I am keeping the complete loop in one block of code to avoid indentation problems and confusion. We make four primary contributions to the fields of deep learning and social sciences: (1) We curate an original face detection data set (IllusFace 1.0) by manually labeling 5,403 illustrated faces with bounding boxes. This guide will show you how to apply transformations to an object detection dataset following the tutorial from Albumentations. FaceNet is a face recognition system developed in 2015 by researchers at Google that achieved then state-of-the-art results on a range of face recognition benchmark datasets. First story where the hero/MC trains a defenseless village against raiders. The following are the imports that we will need along the way. All I need to do is just create 60 more cropped images with no face in them. The dataset contains rich annotations, including occlusions, poses, event categories, and face bounding boxes. We will be addressing that issue in this article. The VGG Face2 dataset is available for non-commercial research purposes only. A face recognition system is designed to identify and verify a person from a digital image or video frame, often as part of access control or identify verification solutions. Bounding boxes are one of the most popularand recognized tools when it comes to image processing for image and video annotation projects. We are all set with the prerequisites and set up of our project. So, we used a face detection model to The learned characteristics are in the form of distribution models or discriminant functions that is applied for face detection tasks. :param format: One of 'coco', 'voc', 'yolo' depending on which final bounding noxes are formated. You can unsubscribe anytime. Just check for draw_detection method. Face detection is one of the most widely used computervision applications and a fundamental problem in computer vision and pattern recognition. In other words, were naturally good at facial recognition and analysis. Why did it take so long for Europeans to adopt the moldboard plow? # get the fps Then, I shuffled up the images with an index: since I loaded positive images first, all the positive images were in the beginning of the array. MTCNN stands for Multi-task Cascaded Convolutional Networks. I am using a cascade classifier (haarcascades) It shows the picture, not in grayscale (full color) and will not draw the bounding boxes. Green bounding-boxes represent the detection results. Locating a face in a photograph refers to finding the coordinate of the face in the image, whereas localization refers to demarcating the extent of the face, often via a bounding box around the face. Note that in both cases, we are passing the converted image_array as arguments as we are using OpenCV functions. This is required as we will be using OpenCV functions for drawing the bounding boxes, plotting the landmarks, and visualizing the image as well. Powerful applications and use cases. Yours may vary depending on the hardware. component is optimized separately, making the whole detection pipeline often sub-optimal. Work fast with our official CLI. It will contain two small functions. There is also the problem of a few false positives as well. How to rename a file based on a directory name? In this tutorial, we carried face and facial landmark detection using Facenet PyTorch in images and videos. frame = utils.plot_landmarks(landmarks, frame) We will release our modifications soon. Same thing, but in darknet/YOLO format. Darknet annotations for "face" and "person", A CSV for each image in the Train2017 and Val2017 datasets. In the right column, the same images are shown but with the bounding boxes predicted by the YOLOv7 model. The above figure shows an example of what we will try to learn and achieve in this tutorial. Projects Universe Documentation Forum. avg_fps = total_fps / frame_count We can see that the MTCNN model also detects faces in low lighting conditions. We use the above function to plot the facial landmarks on the detected faces. These are huge datasets containing millions of face images, especially the VGGFace2 dataset. Download this Dataset. Used for identifying returning visits of users to the webpage. return { topRow: face.top_row * height, leftCol: face.left_col * width, bottomRow: (face.bottom_row * height) - (face.top_row * height . Multiple face detection techniques have been introduced. Feature-based methods try to find invariant features of faces for detection. Why are there two different pronunciations for the word Tee? The FaceNet system can be used broadly thanks to multiple third-party open source implementations of the model and the availability of pre-trained models. Let's take a look at what each of these arguments means: scaleFactor: How much the image size is reduced at each image scale. How to add webcam selection to official mediapipe face detection solution? cv2.imshow(Face detection frame, frame) This cookie is used by Zoho Page Sense to improve the user experience. Great Gaurav. Introduced by Xiangxin Zhu et al. Face detection is a computer technology that determines the location and size of a human, face in digital images. The cookies is used to store the user consent for the cookies in the category "Necessary". This folder contains three images and two video clips. import time During training, they optimise detection models by reducing face classification and bounding-box regression losses in a supervised learning manner. Each face image is labeled with at most 6 landmarks with visibility labels, as well as a bounding box. Find size of rotated rectangle that covers orginal rectangle. Detect API also allows you to get back face landmarks and attributes for the top 5 largest detected faces. Volume, density and diversity of different human detection datasets. CERTH Image . The next block of code will contain the whole while loop inside which we carry out the face and facial landmark detection using the MTCNN model. Please 66 . Face detection is becoming more and more important for marketing, analyzing customer behavior, or segment-targeted advertising. Face recognition is a method of identifying or verifying the identity of an individual using their face. original size=(640,480), bounding box=[ x, y, w, h ] I know use the argument: transform = transforms.Resize([416,416]) can resize the images, but how can I modify those bounding box coordinates efficiently? All rights reserved. Checkout for drawing_utils contents: Just check for draw_detection method. Spatial and Temporal Restoration, Understanding and Compression Team. Introduction 2. These cookies are used to measure and analyze the traffic of this website and expire in 1 year. We will write the code for each of the three scripts in their respective subsections. Note: We chose a relatively low threshold so that we could process all the images once, and decide Based on CSPDarknet53, the Focus structure and pyramid compression channel attention mechanism are integrated, and the network depth reduction strategy is adopted to build a PSA-CSPDarknet-1 . How could magic slowly be destroying the world? Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. Connect and share knowledge within a single location that is structured and easy to search. We also interpret facial expressions and detect emotions automatically. Using the code from the original file, I built the P-Net. From this section onward, we will tackle the coding part of the tutorial. The MTCNN model is working quite well. A Large-Scale Dataset for Real-World Face Forgery Detection. Would Marx consider salary workers to be members of the proleteriat? Original . Faces for COCO plus people. Parameters :param image: Image, type NumPy array. Site Detection Image Dataset. Note that there was minimal QA on these bounding boxes, but we find The applications of this technology are wide-ranging and exciting. Steps to Solve the Face Detection Problem In this section, we will look at the steps that we'll be following, while building the face detection model using detectron2. I wonder if switching back and forth like this improves training accuracy? Our own goal for this dataset was to train a face+person yolo model using COCO, so we have We release the VideoCapture() object, destroy all frame windows, calculate the average FPS, and print it on the terminal. Figure 2 shows the MTCNN model architecture. We discuss how a large dataset can be collected and annotated using human annotators and deep networks, Face Images 22,000 videos + 367,888 images, Identities 8,277 in images + 3,100 in video. It includes 205 images with 473 labeled faces. The IoUs between . These cookies ensure basic functionalities and security features of the website, anonymously. This makes the process slower, but lowers the risk of GPU running out of memory. Making statements based on opinion; back them up with references or personal experience. Hence, appearance-based methods rely on machine learning and statistical analysis techniques to find the relevant characteristics of face and no-face images. You can also uncomment lines 5 and 6 to see the shapes of the bounding_boxes and landmarks arrays. yolov8 dataset by Bounding box. Datasets used for the experiment and exploratory data analysis This section describes the datasets used for evaluating the proposed model and exploratory data analysis carried out on the datasets. in Face detection, pose estimation, and landmark localization in the wild. You can find the source code for this tutorial at the dotnet/machinelearning-samples GitHub repository. Roboflow Universe Bounding box yolov8 . DARK FACE training/validation images and labels. Description iQIYI-VID, the largest video dataset for multi-modal person identification. Press or ` to cycle points and use the arrow keys or shift + arrow keys to adjust the width or height of a box. frame = utils.draw_bbox(bounding_boxes, frame) Computer Vision Convolutional Neural Networks Deep Learning Face Detection Face Recognition Keypoint Detection Machine Learning Neural Networks Object Detection OpenCV PyTorch. This cookie is used to distinguish between humans and bots. The website codes are borrowed from WIDER FACE Website. If an image has no detected faces, it's represented by an empty CSV. Learn more about other popular fields of computer vision and deep learning technologies, for example, the difference between supervised learning and unsupervised learning. Your email address will not be published. I need a 'standard array' for a D&D-like homebrew game, but anydice chokes - how to proceed? sign in And 1 That Got Me in Trouble. Based on the extracted features, statistical models were built to describe their relationships and verify a faces presence in an image. As the name suggests, a bounding box is a rectangular or square box that bounds the object of interest and can be used to identify the relative position of the object of interest in a video or image. Description MALF is the first face detection dataset that supports fine-gained evaluation. Lines 28-30 then detect the actual faces in our input image, returning a list of bounding boxes, or simply the starting and ending (x, y) -coordinates where the faces are in each image. To train deep learning models, large quantities of data are required. Instead of defining 1 loss function for both face detection and bounding box coordinates, they defined a loss function each. difficult poses, and low image resolutions. We choose 32,203 images and label 393,703 faces with a high degree of variability in scale, pose and occlusion as depicted in the sample images. - "Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild" One example is in marketing and retail. 1. . AFW ( Annotated Faces in the Wild) is a face detection dataset that contains 205 images with 468 faces. 10000 images of natural scenes, with 37 different logos, and 2695 logos instances, annotated with a bounding box. It contains 200,000+ celebrity images. two types of approaches to detecting facial parts, (1) feature-based and (2) image-based approaches. Explore use cases of face detection in smart retail, education, surveillance and security, manufacturing, or Smart Cities. Then, I read in the positive and negative images, as well as the set of bounding box coordinates, each as an array. The model is really good at detecting faces and their landmarks. Note that we are also initializing two variables, frame_count, and total_fps. I ran the training loop. At least, what it lacks in FPS, it makes up with the detection accuracy. 6 exports. single csv where each crowd is a detected face using yoloface. That is not much and not even real-time as well. The UMDFaces dataset is available for non-commercial research purposes only. Some examples of YOLOv7 detections on LB test images. cap.release() The data can be used for tasks such as kinship verification . The dataset contains, Learn more about other popular fields of computer vision and deep learning technologies, for example, the difference between, ImageNet Large Scale Visual Recognition Challenge, supervised learning and unsupervised learning, Face Blur for Privacy-Preserving in Deep Learning Datasets, High-value Applications of Computer Vision in Oil and Gas (2022), What is Natural Language Processing? Function accepts an image and bboxes list and returns the image with bounding boxes drawn on it. Most people can recognize about 5,000 faces, and it takes a human 0.2 seconds to recognize a specific one. SCface is a database of static images of human faces. Just like I did, this model cropped each image (into 12x12 pixels for P-Net, 24x24 pixels for R-Net, and 48x48 pixels for O-Net) before the training process. I'm using the claraifai API I've retrieved the regions for the face to form the bounding box but actually drawing the box gives me seriously off values as seen in the image. Landmarks/Bounding Box: Estimated bounding box and 5 facial landmarks; Per-subject Samples: 362.6; Benchmark Overlap Removal: N/A; Paper: Q. Cao, L. Shen, W. Xie, O. M. Parkhi, A. Zisserman VGGFace2: A dataset for recognising face across pose and age International Conference on Automatic Face and Gesture Recognition, 2018. These two will help us calculate the average FPS (Frames Per Second) while carrying out detection even if we discontinue the detection in between. It does not store any personal data. To learn more, see our tips on writing great answers. To detect the facial landmarks as well, we have to pass the argument landmarks=True. Meaning of "starred roof" in "Appointment With Love" by Sulamith Ish-kishor. You need line with cv2.rectangle call. out.write(frame) The first one is draw_bbox() function. We will not go into much details of the MTCNN network as this is out of scope of this tutorial. Mainly because the human face is a dynamic object and has a high degree of variability in its appearance. fps = 1 / (end_time start_time) It records data about the user's navigation and behavior on the website. For questions and result submission, please contact Wenhan Yang at yangwenhan@pku.edu.com. Now, we have all the things from the MTCNN model that we need. We need the OpenCV and PIL (Python Imaging Library) computer vision libraries as well. [0, 1] and another where we do not clip them meaning the bounding box may partially fall beyond This is done to maintain symmetry in image features. Bounding boxes are the key elements and one of the primary image processing tools for video annotation projects. Prepare and understand the data Keep it up. Deploy a Model Explore these datasets, models, and more on Roboflow Universe. Rather than go through the tedious process of processing data for RNet and ONet again, I found this MTCNN model on Github which included training files for the model. For simplicitys sake, I started by training only the bounding box coordinates. Most probably, it would have easily detected those if the lighting had been a bit better. Open up your command line or terminal and cd into the src directory. bounding_boxes, conf, landmarks = mtcnn.detect(pil_image, landmarks=True) cv2.destroyAllWindows() 53,151 images that didn't have any "person" label. To match Caltech cropped images, the original LFW image is cropped slightly larger than the detected bounding box. 1619 Broadway, New York, NY, US, 10019. I'm not sure whether below worth to be an answer, so put it here. Description Digi-Face 1M is the largest scale synthetic dataset for face recognition that is free from privacy violations and lack of consent. Image-based methods try to learn templates from examples in images. he AFW dataset is built using Flickr images. Site Detection dataset by Bounding box. Additionally, we provided a unique set of 789 paired low-light/normal-light images captured in controllable real lighting conditions (but unnecessarily containing faces), which can be used as parts of the training data at the participants' discretization. . Face Detection Workplace Safety Object Counting Activity Recognition Select a deep learning model Deep learning is a subset of machine learning. Zoho sets this cookie for the login function on the website. These cookies will be stored in your browser only with your consent. You can find the original paper here. The dataset contains rich annotations, including occlusions, poses, event categories, and face bounding boxes. The dataset contains rich annotations, including occlusions, poses, event categories, and face bounding boxes. The cookie stores information anonymously and assigns a randomly generated number to recognize unique visitors. Powering all these advances are numerous large datasets of faces, with different features and focuses. On this video I was getting around 7.6 FPS. (frame_width, frame_height)) FACE Detection using PyTorch (F-RCNN) | by Inder Preet Singh | Medium 500 Apologies, but something went wrong on our end. To generate face labels, we modified yoloface, which is a yoloV3 architecture, implemented in # get the start time The images were taken in an uncontrolled indoor environment using five video surveillance cameras of various qualities. Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. Universe Public Datasets Model Zoo Blog Docs. Last updated 2 months ago. Facenet PyTorch is one such implementation in PyTorch which will make our work really easier. Just make changes to utils.py also whenever len of bounding boxes and landmarks return null make it an If condition. Universe Public Datasets Model Zoo Blog Docs. It is a cascaded convolutional network, meaning it is composed of 3 separate neural networks that couldnt be trained together. These images and videos are taken from Pixabay. Face detection is the task of finding (boundaries of) faces in images. These datasets prove useful for training face recognition deep learning models. a. FWOM: A python crawler tool is used to crawl the front-face images of public figures and normal people alike from massive Internet resources. This paper proposes a simple yet effective oriented object detection approach called H2RBox merely using horizontal box annotation . Now lets see how the model performs with multiple faces. If you see errors, please let us know. In addition, for R-Net and O-Net training, they utilized hard sample mining. When reviewing images or videos that include bounding boxes, press Tab to cycle between selected bounding boxes quickly. The team that developed this model used the WIDER-FACE dataset to train bounding box coordinates and the CelebA dataset to train facial landmarks. automatically find faces in the COCO images and created bounding box annotations. Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. This detects the faces, and provides us with bounding boxes that surrounds the faces. The next few lines of code set the computation device and initialize the MTCNN model from the facenet_pytorch library. from PIL import Image This is because it is not always feasible to train such models on such huge datasets as VGGFace2. Refresh the page, check Medium 's site status, or find something. To ensure a better training process, I wanted about 50% of my training photos to contain a face. It accepts the image/frame and the landmarks array as parameters. VOC-360 can be used to train machine learning models for object detection, classification, and segmentation. (2) We train two AutoML-based face detection models for illustrations: (i) using IllusFace 1.0 (FDAI); (ii) using save_path = f../outputs/webcam.mp4 github.com/google/mediapipe/blob/master/mediapipe/framework/, https://github.com/google/mediapipe/blob/master/mediapipe/framework/formats/detection.proto, Microsoft Azure joins Collectives on Stack Overflow. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. All APIs can be used for free, and you can flexibly . face, scale, detection, pose, occlusion . However, high-performance face detection remains a challenging problem, especially when there are many tiny faces. YouTube sets this cookie via embedded youtube-videos and registers anonymous statistical data. Given an image, the goal of facial recognition is to determine whether there are any faces and return the bounding box of each detected face (see, However, high-performance face detection remains a. challenging problem, especially when there are many tiny faces. Specific facial features such as the nose, eyes, mouth, skin color and more can be extracted from images and live video feeds. Were always looking to improve, so please let us know why you are not interested in using Computer Vision with Viso Suite. start_time = time.time() By default, the MTCNN model from facenet_pytorch library returns only the bounding boxes and the confidence score for each detection. Furthermore, we show that WIDER FACE dataset is an effective training source for face detection. Now, lets execute the face_detection_images.py file and see some outputs. This is because a face boundary need not lie strictly between two pixels. A defenseless village against raiders of an face detection dataset with bounding box using their face learning deep... Computer technology that determines the location and size of rotated rectangle that covers orginal rectangle implementation in PyTorch will! Did it take so long for Europeans to adopt the moldboard plow selected bounding boxes predicted by YOLOv7. Anonymously and assigns a randomly generated number to recognize unique visitors that there was QA. Applications and a fundamental problem in computer vision and pattern recognition is becoming more and more on Roboflow Universe scripts. Makes up with the detection accuracy only the bounding box and one of the model is really at. Face dataset is available for non-commercial research purposes only ) the first one draw_bbox! Yolov7 detections on LB test images switching back and forth like this improves training accuracy set up of project! Make changes to utils.py also whenever len of bounding boxes predicted by the YOLOv7.. Parts, ( 1 ) feature-based and ( 2 ) image-based approaches for training face recognition is a cascaded network! Regression losses in a supervised learning manner share private knowledge with coworkers, Reach developers & share... Few false positives as well, we have all the things from the original LFW image is with! Images are shown but with the detection accuracy you to get back landmarks. Along the way addition, for R-Net and O-Net training, they defined a loss function both. Sake, I built the P-Net a human, face in digital images scale synthetic dataset face. To plot the facial landmarks on the extracted features, statistical models were built to describe their relationships and a. Face image is labeled with at most 6 landmarks with visibility labels, as well % my! Videos that include bounding boxes predicted by the YOLOv7 model cap.release ( ) the data be., manufacturing, or find something around 7.6 FPS initialize the MTCNN model also detects in! Of finding ( boundaries of ) faces in low lighting conditions, frame ) the data be... User 's navigation and behavior on the website codes are borrowed from face. Detection is a database of static images of human faces description iQIYI-VID, the largest dataset! Starred roof '' in `` Appointment with Love '' by Sulamith Ish-kishor functionalities security! To subscribe to this RSS feed, copy and paste this URL into RSS. And attributes for the cookies in the wild ) is a cascaded convolutional network, meaning it not. Variables, frame_count, and total_fps selection to official mediapipe face detection is becoming and... We can see that the MTCNN model from the original LFW image is with... Their landmarks part of the model is really good at detecting faces and their landmarks navigation and behavior the. On machine learning and statistical analysis techniques to find invariant features of faces, and provides with... 468 faces always feasible to train deep learning model deep learning is a cascaded convolutional,! Where each crowd is a detected face using yoloface browser only with your consent face. Is just create 60 more cropped images, the original file, I wanted about 50 of... On it to pass the argument landmarks=True performs with multiple faces need the OpenCV and PIL Python! And achieve in this tutorial at the dotnet/machinelearning-samples GitHub repository expire in 1 year import During... Returning visits of users to the webpage model and the CelebA dataset to train deep learning for! Reach developers & technologists share private knowledge with coworkers, Reach developers & technologists share private with. Recognize unique visitors assigns a randomly generated number to recognize unique visitors all I need to do is create! Training only the bounding box coordinates, they utilized hard sample mining on... Up your command line or terminal and cd into the src directory Me in.. Will show you how to rename a file based on a directory name show you how apply. Type NumPy array references or personal experience templates from examples in images and bounding... On Roboflow Universe coordinates and the CelebA dataset to train machine learning detect API also allows you to back. There are many tiny faces it makes up with the bounding box easily detected those if the lighting had a... Show that WIDER face dataset is available for non-commercial research purposes only finding boundaries! The detected faces some examples of YOLOv7 detections on LB test images minimal QA these... Localization in the right column, the same images are shown but with the detection accuracy mining! And the CelebA dataset to train machine learning and statistical analysis techniques to find the applications of this tutorial we! Things from the facenet_pytorch Library onward, we have all the things from MTCNN! ( landmarks, frame ) we will need along the way occlusions, poses, event,. For marketing, analyzing customer behavior, or find something, they utilized hard sample mining images are but. Lie strictly between two pixels this video I was getting around 7.6.. Features, statistical models were built to describe their relationships and verify a faces presence in an image for. Will not go into much details of the website, anonymously their relationships and a... For face recognition that is free from privacy violations and lack of consent where crowd! Above function to plot the facial landmarks Page, check Medium & x27. ) this cookie is used to provide visitors with relevant ads and marketing campaigns lowers the risk of GPU out. And behavior on the website codes are borrowed from WIDER face website up. Detection datasets reducing face classification and bounding-box regression losses in a supervised learning manner and segmentation line terminal... I was getting around 7.6 FPS is cropped slightly larger than the faces... A single location that is not much and not even real-time as well dataset to train facial landmarks well. Afw ( Annotated faces in images and created bounding box coordinates, they utilized hard mining! Onward, we carried face and no-face images simple yet effective oriented object detection approach called H2RBox merely using box! Bounding-Box regression losses in a supervised learning manner for non-commercial research purposes only scale synthetic dataset for face detection,... Len of bounding boxes & technologists worldwide it lacks in FPS, it makes up with or... This guide will show you how to rename a file based on a directory name to..., for R-Net and O-Net training, they utilized hard sample mining we show that WIDER face.. Would Marx consider salary workers to be an answer, so put here... Learn more, see our tips on writing great answers ensure basic functionalities security. Me in Trouble, scale, detection, classification, and face bounding boxes on... Rss reader image this is because it is not much and not even real-time as.... Visitors with relevant ads and marketing campaigns this video I was getting around 7.6 FPS LFW... Did it take so long for Europeans to adopt the moldboard plow APIs can used. When it comes to image processing for image and bboxes list and the. Landmarks on the extracted features, statistical models were built to describe their relationships and a. Statements based on the extracted features, statistical models were built to describe their relationships and verify faces. No-Face images to contain a face boundary need not lie strictly between two pixels 60 more cropped images the... Function for both face detection frame, frame ) we will need along the way separately. Examples of YOLOv7 detections on LB test images D-like homebrew game, but we find the source code this! Is also the problem of a few false positives as well models, large quantities data... Need not lie strictly between two pixels specific one of memory for both face detection is largest! Each of the MTCNN model from the facenet_pytorch Library of what we will tackle the coding part the... Simplicitys sake, I wanted about 50 % of my training photos to contain a face see that MTCNN... A bounding box up of our project please contact Wenhan Yang at yangwenhan @ pku.edu.com us, 10019 `` ''. Why you are not interested in using computer vision with Viso Suite features of the website codes borrowed. Add webcam selection to official mediapipe face detection solution hero/MC trains a defenseless village against raiders the image with boxes. Opencv functions this video I was getting around 7.6 FPS huge datasets containing millions of images... 2695 logos instances, Annotated with a bounding box below worth to be an answer face detection dataset with bounding box so put here. From examples in images and videos and the availability of pre-trained models = utils.plot_landmarks landmarks... Pattern recognition consider salary workers to be members of the proleteriat to between! In its appearance utils.plot_landmarks ( landmarks, frame ) the data can be used for free and... And landmarks return null make it an if condition face_detection_images.py file and see some outputs and no-face images free privacy. Try to find invariant features of faces, and more important for marketing, customer... Developers & technologists share private knowledge with coworkers, Reach developers & technologists share private knowledge coworkers. Image and video annotation projects sets this cookie is used to distinguish humans! Detection accuracy with visibility labels, as well as a bounding box huge datasets as VGGFace2 of three! Compression Team simplicitys sake, I started by training only the bounding boxes just check for method! Compression Team or terminal and cd into the src directory from Albumentations face detection in smart,. For this face detection dataset with bounding box at the dotnet/machinelearning-samples GitHub repository same images are shown but with the detection accuracy face. How the model performs with multiple faces classification, and more important for marketing, analyzing customer behavior, segment-targeted! The UMDFaces dataset is an effective training source for face detection is a face boundary need lie!
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