 +dlib==19.24.2 +docopt==0.6.2 +docutils==0.20.1 +duplicity==0.8.12.0 +dynamic-reconfigure==1.7.3 +empy==3.3.2 +entrypoints==0.3 +et-xmlfile==1.0.1 +exceptiongroup==1.2.0 +executing==2.0.1 +facenet-pytorch==2.5.3 +fasteners==0.14.1 +fastjsonschema==2.19.0 +filelock==3.13.1 +flake8==7.0.0 +flatbuffers==23.5.26 +fonttools==4.45.0 +fsspec==2023.10.0 +future==0.18.2 +gast==0.4.0 +gazebo_plugins==2.9.2 +gazebo_ros==2.9.2 +gencpp==0.7.0 +geneus==3.0.0 +genlisp==0.4.18 +genmsg==0.6.0 +gennodejs==2.0.2 +genpy==0.6.15 +google-auth==2.23.3 +google-auth-oauthlib==1.0.0 +google-pasta==0.2.0 +graphviz==0.20.1 +grpcio==1.59.0 +h5py==3.10.0 +hsrb_angle_sensors_alignment==0.18.1 +hsrb_autocharge==0.18.1 +hsrb_battery_notifier==0.13.1 +hsrb_bumper==0.18.1 +hsrb_dashboard==0.3.5 +hsrb_fetch_hanged==0.4.2 +hsrb_gradational_color==0.18.1 +hsrb_grasp_state_observer==0.30.0 +hsrb_interface_py==0.12.0 +hsrb_joint_impedance_control==0.30.0 +hsrb_move_to_locations==0.4.2 +hsrb_restart_cancel_task==0.4.2 +hsrb_rlp_interface_py==0.3.1 +hsrb_rqt_joint_impedance==0.3.5 +hsrb_short_speech_task==0.4.2 +hsrb_simple_actions==0.4.2 +hsrb_status_led==0.13.1 +hsrb_task_history_trigger==0.4.2 +hsrb_task_state_machines==0.4.2 +hsrb_task_states==0.4.2 +hsrb_task_util==0.4.2 +hsrb_timeopt_ros==0.30.0 +hsrb_trajectory_filter==0.30.0 +hsrb_voice_trigger_task==0.4.2 +hsrb_web_server==0.30.0 +html5lib==1.0.1 +httplib2==0.14.0 +humanfriendly==10.0 +hyperlink==19.0.0 +idna==3.4 +image-geometry==1.16.2 +imageio==2.4.1 +importlib-metadata==6.8.0 +importlib-resources==6.1.1 +incremental==16.10.1 +inquirer==3.1.3 +interactive-markers==1.12.0 +ipykernel==6.27.0 +ipython==8.12.3 +ipython_genutils==0.2.0 +ipywidgets==8.1.1 +isort==5.13.2 +jdcal==1.0 +jedi==0.19.1 +Jinja2==3.1.2 +joblib==0.14.0 +joint-state-publisher==1.15.1 +joint-state-publisher-gui==1.15.1 +json5==0.9.14 +jsonschema==4.20.0 +jsonschema-specifications==2023.11.1 +jupyter==1.0.0 +jupyter-console==6.6.3 +jupyter-events==0.9.0 +jupyter-lsp==2.2.0 +jupyter_client==8.6.0 +jupyter_core==5.5.0 +jupyter_server==2.11.0 +jupyter_server_terminals==0.4.4 +jupyterlab==4.0.9 +jupyterlab-pygments==0.2.2 +jupyterlab-widgets==3.0.9 +jupyterlab_server==2.25.2 +keras==2.13.1 +keyring==18.0.1 +kiwisolver==1.4.5 +language-selector==0.1 +laser_geometry==1.6.7 +launchpadlib==1.10.13 +lazr.restfulclient==0.14.2 +lazr.uri==1.0.3 +libclang==16.0.6 +locket==0.2.0 +lockfile==0.12.2 +louis==3.12.0 +lxml==4.5.0 +lz4==3.0.2+dfsg +macaroonbakery==1.3.1 +Mako==1.1.0 +Markdown==3.1.1 +markdown-it-py==3.0.0 +MarkupSafe==2.1.3 +matplotlib==3.7.4 +matplotlib-inline==0.1.6 +mccabe==0.7.0 +mdurl==0.1.2 +meld==3.20.2 +message-filters==1.16.0 +mistune==3.0.2 +mmengine==0.10.0 +mock==3.0.5 +monotonic==1.5 +more-itertools==4.2.0 +mpi4py==3.0.3 +mpmath==1.3.0 +msgpack==0.6.2 +mypy-extensions==1.0.0 +nbclient==0.9.0 +nbconvert==7.11.0 +nbformat==5.9.2 +nest-asyncio==1.5.8 +netifaces==0.10.4 +networkx==3.1 +nose @ git+https://github.com/tue-robotics/nose.git@d4c51ff09de8e1bb9545b732b09d1f14cbf515cc +notebook==7.0.6 +notebook_shim==0.2.3 +numexpr==2.8.6 +numpy==1.24.4 +nvidia-cublas-cu12==12.1.3.1 +nvidia-cuda-cupti-cu12==12.1.105 +nvidia-cuda-nvrtc-cu12==12.1.105 +nvidia-cuda-runtime-cu12==12.1.105 +nvidia-cudnn-cu12==8.9.2.26 +nvidia-cufft-cu12==11.0.2.54 +nvidia-curand-cu12==10.3.2.106 +nvidia-cusolver-cu12==11.4.5.107 +nvidia-cusparse-cu12==12.1.0.106 +nvidia-nccl-cu12==2.18.1 +nvidia-nvjitlink-cu12==12.3.101 +nvidia-nvtx-cu12==12.1.105 +oauthlib==3.1.0 +olefile==0.46 +onnxruntime-gpu==1.16.0 +opencv-python==4.8.1.78 +openface==0.2.1 +openpyxl==3.0.3 +opt-einsum==3.3.0 +oscrypto==1.3.0 +osrf-pycommon==2.0.2 +overrides==7.4.0 +packaging==23.2 +pandas==2.0.3 +pandocfilters==1.5.0 +paramiko==2.6.0 +parso==0.8.3 +partd==1.0.0 +pathspec==0.12.1 +pbr==5.4.5 +pexpect==4.8.0 +pickleshare==0.7.5 +Pillow==10.1.0 +pkg_resources==0.0.0 +pkgutil_resolve_name==1.3.10 +platformdirs==4.0.0 +pluggy==0.13.0 +prometheus-client==0.19.0 +prompt-toolkit==3.0.41 +protobuf==4.24.4 +psutil==5.9.6 +ptyprocess==0.7.0 +pure-eval==0.2.2 +py==1.8.1 +py-ubjson==0.14.0 +pyasn1==0.4.2 +pyasn1-modules==0.2.1 +pycairo==1.16.2 +pycodestyle==2.11.1 +pycparser==2.21 +pycryptodomex==3.6.1 +pycups==1.9.73 +pydot==1.4.1 +pyflakes==3.2.0 +Pygments==2.17.1 +PyGObject==3.36.0 +PyHamcrest==1.9.0 +pyHanko==0.20.1 +pyhanko-certvalidator==0.24.1 +PyJWT==1.7.1 +pymacaroons==0.13.0 +PyNaCl==1.3.0 +PyOpenGL==3.1.0 +pyOpenSSL==19.0.0 +pyparsing==3.1.1 +pypdf==3.16.4 +pypng==0.0.20 +PyQRCode==1.2.1 +PyQt5==5.14.1 +pyRFC3339==1.1 +pyserial==3.4 +pytest==4.6.9 +python-apt==2.0.1+ubuntu0.20.4.1 +python-bidi==0.4.2 +python-dateutil==2.8.2 +python-debian==0.1.36+ubuntu1.1 +python-editor==1.0.4 +python-gnupg==0.4.5 +python-json-logger==2.0.7 +python-qt-binding==0.4.4 +python-snappy==0.5.3 +PyTrie==0.2 +pytz==2023.3.post1 +PyWavelets==0.5.1 +pyxdg==0.26 +PyYAML==6.0.1 +pyzmq==25.1.1 +qrcode==7.4.2 +qt-dotgraph==0.4.2 +qt-gui==0.4.2 +qt-gui-cpp==0.4.2 +qt-gui-py-common==0.4.2 +qtconsole==5.5.1 +QtPy==2.4.1 +readchar==4.0.5 +referencing==0.31.0 +reportlab==3.6.13 +requests==2.31.0 +requests-oauthlib==1.3.1 +requests-unixsocket==0.2.0 +resource_retriever==1.12.7 +rfc3339-validator==0.1.4 +rfc3986-validator==0.1.1 +rich==13.7.0 +roman==2.0.0 +rosapi==0.11.17 +rosbag==1.16.0 +rosboost-cfg==1.15.8 +rosbridge-library==0.11.17 +rosbridge-server==0.11.17 +rosclean==1.15.8 +roscreate==1.15.8 +rosdep==0.22.2 +rosdep-modules==0.22.2 +rosdistro-modules==0.9.0 +rosgraph==1.16.0 +roslaunch==1.16.0 +roslib==1.15.8 +roslint==0.12.0 +roslz4==1.16.0 +rosmake==1.15.8 +rosmaster==1.16.0 +rosmsg==1.16.0 +rosnode==1.16.0 +rosparam==1.16.0 +rospkg==1.5.0 +rospkg-modules==1.5.0 +rospy==1.16.0 +rospy_message_converter==0.5.9 +rosservice==1.16.0 +rostest==1.16.0 +rostopic==1.16.0 +rosunit==1.15.8 +roswtf==1.16.0 +rpds-py==0.13.1 +rqt-console==0.4.12 +rqt-image-view==0.4.17 +rqt-logger-level==0.4.12 +rqt-moveit==0.5.11 +rqt-reconfigure==0.5.5 +rqt-robot-dashboard==0.5.8 +rqt-robot-monitor==0.5.15 +rqt-runtime-monitor==0.5.10 +rqt-rviz==0.7.0 +rqt-tf-tree==0.6.4 +rqt_action==0.4.9 +rqt_bag==0.5.1 +rqt_bag_plugins==0.5.1 +rqt_dep==0.4.12 +rqt_graph==0.4.14 +rqt_gui==0.5.3 +rqt_gui_py==0.5.3 +rqt_launch==0.4.9 +rqt_msg==0.4.10 +rqt_nav_view==0.5.7 +rqt_plot==0.4.13 +rqt_pose_view==0.5.11 +rqt_publisher==0.4.10 +rqt_py_common==0.5.3 +rqt_py_console==0.4.10 +rqt_robot_steering==0.5.12 +rqt_service_caller==0.4.10 +rqt_shell==0.4.11 +rqt_srv==0.4.9 +rqt_top==0.4.10 +rqt_topic==0.4.13 +rqt_web==0.4.10 +rsa==4.9 +rviz==1.14.20 +scikit-image==0.16.2 +scikit-learn==0.22.2.post1 +scipy==1.3.3 +screen-resolution-extra==0.0.0 +SecretStorage==2.3.1 +Send2Trash==1.8.2 +sensor-msgs==1.13.1 +service-identity==18.1.0 +simplejson==3.16.0 +sip==4.19.21 +six==1.16.0 +smach==2.5.2 +smach-ros==2.5.2 +smach-viewer==4.1.0 +smclib==1.8.6 +sniffio==1.3.0 +sound-play==0.3.17 +soupsieve==2.5 +spline_smoother==1.1.0 +SQLAlchemy==1.3.12 +ssh-import-id==5.10 +stack-data==0.6.3 +svglib==1.5.1 +sympy==1.12 +systemd-python==234 +tables==3.6.1 +tensorboard==2.13.0 +tensorboard-data-server==0.7.1 +tensorflow-estimator==2.13.0 +tensorflow-io-gcs-filesystem==0.34.0 +termcolor==2.3.0 +terminado==0.18.0 +tf==1.13.2 +tf-conversions==1.13.2 +tf2-geometry-msgs==0.7.7 +tf2-kdl==0.7.7 +tf2-py==0.7.7 +tf2-ros==0.7.7 +tf2-sensor-msgs==0.7.7 +tinycss2==1.2.1 +tmc_env_db==0.23.4 +tmc_eus_py==0.1.3 +tmc_eus_py_visualization_tools==0.1.3 +tmc_force_torque_sensor_compensation==0.32.3 +tmc_grasp_state_recognizer==0.32.3 +tmc_grid_map_server==0.33.0 +tmc_image_capturer==0.35.1 +tmc_imu_wheel_odometry==0.33.0 +tmc_journald==0.4.3 +tmc_lint==0.11.0 +tmc_move_base_and_joint_positions==0.24.3 +tmc_mqtt_bridge==0.23.0 +tmc_object_topology_viewer==0.23.4 +tmc_remote_exec==0.30.0 +tmc_ros_node_monitor==0.4.3 +tmc_rosbag_tools==0.23.0 +tmc_rosjulius==0.22.2 +tmc_rostest_utils==0.11.0 +tmc_sanyo_battery==0.27.1 +tmc_sentence_trigger==0.23.4 +tmc_simple_actions==0.24.3 +tmc_smach_action_bridge==0.23.4 +tmc_smach_states==0.24.3 +tmc_stereo_marker_recognizer==0.34.2 +tmc_task_fw==0.23.4 +tmc_timeopt==0.34.1 +tmc_timeopt_ros==0.34.1 +tmc_utils_py==0.23.0 +tmc_vision_util==0.35.1 +tmc_voice_action==0.22.2 +tmc_web_helper==0.30.0 +tomli==2.0.1 +toolz==0.9.0 +topic-tools==1.16.0 +torch==2.1.1 +torchvision==0.16.1 +tornado==6.3.3 +traitlets==5.13.0 +triton==2.1.0 +Twisted==18.9.0 +txaio==2.10.0 +typing_extensions==4.8.0 +tzdata==2023.3 +tzlocal==5.1 +u-msgpack-python==2.1 +ubuntu-advantage-tools==8001 +ubuntu-drivers-common==0.0.0 +ufw==0.36 +unattended-upgrades==0.1 +urdfdom-py==0.4.6 +uritools==4.0.2 +urllib3==2.1.0 +usb-creator==0.3.7 +virtualenv==20.24.5 +wadllib==1.3.3 +wcwidth==0.2.11 +webencodings==0.5.1 +websocket-client==1.6.4 +Werkzeug==3.0.0 +widgetsnbextension==4.0.9 +wrapt==1.15.0 +wsaccel==0.6.2 +wxPython==4.0.7 +xacro==1.14.16 +xdot==1.1 +xhtml2pdf==0.2.11 +xkit==0.0.0 +xlrd==1.1.0 +xlwt==1.3.0 +yapf==0.40.2 +zipp==3.17.0 +zope.interface==4.7.1 diff --git a/image_recognition_face_recognition/src/image_recognition_face_recognition/test.py b/image_recognition_face_recognition/src/image_recognition_face_recognition/test.py new file mode 100644 index 00000000..394f9a61 --- /dev/null +++ b/image_recognition_face_recognition/src/image_recognition_face_recognition/test.py @@ -0,0 +1,154 @@ +# Online Python compiler (interpreter) to run Python online. +# Write Python 3 code in this online editor and run it. +print("Hello world") +import logging +logging.basicConfig(level=logging.INFO, format='%(levelname)s - %(message)s') + +_trained_faces = [] +class TrainedFace: + def __init__(self, label): + self.label = label + self.representations = [] + + def get_label(self) -> str : return self.label + +embeddings = [40,400] + +_trained_faces.append(TrainedFace('jason')) +_trained_faces.append(TrainedFace('kona')) +_trained_faces[0].representations.append(50) +_trained_faces[0].representations.append(40) + +_trained_faces[1].representations.append(300) +_trained_faces[1].representations.append(407) +_trained_faces[1].representations.append(700) +for trained_face in _trained_faces: + print(f"Label: {trained_face.label}, Representations: {trained_face.representations}") + +#dist = [(e1.representations[e3] - e2) for e1 in _trained_faces]for e3 in range(len(e1.representations)) for e2 in embeddings] +dist_per_emb_final = [] +dist = [] +dist_per_emb = [] + +min_of_emb_final = [] + +min_index_list_per_emb = [] +min_index_list= [] + +for e2 in embeddings: + for e1 in _trained_faces: + for e3 in (e1.representations): + dist_per_emb.append(abs(e3 - e2)) + dist.append(dist_per_emb) + logging.info(f"{dist_per_emb} dist_per_emb") + print(dist_per_emb,'dist_per_emb') + + dist_per_emb = [] + dist_per_emb_final.append(dist) + dist = [] + +print(dist_per_emb_final,'dist_per_emb_final') +for i in dist_per_emb_final: + min_of_emb = [min(j) for j in i] + print(min_of_emb,'min_of_emb') + min_of_emb_final.append(min_of_emb) +print(min_of_emb_final,'min_of_emb_final') + + +for idx in min_of_emb_final: + print(idx, 'min_index_list_per_emb') + min_index_list_per_emb.append(idx.index(min(idx))) + min_index_list.append(min(idx)) + print(idx.index(min(idx)),'minimum index') +print(min_index_list,'min_index_list') + +labelling = [_trained_faces[i].get_label() for i in min_index_list_per_emb] +print(labelling, min_index_list) + + +def _get_dists(self, embeddings): + ''' + HERE WE NEED TO FIND THE SHOURTEST EUKLIDEAN DISTANCE BETWEEN ALL OUR VECTORS + SPLIT THE FACES WE HAVE DETECT AND APPEND IT IN THE LIST + THEN FOR EVERY FACE WE DETECT IN embeddedings[i] WE NEED TO CHECK THE CLOSEST DETECTION WITH THE LIST + ''' + dist_per_emb_final = [] + dist = [] + dist_per_emb = [] + + min_of_emb_final = [] + + min_index_list_per_emb = [] + min_index_list= [] + + for e2 in embeddings: + for e1 in _trained_faces: + for e3 in (e1.representations): + dist_per_emb.append(abs(e3 - e2)) + dist.append(dist_per_emb) + print(dist_per_emb,'dist_per_emb') + dist_per_emb = [] + dist_per_emb_final.append(dist) + dist = [] + + print(dist_per_emb_final,'dist_per_emb_final') + for i in dist_per_emb_final: + min_of_emb = [min(j) for j in i] + print(min_of_emb,'min_of_emb') + min_of_emb_final.append(min_of_emb) + print(min_of_emb_final,'min_of_emb_final') + + + for idx in min_of_emb_final: + print(idx, 'min_index_list_per_emb') + min_index_list_per_emb.append(idx.index(min(idx))) + min_index_list.append(min(idx)) + + labelling = [_trained_faces[i].get_label() for i in min_index_list_per_emb] + print(labelling, min_index_list) + + return dist, labelling + + + +def _get_dists(self, embeddings): + ''' + HERE WE NEED TO FIND THE SHOURTEST EUKLIDEAN DISTANCE BETWEEN ALL OUR VECTORS + SPLIT THE FACES WE HAVE DETECT AND APPEND IT IN THE LIST + THEN FOR EVERY FACE WE DETECT IN embeddedings[i] WE NEED TO CHECK THE CLOSEST DETECTION WITH THE LIST + ''' + dist = [] + min_index=[] + labelling = [] + #this is tries for l2 norm but non needed since this technique uses euclidean distanses. + #dist.append(min([[np.subtract(vector_a, embeddings[i,:]) for vector_a in self._trained_faces] for i in range(embeddings.size(0))])) + #dist.append(min([[np.dot(vector_a - embeddings[i,:], vector_a - embeddings[i,:]) for vector_a in self._trained_faces] for i in range(embeddings.size(0))])) + + #for face_recognition in embeddings: + #if save_images: + #this is only for one face stored in every label in self._trained_faces THIS THIS THIS + #dist = [[(e1.representations[0] - e2).norm().item() for e2 in embeddings] for e1 in self._trained_faces] + #dist = [(e1.representations[e3] - e2).norm().item() for e1 in self._trained_faces for e3 in range(len(e1.representations)) for e2 in embeddings] + # dist = [[(e1.representations[e3] - e2).norm().item() for e2 in embeddings] for e1 in self._trained_faces for e3 in range(len(e1.representations))] + #dist = [[[(e1.representations[e3] - e2).norm().item() for e1 in self._trained_faces] for e3 in range(len(self._trained_faces[0].representations))] for e2 in embeddings] + ll = [] + for e2 in embeddings: + for e1 in self._trained_faces: + for e3 in (e1.representations): + ll.append((e3 - e2).norm().item()) + dist.append(ll) + ll = [] + + print(dist, '<-- Dist') + distance = [min(dist[index]) for index in range(len(dist))] + print(min(dist),'minsistmist') + print(distance, '<-- distance') + # get the index of the minimum distance (this would correspond to the appropriate label) + min_index = [idx.index(min(idx)) for idx in dist] + print(min_index,'min index') + + labelling = [self._trained_faces[i].get_label() for i in min_index] + #labelling = [np.argmin(dist[index]) for index in range(len(dist))] + print(distance,labelling,'<--Distance with the close label is') + + return dist, labelling \ No newline at end of file From 65d24ed3fd40b790924105abecf8e9940d874504 Mon Sep 17 00:00:00 2001 From: iasonth95 Date: Tue, 5 Mar 2024 21:58:42 +0100 Subject: [PATCH 2/6] small update on face recognition node --- .../scripts/face_recognition_node | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/image_recognition_face_recognition/scripts/face_recognition_node b/image_recognition_face_recognition/scripts/face_recognition_node index 0248612f..dcf8eab8 100755 --- a/image_recognition_face_recognition/scripts/face_recognition_node +++ b/image_recognition_face_recognition/scripts/face_recognition_node @@ -15,7 +15,7 @@ from image_recognition_msgs.msg import ( ) from image_recognition_msgs.srv import Recognize, Annotate from image_recognition_util import image_writer -from image_recognition_openface.facenet_recognition import Facenet_recognition +from image_recognition_face_recognition.facenet_recognition import Facenet_recognition class OpenfaceROS: From c431a0454d4b2eb076d4728822ef7697ba9ba309 Mon Sep 17 00:00:00 2001 From: iasonth95 Date: Fri, 8 Mar 2024 12:03:55 +0100 Subject: [PATCH 3/6] cherry-pick update of my latest commit --- .../scripts/face_recognition_node | 25 +++++++++++-------- 1 file changed, 14 insertions(+), 11 deletions(-) diff --git a/image_recognition_face_recognition/scripts/face_recognition_node b/image_recognition_face_recognition/scripts/face_recognition_node index dcf8eab8..8e93c573 100755 --- a/image_recognition_face_recognition/scripts/face_recognition_node +++ b/image_recognition_face_recognition/scripts/face_recognition_node @@ -43,7 +43,6 @@ class OpenfaceROS: # Openface ROS self._face_recognizer = Facenet_recognition() - # self._face_recognizer = FaceRecognizer(align_path, net_path) self._save_images_folder = save_images_folder self._topic_save_images = topic_save_images self._service_save_images = service_save_images @@ -134,22 +133,25 @@ class OpenfaceROS: images = [] labels = [] + # Added this line for testing with some labels labels = ["jason", "kona"] - # Call openface + + # Call facebet neural network in two stages face_recognitions = self._face_recognizer.face_detection(bgr_image) - dist, face_labelling = self._face_recognizer.detection_recognition(bgr_image, labels, train=True) + distance, labels_pred = self._face_recognizer.detection_recognition(bgr_image, labels, train=True) + # Fill recognitions recognitions = [] # rospy.loginfo("Face recognitions: %s", face_recognitions) - i = 0 + label_idx = 0 for fr in face_recognitions: import math - + face_recognition = [math.floor(xi) for xi in fr] if save_images: - label = face_labelling[i] + label = labels_pred[label_idx] roi_image = bgr_image[ face_recognition[2]: face_recognition[3], face_recognition[0]: face_recognition[1], @@ -157,14 +159,15 @@ class OpenfaceROS: image_writer.write_annotated(self._save_images_folder, roi_image, label, False) images.append(roi_image) labels.append(label) - label = face_labelling[i] - disti = dist[i] + label = labels_pred[label_idx] + distance_fr = distance[label_idx] recognitions.append( Recognition( categorical_distribution=CategoricalDistribution( unknown_probability=0.0, # TODO: When is it unknown? probabilities=[ - CategoryProbability(label=label, probability=1.0 / (disti + 0.001)) for l2 in face_recognition + # This line needs some changing + CategoryProbability(label=label, probability=1.0 / (distance_fr + 0.001)) for l2 in face_recognition ], ), roi=RegionOfInterest( @@ -175,7 +178,7 @@ class OpenfaceROS: ), ) ) - i = i + 1 + label_idx = label_idx + 1 annotated_original_image = image_writer.get_annotated_cv_image(bgr_image, recognitions) if save_images: @@ -194,7 +197,7 @@ class OpenfaceROS: return recognitions def _image_callback(self, image_msg): - # UNCOMMENT THOSE LINES NOW ITS COMMENTED FOR DEBUGGING + # Comment this exception for beeter debbuging try: recognitions = self._get_recognitions( image_msg, From 9ee08e604a626011daf4edbf2f5a52b5cfb2d7ba Mon Sep 17 00:00:00 2001 From: iasonth95 Date: Fri, 8 Mar 2024 13:54:27 +0100 Subject: [PATCH 4/6] remove unnecessary files --- .../log.txt | 195376 --------------- .../requirements.txt | 493 - .../test.py | 154 - 3 files changed, 196023 deletions(-) delete mode 100644 image_recognition_face_recognition/src/image_recognition_face_recognition/log.txt delete mode 100644 image_recognition_face_recognition/src/image_recognition_face_recognition/requirements.txt delete mode 100644 image_recognition_face_recognition/src/image_recognition_face_recognition/test.py diff --git a/image_recognition_face_recognition/src/image_recognition_face_recognition/log.txt b/image_recognition_face_recognition/src/image_recognition_face_recognition/log.txt deleted file mode 100644 index c39ed83b..00000000 --- a/image_recognition_face_recognition/src/image_recognition_face_recognition/log.txt +++ /dev/null @@ -1,195376 +0,0 @@ -[INFO] [1709671590.441693]: OpenfaceROS initialized: : 68 -[INFO] [1709671590.443011]: - dlib_align_path=/home/iason/openface/models/dlib/shape_predictor_68_face_landmarks.dat : 69 -[INFO] [1709671590.444208]: - openface_net_path=/home/iason/openface/models/openface/nn4.small2.v1.t7 : 70 -[INFO] [1709671590.445281]: - save_images_folder=/tmp/openface : 71 -[INFO] [1709671590.446391]: - topic_save_images=False : 72 -[INFO] [1709671590.447434]: - service_save_images=True : 73 -[INFO] [1709671590.448538]: - topic_publish_result_image=True : 74 -[INFO] [1709671590.449569]: - service_publish_result_image=True : 75 -tensor([[[[-0.4102, -0.4232, -0.4199, ..., -0.6133, -0.6211, -0.6211], - [-0.4023, -0.4076, -0.4036, ..., -0.5938, -0.6150, 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5.5022e-02, - 6.2635e-02, 8.9971e-02], - ..., - [-2.2822e-02, -2.5764e-02, -2.1257e-02, ..., -1.3581e-02, - -1.3764e-02, -7.3275e-03], - [-1.3147e-02, -1.5066e-02, -1.1592e-02, ..., -7.2691e-03, - -7.6844e-03, -3.0542e-03], - [-3.0500e-03, -3.1917e-03, -2.0891e-03, ..., 1.4627e-03, - -5.2088e-04, 1.7363e-02]], - - [[ 2.1842e-02, 2.1032e-02, 1.9697e-02, ..., 2.4740e-02, - 2.5878e-02, 2.5056e-02], - [ 2.1906e-02, 1.7408e-02, 1.4542e-02, ..., 2.5879e-02, - 2.2051e-02, 1.7832e-02], - [ 3.6159e-02, 1.7914e-02, 6.0023e-03, ..., 2.6063e-02, - 1.9051e-02, 1.5500e-02], - ..., - [ 1.0065e-02, 1.3269e-01, 1.5706e-01, ..., 1.2766e-02, - 1.2417e-01, 2.6893e-04], - [ 1.4856e-01, 2.5785e-01, 1.6636e-01, ..., 2.6152e-03, - 1.0829e-01, 4.4831e-03], - [ 8.9642e-02, 8.7655e-02, 1.2341e-02, ..., 7.3832e-03, - 4.4752e-03, 1.0576e-02]]], - - - [[[-4.5979e-01, -4.4834e-01, -4.4095e-01, ..., -9.4249e-01, - -4.8920e-01, -5.0692e-01], - [-4.5212e-01, -4.3622e-01, -4.2840e-01, ..., -9.7689e-01, - -5.3183e-01, 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4.3654e-02, 4.2510e-02, ..., 4.9251e-02, - 5.1935e-02, 6.1449e-02], - [ 4.0281e-02, 4.0578e-02, 3.9960e-02, ..., 5.0087e-02, - 5.9752e-02, 7.4980e-02], - ..., - [ 6.3796e-02, 8.7497e-02, 8.7254e-02, ..., 1.5384e-02, - 2.0188e-02, 1.4412e-02], - [ 6.8881e-02, 7.5677e-02, 6.1658e-02, ..., 3.1918e-02, - 5.0599e-02, 6.2933e-02], - [ 5.5977e-02, 4.9344e-02, 3.3598e-02, ..., 6.8299e-02, - 9.0821e-02, 9.4675e-02]], - - ..., - - [[ 2.7473e-02, 3.1682e-02, 3.4366e-02, ..., 2.8631e-01, - 1.7069e-02, 7.6023e-03], - [ 2.8372e-02, 3.6269e-02, 3.9809e-02, ..., 3.1638e-01, - 1.3425e-02, 8.4799e-05], - [ 2.5046e-02, 3.7868e-02, 4.7575e-02, ..., 3.7871e-01, - 1.1220e-01, 4.4693e-02], - ..., - [ 1.7619e-01, 1.5119e-01, 7.1186e-02, ..., 3.5625e-01, - 1.4739e-01, 2.1793e-02], - [ 3.1663e-01, 2.2678e-01, 1.4646e-01, ..., 2.7875e-01, - 1.3962e-01, 5.2945e-02], - [ 3.6281e-01, 1.8020e-01, 2.0124e-01, ..., 1.9028e-01, - 1.0137e-01, 3.8639e-02]], - - [[ 1.6642e-01, 1.6751e-01, 1.6653e-01, ..., -4.4584e-03, - 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8.6974e-02], - [ 5.6104e-01, 5.8962e-01, 7.8870e-02, ..., 1.8763e-03, - 9.3642e-02, 7.5876e-02]], - - [[ 3.0866e-02, 4.9373e-04, -6.2105e-03, ..., -3.9997e-02, - -5.1093e-02, -5.3665e-02], - [-1.9614e-03, -3.9706e-03, -1.4402e-02, ..., -3.7174e-02, - -4.2590e-02, -4.1859e-02], - [-6.5041e-03, -9.7130e-03, -2.4027e-02, ..., -2.6554e-02, - -2.6383e-02, -2.3102e-02], - ..., - [-2.5575e-02, -4.3776e-02, -5.7328e-02, ..., -2.8262e-03, - -7.3589e-03, -1.4239e-02], - [-2.5579e-02, -4.7245e-02, -6.6188e-02, ..., -1.2475e-02, - -1.2582e-02, -1.5091e-02], - [-2.6720e-02, -4.9131e-02, -6.9192e-02, ..., -2.3874e-02, - -2.1249e-02, -1.6289e-02]], - - [[ 3.0970e-02, 4.2318e-02, 6.0173e-02, ..., 6.8190e-02, - 3.2635e-02, 8.6266e-03], - [ 3.6369e-02, 6.4640e-02, 9.6876e-02, ..., 1.6558e-02, - 1.0837e-01, 2.8765e-01], - [ 4.7696e-02, 8.6694e-02, 1.2505e-01, ..., 2.6811e-01, - 4.6569e-01, 5.9513e-01], - ..., - [ 7.8515e-02, 9.0262e-02, 2.7890e-02, ..., 4.8128e-02, - 5.2836e-02, 4.6080e-02], - [ 9.0569e-02, 9.3894e-02, 2.7871e-02, ..., 5.4314e-02, - 4.6558e-02, 3.0474e-02], - [ 9.3976e-02, 9.0085e-02, 3.4560e-02, ..., 4.5071e-02, - 2.4815e-02, 9.9933e-03]]], - - - [[[-3.7197e-01, -3.1981e-01, -3.3752e-01, ..., -3.0667e-01, - -3.0894e-01, -1.9175e-01], - [-3.4820e-01, -3.1746e-01, -2.8888e-01, ..., -3.0507e-01, - -2.4134e-01, -1.4294e-01], - [-3.2728e-01, -3.4169e-01, -1.9078e-01, ..., -9.2536e-01, - -7.8387e-01, -7.3839e-01], - ..., - [-1.6223e-01, -2.0573e-01, -2.9876e-01, ..., -4.0652e-01, - -4.2133e-01, -4.2716e-01], - [-2.0205e-01, -2.2161e-01, -3.2013e-01, ..., -3.3129e-01, - -3.7444e-01, -4.0880e-01], - [-2.5333e-01, -2.6332e-01, -3.3755e-01, ..., -2.6700e-01, - -3.4792e-01, -3.7848e-01]], - - [[ 1.3232e-01, 1.3680e-01, 1.1865e-01, ..., 2.4671e-01, - 2.1412e-01, 1.9765e-01], - [ 1.0752e-01, 1.3992e-01, 9.3890e-02, ..., -2.8273e-02, - -2.8418e-02, -1.9602e-02], - [ 9.1051e-02, 1.0112e-01, 1.2834e-01, ..., -4.8101e-02, - -4.6139e-02, -3.8151e-02], - ..., - [ 2.0385e-01, 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5.2836e-02], - [ 9.3976e-02, 2.5376e-01, 2.3678e-01, ..., 7.3890e-02, - 5.6098e-02, 4.6558e-02]]], - - - [[[-1.9078e-01, 9.5373e-01, 9.5373e-01, ..., -1.0690e-01, - -2.4134e-01, -1.4294e-01], - [ 8.0825e-03, 9.5373e-01, 9.5373e-01, ..., -7.0075e-01, - -7.8387e-01, -7.3839e-01], - [ 8.8235e-01, 1.7671e+00, 6.5537e-01, ..., -7.0075e-01, - -9.7856e-01, -9.7856e-01], - ..., - [ 1.3265e-01, 1.3265e-01, -1.0113e-01, ..., -3.8600e-01, - -3.8600e-01, -4.8153e-01], - [-1.4779e-01, -1.4136e-01, -1.6235e-01, ..., -2.7557e-01, - -2.7557e-01, -3.7444e-01], - [-2.0205e-01, -2.8684e-01, -2.1774e-01, ..., -1.9724e-01, - -1.9724e-01, -3.4792e-01]], - - [[ 1.3992e-01, 1.2834e-01, 8.2668e-02, ..., 3.1642e-01, - 3.1642e-01, 2.1412e-01], - [ 2.0908e-01, 5.4565e-01, 7.0236e-01, ..., 5.8746e-01, - 6.5783e-01, 6.5783e-01], - [ 3.5149e-01, 3.7827e-01, 7.0236e-01, ..., 1.9077e-02, - 2.6847e-01, 3.8001e-01], - ..., - [ 3.0767e-01, 3.3650e-01, 3.0655e-01, ..., 9.3729e-02, - 7.8897e-02, 2.9097e-02], - [ 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7.0901e-01], - ..., - [ 4.1798e-02, 4.1798e-02, 2.4886e-02, ..., 2.7520e-02, - 2.7520e-02, 3.2412e-02], - [ 3.1335e-02, 2.4141e-02, 2.5869e-02, ..., 2.8759e-02, - 2.9202e-02, 2.9202e-02], - [ 3.1024e-02, 2.4141e-02, 2.5869e-02, ..., 3.1233e-02, - 3.1233e-02, 2.9202e-02]]], - - - [[[-4.2920e-01, -4.0136e-01, -4.1994e-01, ..., -3.2371e-01, - -3.9930e-01, -5.3449e-01], - [-3.5052e-01, -4.0136e-01, -3.9275e-01, ..., -3.8572e-01, - -3.8572e-01, -5.0088e-01], - [-2.4246e-01, -2.4246e-01, -4.0117e-01, ..., -3.5091e-01, - -3.5091e-01, -4.2473e-01], - ..., - [-2.8948e-01, -1.9473e-01, -1.9473e-01, ..., -6.0451e-01, - -4.4810e-01, -3.6946e-01], - [-3.4885e-01, -2.1035e-01, -2.1035e-01, ..., -4.8909e-01, - -4.3296e-01, -3.6946e-01], - [-3.4112e-01, -2.3035e-01, -2.3035e-01, ..., -4.0481e-01, - -4.4921e-01, -3.9411e-01]], - - [[ 3.3044e-01, 3.4840e-01, 2.2743e-01, ..., 2.1203e-01, - 2.1202e-01, 1.0486e-01], - [ 3.2158e-01, 3.8086e-01, 4.9665e-01, ..., 2.3613e-01, - 2.4430e-01, 2.4430e-01], - [ 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2.0374e-01, ..., 8.0601e-02, - -2.3338e-03, 7.1902e-02]], - - ..., - - [[ 2.7192e-01, 5.3189e-01, 4.5322e-01, ..., -1.5859e-02, - 6.1419e-02, 2.8265e-01], - [ 2.2663e-01, 2.1504e-01, 2.4733e-01, ..., 2.6470e-01, - 2.2786e-01, 3.9555e-01], - [ 2.6800e-01, 1.0419e-01, 3.7515e-02, ..., 3.5614e-01, - 2.4314e-01, 4.5241e-01], - ..., - [-1.9099e-04, -3.0936e-02, -3.5089e-03, ..., 1.0738e-01, - 1.6034e-01, 4.9459e-01], - [ 1.8805e-01, 1.5420e-01, 3.7953e-01, ..., 7.3072e-02, - 1.3125e-01, 3.7600e-01], - [ 2.7187e-01, 3.3469e-01, 3.7685e-01, ..., -1.1309e-02, - -1.0646e-02, 3.9416e-02]], - - [[ 2.5740e-03, 6.3536e-02, -1.9921e-03, ..., 2.6573e-02, - -3.3045e-05, 5.7697e-02], - [-2.9002e-04, 4.4727e-02, -2.0818e-03, ..., 1.8006e-02, - -3.3760e-04, 5.1246e-02], - [-9.3732e-04, -1.1194e-03, -3.6692e-03, ..., -1.1034e-03, - -2.7542e-03, -1.5439e-03], - ..., - [-2.0610e-03, -7.6499e-04, -2.6388e-03, ..., 3.6978e-02, - 1.2420e-01, 2.5249e-01], - [-2.7885e-03, -4.8200e-04, -7.8672e-04, ..., 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[1709671597.191502]: [[0.0]] min_of_emb_final : 89 -[INFO] [1709671597.192464]: [0.0] idx : 92 -[INFO] [1709671597.193356]: [0], min_index_list_per_emb : 95 -[INFO] [1709671597.194338]: [0.0], min_index_list : 96 -[INFO] [1709671597.195240]: ['jason'], [0.0] : 99 -[INFO] [1709671597.196127]: jason, ['jason'], label[0],labelling : 152 -[INFO] [1709671597.197053]: 0, idx_label : 157 -[INFO] [1709671597.197853]: Trained faces: : 189 -[INFO] [1709671597.198672]: Label: jason, Representations: 2 : 191 -[INFO] [1709671597.199523]: 1 : 161 -tensor([[[[-0.4492, -0.4362, -0.4238, ..., -0.6289, -0.6406, -0.6484], - [-0.4219, -0.4032, -0.3880, ..., -0.6367, -0.6402, -0.6445], - [-0.4355, -0.4036, -0.3848, ..., -0.6094, -0.6302, -0.6406], - ..., - [-0.9395, -0.8919, -0.7871, ..., -0.0352, -0.0534, -0.0938], - [-0.9635, -0.9023, -0.7500, ..., -0.0573, -0.0734, -0.0872], - [-0.9805, -0.8958, -0.6953, ..., -0.0801, -0.0846, -0.0898]], - - [[-0.4023, -0.4062, -0.3984, ..., -0.5801, -0.5651, -0.5508], 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8.0597e-02, 1.2063e-01, 1.2932e-01, ..., 6.9364e-02, - 7.6210e-02, 8.3521e-02], - ..., - [ 3.4934e-02, 3.9301e-02, 3.3925e-02, ..., 7.0545e-02, - 4.0662e-02, 9.3240e-03], - [ 3.1830e-02, 3.3361e-02, 2.6412e-02, ..., 1.0804e-01, - 6.3574e-02, 2.1506e-02], - [ 2.0064e-02, 2.4419e-02, 2.3310e-02, ..., 1.0958e-01, - 5.9106e-02, 1.8616e-03]]], - - - ..., - - - [[[-1.8328e+00, -1.0131e+00, -7.8239e-01, ..., 5.2720e-02, - 3.3498e-01, 7.1852e-01], - [-2.5474e+00, -1.4401e+00, -1.2710e+00, ..., -9.2255e-03, - 4.8022e-01, 3.5277e-01], - [-3.0824e+00, -2.0597e+00, -1.7784e+00, ..., 4.4583e-01, - 1.2551e+00, 7.3161e-01], - ..., - [-4.2533e-01, -3.4504e-01, -1.3035e+00, ..., -4.8146e-01, - -9.7846e-01, -1.3411e+00], - [-9.3881e-01, -3.2946e-01, -6.4979e-01, ..., -5.0121e-01, - -8.3093e-01, -1.3782e+00], - [-1.5011e+00, -5.2376e-01, -3.4565e-01, ..., -6.3489e-01, - -2.5334e-01, -8.1881e-01]], - - [[ 1.9174e-01, 1.0260e-01, 1.3616e-01, ..., -3.8168e-02, - -3.5655e-02, 4.1513e-02], - [-3.2196e-02, 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min_index_list_per_emb : 95 -[INFO] [1709671604.852951]: [0.1577223241329193], min_index_list : 96 -[INFO] [1709671604.855376]: ['jason'], [0.1577223241329193] : 99 -[INFO] [1709671604.857262]: jason, ['jason'], label[0],labelling : 152 -[INFO] [1709671604.858418]: 0, idx_label : 157 -[INFO] [1709671604.859411]: Trained faces: : 189 -[INFO] [1709671604.860345]: Label: jason, Representations: 3 : 191 -[INFO] [1709671604.861136]: 1 : 161 -tensor([[[[-0.4492, -0.4193, -0.3906, ..., -0.6562, -0.6510, -0.6348], - [-0.4310, -0.3911, -0.3659, ..., -0.6120, -0.6220, -0.6263], - [-0.3965, -0.3659, -0.3340, ..., -0.5820, -0.5924, -0.5977], - ..., - [-0.9512, -0.8841, -0.7598, ..., -0.0957, -0.0755, -0.0742], - [-0.9479, -0.9197, -0.8242, ..., -0.0703, -0.0716, -0.0651], - [-0.9766, -0.8958, -0.7461, ..., -0.0664, -0.0560, -0.0469]], - - [[-0.3730, -0.3711, -0.3730, ..., -0.5547, -0.5456, -0.5293], - [-0.4023, -0.3893, -0.3789, ..., -0.5677, -0.5655, -0.5586], - [-0.4160, -0.4089, -0.3730, ..., 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[1709671611.920411]: torch.Size([1, 512]), , embeddings size : 136 -[INFO] [1709671611.922250]: [0.1684955656528473, 0.1684955656528473, 0.2149129956960678] dist_per_emb : 79 -[INFO] [1709671611.923641]: [[[0.1684955656528473, 0.1684955656528473, 0.2149129956960678]]] dist_per_emb_final : 84 -[INFO] [1709671611.925103]: [0.1684955656528473] min_of_emb : 87 -[INFO] [1709671611.928719]: [[0.1684955656528473]] min_of_emb_final : 89 -[INFO] [1709671611.931761]: [0.1684955656528473] idx : 92 -[INFO] [1709671611.934478]: [0], min_index_list_per_emb : 95 -[INFO] [1709671611.936131]: [0.1684955656528473], min_index_list : 96 -[INFO] [1709671611.937288]: ['jason'], [0.1684955656528473] : 99 -[INFO] [1709671611.938338]: jason, ['jason'], label[0],labelling : 152 -[INFO] [1709671611.939588]: 0, idx_label : 157 -[INFO] [1709671611.940928]: Trained faces: : 189 -[INFO] [1709671611.942152]: Label: jason, Representations: 4 : 191 -[INFO] [1709671611.945514]: 1 : 161 -tensor([[[[-0.3809, -0.3906, 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3.4703e-01, 5.6660e-02, ..., 3.2475e-01, - 1.6774e-01, 3.9822e-01], - ..., - [ 7.2544e-01, 4.8323e-01, 2.1412e-01, ..., 8.8448e-02, - 1.0198e+00, 7.3953e-01], - [ 7.2544e-01, 4.8323e-01, 1.6909e-01, ..., 1.1962e-01, - 2.5267e-01, 2.3176e-01], - [ 1.9677e-01, 1.9677e-01, 1.9066e-02, ..., 1.0248e-01, - 9.8175e-02, 9.5691e-02]]], - - - [[[ 6.5198e-01, 6.3742e-01, -6.1423e-01, ..., -1.4567e-01, - 3.4820e-02, 1.1526e-01], - [ 1.4989e+00, 1.3821e+00, -9.2000e-01, ..., 1.9545e-02, - 1.1329e-01, 1.9488e-01], - [ 1.7095e+00, 1.3821e+00, -1.1411e+00, ..., 1.9545e-02, - 9.8049e-02, 1.2404e-01], - ..., - [ 1.2986e+00, 2.1553e+00, 7.1353e-02, ..., 3.4783e-01, - 9.2816e-01, 9.1174e-01], - [ 3.7902e-01, 1.5754e+00, 1.3234e-01, ..., 6.5569e-01, - 6.5569e-01, 3.2645e-01], - [-6.4015e-02, 3.0740e-01, 2.0654e-01, ..., 9.5214e-01, - 9.5214e-01, -5.3004e-01]], - - [[ 1.1863e-01, 3.8791e-02, 8.2674e-02, ..., 1.2144e-01, - 1.2216e-01, 1.3094e-01], - [ 1.4030e-01, -9.4815e-03, 2.2297e-01, ..., 1.1190e-01, - 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2.6502e-01, -1.1881e-01, - -2.4434e-01, -4.7826e-01, -2.5072e-01]]]], device='cuda:0') diff --git a/image_recognition_face_recognition/src/image_recognition_face_recognition/requirements.txt b/image_recognition_face_recognition/src/image_recognition_face_recognition/requirements.txt deleted file mode 100644 index 3f2d45f0..00000000 --- a/image_recognition_face_recognition/src/image_recognition_face_recognition/requirements.txt +++ /dev/null @@ -1,493 +0,0 @@ -absl-py==2.0.0 -actionlib==1.14.0 -addict==2.4.0 -angles==1.9.13 -anyio==4.0.0 -apturl==0.5.2 -arabic-reshaper==3.0.0 -argon2-cffi==23.1.0 -argon2-cffi-bindings==21.2.0 -asn1crypto==1.5.1 -asttokens==2.4.1 -astunparse==1.6.3 -async-lru==2.0.4 -atomicwrites==1.1.5 -attrs==23.1.0 -autobahn==17.10.1 -Automat==0.8.0 -Babel==2.13.1 -backcall==0.2.0 -backports.zoneinfo==0.2.1 -base_local_planner==1.17.3 -bcrypt==3.1.7 -beautifulsoup4==4.12.2 -black==24.2.0 -bleach==6.1.0 -blessed==1.20.0 -blinker==1.4 -blosc==1.7.0 -bondpy==1.8.6 -Brlapi==0.7.0 -cachetools==5.3.1 -camera-calibration-parsers==1.12.0 -catkin==0.8.10 -catkin-pkg==1.0.0 -catkin-pkg-modules==1.0.0 -catkin-tools==0.9.2 -cbor==1.0.0 -certifi==2023.7.22 -cffi==1.16.0 -chardet==3.0.4 -charset-normalizer==3.3.2 -click==8.1.7 -cloudpickle==1.3.0 -colorama==0.4.3 -coloredlogs==15.0.1 -comm==0.2.0 -command-not-found==0.3 -configobj==5.0.6 -constantly==15.1.0 -contourpy==1.1.1 -controller-manager==0.19.6 -controller-manager-msgs==0.19.6 -cryptography==41.0.4 -cssselect2==0.7.0 -cupshelpers==1.0 -cv-bridge==1.16.2 -cycler==0.12.1 -Cython==0.29.14 -dask==2.8.1+dfsg -dbus-python==1.2.16 -debugpy==1.8.0 -decorator==5.1.1 -defer==1.0.6 -defusedxml==0.7.1 -diagnostic-analysis==1.11.0 -diagnostic-common-diagnostics==1.11.0 -diagnostic-updater==1.11.0 -distlib==0.3.7 -distro==1.4.0 -distro-info==0.23+ubuntu1.1 -dlib==19.24.2 -docopt==0.6.2 -docutils==0.20.1 -duplicity==0.8.12.0 -dynamic-reconfigure==1.7.3 -empy==3.3.2 -entrypoints==0.3 -et-xmlfile==1.0.1 -exceptiongroup==1.2.0 -executing==2.0.1 -facenet-pytorch==2.5.3 -fasteners==0.14.1 -fastjsonschema==2.19.0 -filelock==3.13.1 -flake8==7.0.0 -flatbuffers==23.5.26 -fonttools==4.45.0 -fsspec==2023.10.0 -future==0.18.2 -gast==0.4.0 -gazebo_plugins==2.9.2 -gazebo_ros==2.9.2 -gencpp==0.7.0 -geneus==3.0.0 -genlisp==0.4.18 -genmsg==0.6.0 -gennodejs==2.0.2 -genpy==0.6.15 -google-auth==2.23.3 -google-auth-oauthlib==1.0.0 -google-pasta==0.2.0 -graphviz==0.20.1 -grpcio==1.59.0 -h5py==3.10.0 -hsrb_angle_sensors_alignment==0.18.1 -hsrb_autocharge==0.18.1 -hsrb_battery_notifier==0.13.1 -hsrb_bumper==0.18.1 -hsrb_dashboard==0.3.5 -hsrb_fetch_hanged==0.4.2 -hsrb_gradational_color==0.18.1 -hsrb_grasp_state_observer==0.30.0 -hsrb_interface_py==0.12.0 -hsrb_joint_impedance_control==0.30.0 -hsrb_move_to_locations==0.4.2 -hsrb_restart_cancel_task==0.4.2 -hsrb_rlp_interface_py==0.3.1 -hsrb_rqt_joint_impedance==0.3.5 -hsrb_short_speech_task==0.4.2 -hsrb_simple_actions==0.4.2 -hsrb_status_led==0.13.1 -hsrb_task_history_trigger==0.4.2 -hsrb_task_state_machines==0.4.2 -hsrb_task_states==0.4.2 -hsrb_task_util==0.4.2 -hsrb_timeopt_ros==0.30.0 -hsrb_trajectory_filter==0.30.0 -hsrb_voice_trigger_task==0.4.2 -hsrb_web_server==0.30.0 -html5lib==1.0.1 -httplib2==0.14.0 -humanfriendly==10.0 -hyperlink==19.0.0 -idna==3.4 -image-geometry==1.16.2 -imageio==2.4.1 -importlib-metadata==6.8.0 -importlib-resources==6.1.1 -incremental==16.10.1 -inquirer==3.1.3 -interactive-markers==1.12.0 -ipykernel==6.27.0 -ipython==8.12.3 -ipython_genutils==0.2.0 -ipywidgets==8.1.1 -isort==5.13.2 -jdcal==1.0 -jedi==0.19.1 -Jinja2==3.1.2 -joblib==0.14.0 -joint-state-publisher==1.15.1 -joint-state-publisher-gui==1.15.1 -json5==0.9.14 -jsonschema==4.20.0 -jsonschema-specifications==2023.11.1 -jupyter==1.0.0 -jupyter-console==6.6.3 -jupyter-events==0.9.0 -jupyter-lsp==2.2.0 -jupyter_client==8.6.0 -jupyter_core==5.5.0 -jupyter_server==2.11.0 -jupyter_server_terminals==0.4.4 -jupyterlab==4.0.9 -jupyterlab-pygments==0.2.2 -jupyterlab-widgets==3.0.9 -jupyterlab_server==2.25.2 -keras==2.13.1 -keyring==18.0.1 -kiwisolver==1.4.5 -language-selector==0.1 -laser_geometry==1.6.7 -launchpadlib==1.10.13 -lazr.restfulclient==0.14.2 -lazr.uri==1.0.3 -libclang==16.0.6 -locket==0.2.0 -lockfile==0.12.2 -louis==3.12.0 -lxml==4.5.0 -lz4==3.0.2+dfsg -macaroonbakery==1.3.1 -Mako==1.1.0 -Markdown==3.1.1 -markdown-it-py==3.0.0 -MarkupSafe==2.1.3 -matplotlib==3.7.4 -matplotlib-inline==0.1.6 -mccabe==0.7.0 -mdurl==0.1.2 -meld==3.20.2 -message-filters==1.16.0 -mistune==3.0.2 -mmengine==0.10.0 -mock==3.0.5 -monotonic==1.5 -more-itertools==4.2.0 -mpi4py==3.0.3 -mpmath==1.3.0 -msgpack==0.6.2 -mypy-extensions==1.0.0 -nbclient==0.9.0 -nbconvert==7.11.0 -nbformat==5.9.2 -nest-asyncio==1.5.8 -netifaces==0.10.4 -networkx==3.1 -nose @ git+https://github.com/tue-robotics/nose.git@d4c51ff09de8e1bb9545b732b09d1f14cbf515cc -notebook==7.0.6 -notebook_shim==0.2.3 -numexpr==2.8.6 -numpy==1.24.4 -nvidia-cublas-cu12==12.1.3.1 -nvidia-cuda-cupti-cu12==12.1.105 -nvidia-cuda-nvrtc-cu12==12.1.105 -nvidia-cuda-runtime-cu12==12.1.105 -nvidia-cudnn-cu12==8.9.2.26 -nvidia-cufft-cu12==11.0.2.54 -nvidia-curand-cu12==10.3.2.106 -nvidia-cusolver-cu12==11.4.5.107 -nvidia-cusparse-cu12==12.1.0.106 -nvidia-nccl-cu12==2.18.1 -nvidia-nvjitlink-cu12==12.3.101 -nvidia-nvtx-cu12==12.1.105 -oauthlib==3.1.0 -olefile==0.46 -onnxruntime-gpu==1.16.0 -opencv-python==4.8.1.78 -openface==0.2.1 -openpyxl==3.0.3 -opt-einsum==3.3.0 -oscrypto==1.3.0 -osrf-pycommon==2.0.2 -overrides==7.4.0 -packaging==23.2 -pandas==2.0.3 -pandocfilters==1.5.0 -paramiko==2.6.0 -parso==0.8.3 -partd==1.0.0 -pathspec==0.12.1 -pbr==5.4.5 -pexpect==4.8.0 -pickleshare==0.7.5 -Pillow==10.1.0 -pkg_resources==0.0.0 -pkgutil_resolve_name==1.3.10 -platformdirs==4.0.0 -pluggy==0.13.0 -prometheus-client==0.19.0 -prompt-toolkit==3.0.41 -protobuf==4.24.4 -psutil==5.9.6 -ptyprocess==0.7.0 -pure-eval==0.2.2 -py==1.8.1 -py-ubjson==0.14.0 -pyasn1==0.4.2 -pyasn1-modules==0.2.1 -pycairo==1.16.2 -pycodestyle==2.11.1 -pycparser==2.21 -pycryptodomex==3.6.1 -pycups==1.9.73 -pydot==1.4.1 -pyflakes==3.2.0 -Pygments==2.17.1 -PyGObject==3.36.0 -PyHamcrest==1.9.0 -pyHanko==0.20.1 -pyhanko-certvalidator==0.24.1 -PyJWT==1.7.1 -pymacaroons==0.13.0 -PyNaCl==1.3.0 -PyOpenGL==3.1.0 -pyOpenSSL==19.0.0 -pyparsing==3.1.1 -pypdf==3.16.4 -pypng==0.0.20 -PyQRCode==1.2.1 -PyQt5==5.14.1 -pyRFC3339==1.1 -pyserial==3.4 -pytest==4.6.9 -python-apt==2.0.1+ubuntu0.20.4.1 -python-bidi==0.4.2 -python-dateutil==2.8.2 -python-debian==0.1.36+ubuntu1.1 -python-editor==1.0.4 -python-gnupg==0.4.5 -python-json-logger==2.0.7 -python-qt-binding==0.4.4 -python-snappy==0.5.3 -PyTrie==0.2 -pytz==2023.3.post1 -PyWavelets==0.5.1 -pyxdg==0.26 -PyYAML==6.0.1 -pyzmq==25.1.1 -qrcode==7.4.2 -qt-dotgraph==0.4.2 -qt-gui==0.4.2 -qt-gui-cpp==0.4.2 -qt-gui-py-common==0.4.2 -qtconsole==5.5.1 -QtPy==2.4.1 -readchar==4.0.5 -referencing==0.31.0 -reportlab==3.6.13 -requests==2.31.0 -requests-oauthlib==1.3.1 -requests-unixsocket==0.2.0 -resource_retriever==1.12.7 -rfc3339-validator==0.1.4 -rfc3986-validator==0.1.1 -rich==13.7.0 -roman==2.0.0 -rosapi==0.11.17 -rosbag==1.16.0 -rosboost-cfg==1.15.8 -rosbridge-library==0.11.17 -rosbridge-server==0.11.17 -rosclean==1.15.8 -roscreate==1.15.8 -rosdep==0.22.2 -rosdep-modules==0.22.2 -rosdistro-modules==0.9.0 -rosgraph==1.16.0 -roslaunch==1.16.0 -roslib==1.15.8 -roslint==0.12.0 -roslz4==1.16.0 -rosmake==1.15.8 -rosmaster==1.16.0 -rosmsg==1.16.0 -rosnode==1.16.0 -rosparam==1.16.0 -rospkg==1.5.0 -rospkg-modules==1.5.0 -rospy==1.16.0 -rospy_message_converter==0.5.9 -rosservice==1.16.0 -rostest==1.16.0 -rostopic==1.16.0 -rosunit==1.15.8 -roswtf==1.16.0 -rpds-py==0.13.1 -rqt-console==0.4.12 -rqt-image-view==0.4.17 -rqt-logger-level==0.4.12 -rqt-moveit==0.5.11 -rqt-reconfigure==0.5.5 -rqt-robot-dashboard==0.5.8 -rqt-robot-monitor==0.5.15 -rqt-runtime-monitor==0.5.10 -rqt-rviz==0.7.0 -rqt-tf-tree==0.6.4 -rqt_action==0.4.9 -rqt_bag==0.5.1 -rqt_bag_plugins==0.5.1 -rqt_dep==0.4.12 -rqt_graph==0.4.14 -rqt_gui==0.5.3 -rqt_gui_py==0.5.3 -rqt_launch==0.4.9 -rqt_msg==0.4.10 -rqt_nav_view==0.5.7 -rqt_plot==0.4.13 -rqt_pose_view==0.5.11 -rqt_publisher==0.4.10 -rqt_py_common==0.5.3 -rqt_py_console==0.4.10 -rqt_robot_steering==0.5.12 -rqt_service_caller==0.4.10 -rqt_shell==0.4.11 -rqt_srv==0.4.9 -rqt_top==0.4.10 -rqt_topic==0.4.13 -rqt_web==0.4.10 -rsa==4.9 -rviz==1.14.20 -scikit-image==0.16.2 -scikit-learn==0.22.2.post1 -scipy==1.3.3 -screen-resolution-extra==0.0.0 -SecretStorage==2.3.1 -Send2Trash==1.8.2 -sensor-msgs==1.13.1 -service-identity==18.1.0 -simplejson==3.16.0 -sip==4.19.21 -six==1.16.0 -smach==2.5.2 -smach-ros==2.5.2 -smach-viewer==4.1.0 -smclib==1.8.6 -sniffio==1.3.0 -sound-play==0.3.17 -soupsieve==2.5 -spline_smoother==1.1.0 -SQLAlchemy==1.3.12 -ssh-import-id==5.10 -stack-data==0.6.3 -svglib==1.5.1 -sympy==1.12 -systemd-python==234 -tables==3.6.1 -tensorboard==2.13.0 -tensorboard-data-server==0.7.1 -tensorflow-estimator==2.13.0 -tensorflow-io-gcs-filesystem==0.34.0 -termcolor==2.3.0 -terminado==0.18.0 -tf==1.13.2 -tf-conversions==1.13.2 -tf2-geometry-msgs==0.7.7 -tf2-kdl==0.7.7 -tf2-py==0.7.7 -tf2-ros==0.7.7 -tf2-sensor-msgs==0.7.7 -tinycss2==1.2.1 -tmc_env_db==0.23.4 -tmc_eus_py==0.1.3 -tmc_eus_py_visualization_tools==0.1.3 -tmc_force_torque_sensor_compensation==0.32.3 -tmc_grasp_state_recognizer==0.32.3 -tmc_grid_map_server==0.33.0 -tmc_image_capturer==0.35.1 -tmc_imu_wheel_odometry==0.33.0 -tmc_journald==0.4.3 -tmc_lint==0.11.0 -tmc_move_base_and_joint_positions==0.24.3 -tmc_mqtt_bridge==0.23.0 -tmc_object_topology_viewer==0.23.4 -tmc_remote_exec==0.30.0 -tmc_ros_node_monitor==0.4.3 -tmc_rosbag_tools==0.23.0 -tmc_rosjulius==0.22.2 -tmc_rostest_utils==0.11.0 -tmc_sanyo_battery==0.27.1 -tmc_sentence_trigger==0.23.4 -tmc_simple_actions==0.24.3 -tmc_smach_action_bridge==0.23.4 -tmc_smach_states==0.24.3 -tmc_stereo_marker_recognizer==0.34.2 -tmc_task_fw==0.23.4 -tmc_timeopt==0.34.1 -tmc_timeopt_ros==0.34.1 -tmc_utils_py==0.23.0 -tmc_vision_util==0.35.1 -tmc_voice_action==0.22.2 -tmc_web_helper==0.30.0 -tomli==2.0.1 -toolz==0.9.0 -topic-tools==1.16.0 -torch==2.1.1 -torchvision==0.16.1 -tornado==6.3.3 -traitlets==5.13.0 -triton==2.1.0 -Twisted==18.9.0 -txaio==2.10.0 -typing_extensions==4.8.0 -tzdata==2023.3 -tzlocal==5.1 -u-msgpack-python==2.1 -ubuntu-advantage-tools==8001 -ubuntu-drivers-common==0.0.0 -ufw==0.36 -unattended-upgrades==0.1 -urdfdom-py==0.4.6 -uritools==4.0.2 -urllib3==2.1.0 -usb-creator==0.3.7 -virtualenv==20.24.5 -wadllib==1.3.3 -wcwidth==0.2.11 -webencodings==0.5.1 -websocket-client==1.6.4 -Werkzeug==3.0.0 -widgetsnbextension==4.0.9 -wrapt==1.15.0 -wsaccel==0.6.2 -wxPython==4.0.7 -xacro==1.14.16 -xdot==1.1 -xhtml2pdf==0.2.11 -xkit==0.0.0 -xlrd==1.1.0 -xlwt==1.3.0 -yapf==0.40.2 -zipp==3.17.0 -zope.interface==4.7.1 diff --git a/image_recognition_face_recognition/src/image_recognition_face_recognition/test.py b/image_recognition_face_recognition/src/image_recognition_face_recognition/test.py deleted file mode 100644 index 394f9a61..00000000 --- a/image_recognition_face_recognition/src/image_recognition_face_recognition/test.py +++ /dev/null @@ -1,154 +0,0 @@ -# Online Python compiler (interpreter) to run Python online. -# Write Python 3 code in this online editor and run it. -print("Hello world") -import logging -logging.basicConfig(level=logging.INFO, format='%(levelname)s - %(message)s') - -_trained_faces = [] -class TrainedFace: - def __init__(self, label): - self.label = label - self.representations = [] - - def get_label(self) -> str : return self.label - -embeddings = [40,400] - -_trained_faces.append(TrainedFace('jason')) -_trained_faces.append(TrainedFace('kona')) -_trained_faces[0].representations.append(50) -_trained_faces[0].representations.append(40) - -_trained_faces[1].representations.append(300) -_trained_faces[1].representations.append(407) -_trained_faces[1].representations.append(700) -for trained_face in _trained_faces: - print(f"Label: {trained_face.label}, Representations: {trained_face.representations}") - -#dist = [(e1.representations[e3] - e2) for e1 in _trained_faces]for e3 in range(len(e1.representations)) for e2 in embeddings] -dist_per_emb_final = [] -dist = [] -dist_per_emb = [] - -min_of_emb_final = [] - -min_index_list_per_emb = [] -min_index_list= [] - -for e2 in embeddings: - for e1 in _trained_faces: - for e3 in (e1.representations): - dist_per_emb.append(abs(e3 - e2)) - dist.append(dist_per_emb) - logging.info(f"{dist_per_emb} dist_per_emb") - print(dist_per_emb,'dist_per_emb') - - dist_per_emb = [] - dist_per_emb_final.append(dist) - dist = [] - -print(dist_per_emb_final,'dist_per_emb_final') -for i in dist_per_emb_final: - min_of_emb = [min(j) for j in i] - print(min_of_emb,'min_of_emb') - min_of_emb_final.append(min_of_emb) -print(min_of_emb_final,'min_of_emb_final') - - -for idx in min_of_emb_final: - print(idx, 'min_index_list_per_emb') - min_index_list_per_emb.append(idx.index(min(idx))) - min_index_list.append(min(idx)) - print(idx.index(min(idx)),'minimum index') -print(min_index_list,'min_index_list') - -labelling = [_trained_faces[i].get_label() for i in min_index_list_per_emb] -print(labelling, min_index_list) - - -def _get_dists(self, embeddings): - ''' - HERE WE NEED TO FIND THE SHOURTEST EUKLIDEAN DISTANCE BETWEEN ALL OUR VECTORS - SPLIT THE FACES WE HAVE DETECT AND APPEND IT IN THE LIST - THEN FOR EVERY FACE WE DETECT IN embeddedings[i] WE NEED TO CHECK THE CLOSEST DETECTION WITH THE LIST - ''' - dist_per_emb_final = [] - dist = [] - dist_per_emb = [] - - min_of_emb_final = [] - - min_index_list_per_emb = [] - min_index_list= [] - - for e2 in embeddings: - for e1 in _trained_faces: - for e3 in (e1.representations): - dist_per_emb.append(abs(e3 - e2)) - dist.append(dist_per_emb) - print(dist_per_emb,'dist_per_emb') - dist_per_emb = [] - dist_per_emb_final.append(dist) - dist = [] - - print(dist_per_emb_final,'dist_per_emb_final') - for i in dist_per_emb_final: - min_of_emb = [min(j) for j in i] - print(min_of_emb,'min_of_emb') - min_of_emb_final.append(min_of_emb) - print(min_of_emb_final,'min_of_emb_final') - - - for idx in min_of_emb_final: - print(idx, 'min_index_list_per_emb') - min_index_list_per_emb.append(idx.index(min(idx))) - min_index_list.append(min(idx)) - - labelling = [_trained_faces[i].get_label() for i in min_index_list_per_emb] - print(labelling, min_index_list) - - return dist, labelling - - - -def _get_dists(self, embeddings): - ''' - HERE WE NEED TO FIND THE SHOURTEST EUKLIDEAN DISTANCE BETWEEN ALL OUR VECTORS - SPLIT THE FACES WE HAVE DETECT AND APPEND IT IN THE LIST - THEN FOR EVERY FACE WE DETECT IN embeddedings[i] WE NEED TO CHECK THE CLOSEST DETECTION WITH THE LIST - ''' - dist = [] - min_index=[] - labelling = [] - #this is tries for l2 norm but non needed since this technique uses euclidean distanses. - #dist.append(min([[np.subtract(vector_a, embeddings[i,:]) for vector_a in self._trained_faces] for i in range(embeddings.size(0))])) - #dist.append(min([[np.dot(vector_a - embeddings[i,:], vector_a - embeddings[i,:]) for vector_a in self._trained_faces] for i in range(embeddings.size(0))])) - - #for face_recognition in embeddings: - #if save_images: - #this is only for one face stored in every label in self._trained_faces THIS THIS THIS - #dist = [[(e1.representations[0] - e2).norm().item() for e2 in embeddings] for e1 in self._trained_faces] - #dist = [(e1.representations[e3] - e2).norm().item() for e1 in self._trained_faces for e3 in range(len(e1.representations)) for e2 in embeddings] - # dist = [[(e1.representations[e3] - e2).norm().item() for e2 in embeddings] for e1 in self._trained_faces for e3 in range(len(e1.representations))] - #dist = [[[(e1.representations[e3] - e2).norm().item() for e1 in self._trained_faces] for e3 in range(len(self._trained_faces[0].representations))] for e2 in embeddings] - ll = [] - for e2 in embeddings: - for e1 in self._trained_faces: - for e3 in (e1.representations): - ll.append((e3 - e2).norm().item()) - dist.append(ll) - ll = [] - - print(dist, '<-- Dist') - distance = [min(dist[index]) for index in range(len(dist))] - print(min(dist),'minsistmist') - print(distance, '<-- distance') - # get the index of the minimum distance (this would correspond to the appropriate label) - min_index = [idx.index(min(idx)) for idx in dist] - print(min_index,'min index') - - labelling = [self._trained_faces[i].get_label() for i in min_index] - #labelling = [np.argmin(dist[index]) for index in range(len(dist))] - print(distance,labelling,'<--Distance with the close label is') - - return dist, labelling \ No newline at end of file From 1c3d480587aab7992922717de2ccb230b78bed67 Mon Sep 17 00:00:00 2001 From: iasonth95 Date: Mon, 11 Mar 2024 16:53:57 +0100 Subject: [PATCH 5/6] changed ReadME.md and get_face_recognition in order to make it work with facenet model --- image_recognition_face_recognition/README.md | 43 ++++++++----------- .../scripts/get_face_recognition | 27 +++++++----- 2 files changed, 34 insertions(+), 36 deletions(-) diff --git a/image_recognition_face_recognition/README.md b/image_recognition_face_recognition/README.md index 33e31446..fde94d30 100644 --- a/image_recognition_face_recognition/README.md +++ b/image_recognition_face_recognition/README.md @@ -1,34 +1,32 @@ # image_recognition_face_recognition -NEEDS WORK +TO DO -Face recognition with use of Openpose (https://cmusatyalab.github.io/openface/) +Face recognition with use of Facenet (https://github.com/timesler/facenet-pytorch/tree/master) +Paper can be found: [paper](https://arxiv.org/pdf/1503.03832.pdf) ## Installation See https://github.com/tue-robotics/image_recognition -Make sure that openface is correctly installed. Installation instructions can be found here: https://cmusatyalab.github.io/openface/setup/. Make sure you have installed **CUDA8**. CUDA10 is not working: https://github.com/torch/torch7/issues/1180 +Make sure you have installed **CUDA8**. -```bash -export TORCH_INSTALL_PATH=~/torch -export OPENFACE_INSTALL_PATH=~/openface -git clone https://github.com/torch/distro.git ~/torch --recursive && \ -cd $TORCH_INSTALL_PATH && bash install-deps && ./install.sh && \ -for NAME in dpnn nn optim optnet csvigo cutorch cunn fblualib torchx tds; do $TORCH_INSTALL_PATH/install/bin/luarocks install $NAME; done && \ -sudo -H pip install dlib && \ -git clone https://github.com/cmusatyalab/openface.git $OPENFACE_INSTALL_PATH && \ -cd $OPENFACE_INSTALL_PATH && sudo -H python setup.py install && \ -./models/get-models.sh -``` +bash commends will be available when merged ## How-to +### Run Face Recognition Node + +Run the command why using your camera as an input (use roscamera node): + + rosrun cv_camera cv_camera_node + rosrun image_recognition_face_recognition face_recognition_node image:=/cv_camera/image_raw + ### ROS Node -Run the image_recognition_openface node in one terminal (Specify the dlib and openface_net path as ROS parameter): +Run the image_recognition_face_detection node in one terminal (Specify the dlib and openface_net path as ROS parameter): - rosrun image_recognition_openface face_recognition_node + rosrun image_recognition_face_detection face_recognition_node Run the rqt annotation client (https://github.com/tue-robotics/image_recognition_rqt) @@ -58,6 +56,7 @@ Again configure the service you want to call with the gear-wheel in the top-righ You will see that the result of the detection will prompt in a dialog combo box. Also the detections will be drawn on the image. + ### Command line Command line interface to test the detection / recognition based on an image: @@ -66,14 +65,6 @@ Command line interface to test the detection / recognition based on an image: Run the command on an example image: - rosrun image_recognition_openface get_face_recognition `rospack find image_recognition_openface`/doc/example.png - -This will lookup this image in the image_recognition_openface/doc folder and perform recognitions - -![Example](doc/example.png) - -Output: - - [RecognizedFace(roi=(374, 188, 108, 123), l2_distances=[]), RecognizedFace(roi=(72, 147, 88, 105), l2_distances=[]), RecognizedFace(roi=(377, 95, 74, 86), l2_distances=[]), RecognizedFace(roi=(149, 26, 74, 86), l2_distances=[]), RecognizedFace(roi=(52, 47, 75, 86), l2_distances=[]), RecognizedFace(roi=(246, 115, 88, 102), l2_distances=[]), RecognizedFace(roi=(0, 0, 42, 60), l2_distances=[]), RecognizedFace(roi=(336, 33, 74, 86), l2_distances=[]), RecognizedFace(roi=(228, 0, 62, 60), l2_distances=[])] + rosrun image_recognition_face_recognition get_face_recognition `rospack find image_recognition_face_recognition`/doc/example.png -Since no faces were trained, the l2_distances will not be calculated of-course. +![Example](doc/example.png) \ No newline at end of file diff --git a/image_recognition_face_recognition/scripts/get_face_recognition b/image_recognition_face_recognition/scripts/get_face_recognition index c2982e14..b34c6e2a 100755 --- a/image_recognition_face_recognition/scripts/get_face_recognition +++ b/image_recognition_face_recognition/scripts/get_face_recognition @@ -5,8 +5,9 @@ import argparse import cv2 from image_recognition_msgs.msg import Recognition -from image_recognition_openface.face_recognizer import FaceRecognizer +from image_recognition_face_recognition.facenet_recognition import Facenet_recognition # Assign description to the help doc +import math from sensor_msgs.msg import RegionOfInterest from image_recognition_util import image_writer @@ -28,20 +29,26 @@ args = parser.parse_args() img = cv2.imread(args.image) # Create openface interface -face_recognizer = FaceRecognizer(args.align_path, args.net_path) +face_recognizer = Facenet_recognition() if args.db: face_recognizer.restore_trained_faces(args.db) -recognized_faces = face_recognizer.recognize(img) +recognized_faces = face_recognizer.face_detection(img) print(recognized_faces) -annotated_original_image = image_writer.get_annotated_cv_image(img, [Recognition( - roi=RegionOfInterest( - x_offset=f.roi.x_offset, - y_offset=f.roi.y_offset, - width=f.roi.width, - height=f.roi.height + +recognitions = [] +for fr in recognized_faces: + face_recognition = [math.floor(xi) for xi in fr] + recognitions.append(Recognition( + roi=RegionOfInterest( + x_offset=face_recognition[0], + y_offset=face_recognition[1], + width=face_recognition[2] - face_recognition[0], + height=face_recognition[3] - face_recognition[1], + ) ) -) for f in recognized_faces]) +) + annotated_original_image = image_writer.get_annotated_cv_image(img, recognitions) cv2.imshow("result", annotated_original_image) cv2.waitKey() From ab780eecf16c21b00c074adad9d61ecd7478399c Mon Sep 17 00:00:00 2001 From: Matthijs van der Burgh Date: Mon, 11 Mar 2024 18:57:47 +0100 Subject: [PATCH 6/6] (face_recognition) fix missing newline at EOF --- image_recognition_face_recognition/scripts/train_from_images | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/image_recognition_face_recognition/scripts/train_from_images b/image_recognition_face_recognition/scripts/train_from_images index f735a726..11abd33e 100755 --- a/image_recognition_face_recognition/scripts/train_from_images +++ b/image_recognition_face_recognition/scripts/train_from_images @@ -67,4 +67,4 @@ if __name__ == '__main__': parser.add_argument('-v', '--verbose', action='store_true') args = parser.parse_args() - main(**vars(args)) \ No newline at end of file + main(**vars(args))