![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2F06a29def24c04283ad2be76db56ecc34%2Ffacefake.jpg?generation=1576317185647868&alt=media\")
Aligned Face Dataset\nWith images taken from Pinterest, this dataset includes over 10,000 images of 100 different celebrities. There is an average of 100 images included of each celebrity.
CelebA Dataset\nFor non-commercial research purposes only, this dataset from MMLAB contains over 200,000 celebrity images.
Face Detection in Images with Bounding Boxes\nA simple, yet useful dataset, Face Detection in Images contains just over 500 images with approximately 1,100 faces already tagged with bounding boxes.
Face Images with Marked Landmark Points\nThis dataset includes over 7,000 facial images with keypoints annotated on every image. The number of keypoints on each image varies, with the max number of keypoints being 15 on a single image. The keypoints data is included in a separate CSV file.
Flickr Faces\nWith images taken from Flickr, this dataset has 210,000 images. The total image count is made up of 70,000 original images from Flickr, 70,000 images cropped at 1024 x 1024 pixels, and 70,000 cropped at 128 x 128 pixels.
Google Facial Expression Comparison\nFrom Google AI comes the Google Facial Expression Comparison dataset which includes 156,000 facial images. The images come in triplets, with two images out of each triplet annotated as the “most similar” in the triplet in terms of facial expression. In true Google fashion, these images were meticulously annotated and each triplet was worked on by at least six separate human annotators.
Labeled Faces in the Wild\nCreated by researchers at the University of Massachusetts, this dataset was originally made to study unconstrained face recognition. It totals over 13,000 images of over 5,700 people. The dataset also includes helpful metadata in CSV format.
Real and Fake Face Detection\nThis dataset was made to train facial recognition models to distinguish real face images from generated face images. The dataset includes over 1,000 real face images and over 900 fake face images which vary from easy, mid, and hard recognition difficulty.
Simpsons Faces\nWith images taken from seasons 25 to 28 of the popular American cartoon series, this dataset includes over 9,800 cropped faces of Simpsons characters.
Tufts Face Database\nWith over 100,000 images, the Tufts Face Database includes a huge collection of facial images divided into nine categories. The categories include computerized sketches, thermal, thermal cropped, three dimensional, Lytro, 2D RGB around, 2D RGB emotion, night vision, and video.
UMDFaces\nBy far the largest dataset on this list, the UMDFaces dataset has over 367,000 face annotations across over 8,200 different subjects in still images. Apart from those images, the dataset also includes over 3.7 million video frames all annotated with facial keypoints of over 3,100 subjects. It should be noted that this dataset is strictly for non-commercial research purposes only.
UTKFace\nThe UTKFace dataset includes faces from a wide age range. The people in these images range from less than a year old to over 100 years old. The dataset includes over 20,000 face images with age, gender, and ethnicity annotations.
Wider Face\nThis dataset contains over 10,000 images that include multiple people or just a single person. The images are divided into numerous settings such as meetings, traffic, parades, and more.
Yale Face Database\nThe Yale Face Database is a dataset containing 165 GIF images of 15 different subjects in a variety of lighting conditions. The subjects in the images display different emotions and expressions.
Youtube Faces with Facial Keypoints\nThis dataset is composed of public Youtube videos of celebrities which total 155,560 still frames. The videos have been cropped around the faces of the celebrities and have been annotated with facial keypoints for each frame of every video.
Source: https://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/
", "messages": [ { "id": 694898, "postDate": "2019-12-14T09:53:12.547Z", "content": "
Aligned Face Dataset\nWith images taken from Pinterest, this dataset includes over 10,000 images of 100 different celebrities. There is an average of 100 images included of each celebrity.
CelebA Dataset\nFor non-commercial research purposes only, this dataset from MMLAB contains over 200,000 celebrity images.
Face Detection in Images with Bounding Boxes\nA simple, yet useful dataset, Face Detection in Images contains just over 500 images with approximately 1,100 faces already tagged with bounding boxes.
Face Images with Marked Landmark Points\nThis dataset includes over 7,000 facial images with keypoints annotated on every image. The number of keypoints on each image varies, with the max number of keypoints being 15 on a single image. The keypoints data is included in a separate CSV file.
Flickr Faces\nWith images taken from Flickr, this dataset has 210,000 images. The total image count is made up of 70,000 original images from Flickr, 70,000 images cropped at 1024 x 1024 pixels, and 70,000 cropped at 128 x 128 pixels.
Google Facial Expression Comparison\nFrom Google AI comes the Google Facial Expression Comparison dataset which includes 156,000 facial images. The images come in triplets, with two images out of each triplet annotated as the “most similar” in the triplet in terms of facial expression. In true Google fashion, these images were meticulously annotated and each triplet was worked on by at least six separate human annotators.
Labeled Faces in the Wild\nCreated by researchers at the University of Massachusetts, this dataset was originally made to study unconstrained face recognition. It totals over 13,000 images of over 5,700 people. The dataset also includes helpful metadata in CSV format.
Real and Fake Face Detection\nThis dataset was made to train facial recognition models to distinguish real face images from generated face images. The dataset includes over 1,000 real face images and over 900 fake face images which vary from easy, mid, and hard recognition difficulty.
Simpsons Faces\nWith images taken from seasons 25 to 28 of the popular American cartoon series, this dataset includes over 9,800 cropped faces of Simpsons characters.
Tufts Face Database\nWith over 100,000 images, the Tufts Face Database includes a huge collection of facial images divided into nine categories. The categories include computerized sketches, thermal, thermal cropped, three dimensional, Lytro, 2D RGB around, 2D RGB emotion, night vision, and video.
UMDFaces\nBy far the largest dataset on this list, the UMDFaces dataset has over 367,000 face annotations across over 8,200 different subjects in still images. Apart from those images, the dataset also includes over 3.7 million video frames all annotated with facial keypoints of over 3,100 subjects. It should be noted that this dataset is strictly for non-commercial research purposes only.
UTKFace\nThe UTKFace dataset includes faces from a wide age range. The people in these images range from less than a year old to over 100 years old. The dataset includes over 20,000 face images with age, gender, and ethnicity annotations.
Wider Face\nThis dataset contains over 10,000 images that include multiple people or just a single person. The images are divided into numerous settings such as meetings, traffic, parades, and more.
Yale Face Database\nThe Yale Face Database is a dataset containing 165 GIF images of 15 different subjects in a variety of lighting conditions. The subjects in the images display different emotions and expressions.
Youtube Faces with Facial Keypoints\nThis dataset is composed of public Youtube videos of celebrities which total 155,560 still frames. The videos have been cropped around the faces of the celebrities and have been annotated with facial keypoints for each frame of every video.
Source: https://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/
", "rawMarkdown": "\n\n1. [Aligned Face Dataset](https://www.kaggle.com/frules11/pins-face-recognition)\nWith images taken from Pinterest, this dataset includes over 10,000 images of 100 different celebrities. There is an average of 100 images included of each celebrity.\n\n2. [CelebA Dataset](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html)\nFor non-commercial research purposes only, this dataset from MMLAB contains over 200,000 celebrity images.\n\n3. [Face Detection in Images with Bounding Boxes](https://dataturks.com/projects/devika.mishra/face_detection)\nA simple, yet useful dataset, Face Detection in Images contains just over 500 images with approximately 1,100 faces already tagged with bounding boxes.\n\n\n4. [Face Images with Marked Landmark Points](https://www.kaggle.com/drgilermo/face-images-with-marked-landmark-points)\nThis dataset includes over 7,000 facial images with keypoints annotated on every image. The number of keypoints on each image varies, with the max number of keypoints being 15 on a single image. The keypoints data is included in a separate CSV file.\n\n5. [Flickr Faces](https://github.com/NVlabs/ffhq-dataset)\nWith images taken from Flickr, this dataset has 210,000 images. The total image count is made up of 70,000 original images from Flickr, 70,000 images cropped at 1024 x 1024 pixels, and 70,000 cropped at 128 x 128 pixels.\n\n6. [Google Facial Expression Comparison](https://ai.google/tools/datasets/google-facial-expression/)\nFrom Google AI comes the Google Facial Expression Comparison dataset which includes 156,000 facial images. The images come in triplets, with two images out of each triplet annotated as the “most similar” in the triplet in terms of facial expression. In true Google fashion, these images were meticulously annotated and each triplet was worked on by at least six separate human annotators.\n\n7. [Labeled Faces in the Wild](https://www.kaggle.com/jessicali9530/lfw-dataset)\nCreated by researchers at the University of Massachusetts, this dataset was originally made to study unconstrained face recognition. It totals over 13,000 images of over 5,700 people. The dataset also includes helpful metadata in CSV format.\n\n8. [Real and Fake Face Detection](https://www.kaggle.com/ciplab/real-and-fake-face-detection)\nThis dataset was made to train facial recognition models to distinguish real face images from generated face images. The dataset includes over 1,000 real face images and over 900 fake face images which vary from easy, mid, and hard recognition difficulty.\n\n9. [Simpsons Faces](https://www.kaggle.com/kostastokis/simpsons-faces)\nWith images taken from seasons 25 to 28 of the popular American cartoon series, this dataset includes over 9,800 cropped faces of Simpsons characters.\n\n10. [Tufts Face Database](https://www.kaggle.com/kpvisionlab/tufts-face-database)\nWith over 100,000 images, the Tufts Face Database includes a huge collection of facial images divided into nine categories. The categories include computerized sketches, thermal, thermal cropped, three dimensional, Lytro, 2D RGB around, 2D RGB emotion, night vision, and video.\n\n11. [UMDFaces](https://www.umdfaces.io/)\nBy far the largest dataset on this list, the UMDFaces dataset has over 367,000 face annotations across over 8,200 different subjects in still images. Apart from those images, the dataset also includes over 3.7 million video frames all annotated with facial keypoints of over 3,100 subjects. It should be noted that this dataset is strictly for non-commercial research purposes only.\n\n12. [UTKFace](https://susanqq.github.io/UTKFace/)\nThe UTKFace dataset includes faces from a wide age range. The people in these images range from less than a year old to over 100 years old. The dataset includes over 20,000 face images with age, gender, and ethnicity annotations.\n\n13. [Wider Face](https://www.kaggle.com/mksaad/wider-face-a-face-detection-benchmark)\nThis dataset contains over 10,000 images that include multiple people or just a single person. The images are divided into numerous settings such as meetings, traffic, parades, and more.\n\n14. [Yale Face Database](https://www.kaggle.com/olgabelitskaya/yale-face-database)\nThe Yale Face Database is a dataset containing 165 GIF images of 15 different subjects in a variety of lighting conditions. The subjects in the images display different emotions and expressions.\n\n15. [Youtube Faces with Facial Keypoints](https://www.kaggle.com/selfishgene/youtube-faces-with-facial-keypoints)\nThis dataset is composed of public Youtube videos of celebrities which total 155,560 still frames. The videos have been cropped around the faces of the celebrities and have been annotated with facial keypoints for each frame of every video.\n\nSource: https://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/", "votes": 62 }, { "id": 854428, "postDate": "2020-05-20T02:47:11.150Z", "content": "Actually this article was originally mine published here:
\n\nhttps://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/
\n\nYou should be attributing your source when you copy and paste something.
", "rawMarkdown": "Actually this article was originally mine published here:\n\nhttps://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/\n\nYou should be attributing your source when you copy and paste something.", "votes": 19, "replies": [ { "id": 879490, "postDate": "2020-06-09T14:08:33.577Z", "content": "even after the case of plagiarism by famous youtube, people are still doing this and not even citing the original author😑
", "rawMarkdown": "even after the case of plagiarism by famous youtube, people are still doing this and not even citing the original author😑 " }, { "id": 880037, "postDate": "2020-06-10T00:22:53.107Z", "content": "Yes unfortunately many people don't know the basic practices of citing sources to avoid plagiarism
", "rawMarkdown": "Yes unfortunately many people don't know the basic practices of citing sources to avoid plagiarism" }, { "id": 896125, "postDate": "2020-06-21T21:55:05.333Z", "content": "@limarcambalina sorry, I was thinking that I am already sited the source, I added it now, and if you want I can delete this article, sorry again, you can verify that I am always citing people\"s work
", "rawMarkdown": "@limarcambalina sorry, I was thinking that I am already sited the source, I added it now, and if you want I can delete this article, sorry again, you can verify that I am always citing people\"s work", "votes": -2 }, { "id": 896214, "postDate": "2020-06-22T01:15:39.400Z", "content": "Thanks for citing
", "rawMarkdown": "Thanks for citing", "votes": 1 }, { "id": 897359, "postDate": "2020-06-22T19:54:22.103Z", "content": "sorry again @limarcambalina
", "rawMarkdown": "sorry again @limarcambalina ", "votes": -2 } ] }, { "id": 838300, "postDate": "2020-05-08T13:05:03.663Z", "content": "Thanks!
", "rawMarkdown": "Thanks!", "votes": 1, "replies": [ { "id": 839162, "postDate": "2020-05-09T05:58:23.293Z", "content": "You are welcome
", "rawMarkdown": "You are welcome", "votes": -3 } ] }, { "id": 837655, "postDate": "2020-05-07T23:43:08.147Z", "content": "Nice compilation. Thanks!
", "rawMarkdown": "Nice compilation. Thanks!", "votes": 1, "replies": [ { "id": 839161, "postDate": "2020-05-09T05:58:09.503Z", "content": "You are welcome
", "rawMarkdown": "You are welcome", "votes": -3 }, { "id": 854430, "postDate": "2020-05-20T02:47:45.797Z", "content": "Actually Tarek, this article was originally mine published here:
\n\nhttps://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/
\n\nYou should be attributing your source when you copy and paste something.
", "rawMarkdown": "Actually Tarek, this article was originally mine published here:\n\nhttps://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/\n\nYou should be attributing your source when you copy and paste something.", "votes": 4 }, { "id": 896126, "postDate": "2020-06-21T21:55:26.920Z", "content": "@limarcambalina sorry, I was thinking that I am already sited the source, I added it now, and if you want I can delete this article, sorry again, you can verify that I am always citing people\"s work
", "rawMarkdown": "@limarcambalina sorry, I was thinking that I am already sited the source, I added it now, and if you want I can delete this article, sorry again, you can verify that I am always citing people\"s work", "votes": -1 }, { "id": 896216, "postDate": "2020-06-22T01:16:17.640Z", "content": "thanks for citing
", "rawMarkdown": "thanks for citing", "votes": 1 }, { "id": 897355, "postDate": "2020-06-22T19:53:44.170Z", "content": "sorry again @limarcambalina
", "rawMarkdown": "sorry again @limarcambalina ", "votes": -1 } ] }, { "id": 836825, "postDate": "2020-05-07T09:19:05.497Z", "content": "Thank you !
", "rawMarkdown": "Thank you !", "votes": 1, "replies": [ { "id": 839160, "postDate": "2020-05-09T05:57:55.067Z", "content": "You are welcome
", "rawMarkdown": "You are welcome", "votes": -2 }, { "id": 872183, "postDate": "2020-06-03T01:31:37.500Z", "rawMarkdown": "", "votes": 2, "isDeleted": true } ] }, { "id": 804425, "postDate": "2020-04-11T15:13:29.350Z", "content": "Bookmarked, Thank You @hamditarek
", "rawMarkdown": "Bookmarked, Thank You @hamditarek ", "votes": 1, "replies": [ { "id": 839159, "postDate": "2020-05-09T05:57:38.390Z", "content": "You are welcome
", "rawMarkdown": "You are welcome", "votes": -2 } ] }, { "id": 699224, "postDate": "2019-12-20T07:45:32.627Z", "content": "That's helpful :) Thank you :)
", "rawMarkdown": "That's helpful :) Thank you :) ", "votes": 1, "replies": [ { "id": 699762, "postDate": "2019-12-20T21:31:29.813Z", "content": "You are welcome
", "rawMarkdown": "You are welcome", "votes": -1 } ] }, { "id": 697681, "postDate": "2019-12-18T09:07:03.093Z", "content": "Thanks @hamditarek for sharing this data-sets 😊
", "rawMarkdown": "Thanks @hamditarek for sharing this data-sets 😊 ", "votes": 1, "replies": [ { "id": 697907, "postDate": "2019-12-18T14:39:24.950Z", "content": "You are welcome
", "rawMarkdown": "You are welcome", "votes": -1 } ] }, { "id": 696914, "postDate": "2019-12-17T08:18:49.977Z", "content": "Bookmarked, Thanks :100:
", "rawMarkdown": "Bookmarked, Thanks :100:", "votes": 1, "replies": [ { "id": 697141, "postDate": "2019-12-17T14:25:58.887Z", "content": "You are welcome
", "rawMarkdown": "You are welcome", "votes": -1 } ] }, { "id": 697287, "postDate": "2019-12-17T17:20:07.697Z", "content": "gonna use this in my project , thanks!
", "rawMarkdown": "gonna use this in my project , thanks!", "votes": 2, "replies": [ { "id": 697906, "postDate": "2019-12-18T14:39:00.353Z", "content": "You are welcome
", "rawMarkdown": "You are welcome", "votes": -2 } ] }, { "id": 902736, "postDate": "2020-06-26T10:24:02.503Z", "rawMarkdown": "", "isDeleted": true }, { "id": 1255786, "postDate": "2021-03-29T07:40:22.817Z", "content": "Thank you !
", "rawMarkdown": "Thank you !" }, { "id": 852783, "postDate": "2020-05-18T17:12:15.147Z", "content": "Thanks
", "rawMarkdown": "Thanks " } ], "comments": [ { "id": 854428, "author_name": "LionHeart", "author_url": "", "post_date": "2020-05-20T02:47:11.150000", "content": "Actually this article was originally mine published here:
\n\nhttps://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/
\n\nYou should be attributing your source when you copy and paste something.
", "votes": 19, "replies": [ { "id": 879490, "author_name": "Manoj Balaji J", "author_url": "", "post_date": "2020-06-09T14:08:33.577000", "content": "even after the case of plagiarism by famous youtube, people are still doing this and not even citing the original author😑
", "votes": 0, "replies": [] }, { "id": 880037, "author_name": "LionHeart", "author_url": "", "post_date": "2020-06-10T00:22:53.107000", "content": "Yes unfortunately many people don't know the basic practices of citing sources to avoid plagiarism
", "votes": 0, "replies": [] }, { "id": 896125, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-06-21T21:55:05.333000", "content": "@limarcambalina sorry, I was thinking that I am already sited the source, I added it now, and if you want I can delete this article, sorry again, you can verify that I am always citing people\"s work
", "votes": -2, "replies": [] }, { "id": 896214, "author_name": "LionHeart", "author_url": "", "post_date": "2020-06-22T01:15:39.400000", "content": "Thanks for citing
", "votes": 1, "replies": [] }, { "id": 897359, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-06-22T19:54:22.103000", "content": "sorry again @limarcambalina
", "votes": -2, "replies": [] } ] }, { "id": 838300, "author_name": "Tiago Provenzano", "author_url": "", "post_date": "2020-05-08T13:05:03.663000", "content": "Thanks!
", "votes": 1, "replies": [ { "id": 839162, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-05-09T05:58:23.293000", "content": "You are welcome
", "votes": -3, "replies": [] } ] }, { "id": 837655, "author_name": "Baran Sahin", "author_url": "", "post_date": "2020-05-07T23:43:08.147000", "content": "Nice compilation. Thanks!
", "votes": 1, "replies": [ { "id": 839161, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-05-09T05:58:09.503000", "content": "You are welcome
", "votes": -3, "replies": [] }, { "id": 854430, "author_name": "LionHeart", "author_url": "", "post_date": "2020-05-20T02:47:45.797000", "content": "Actually Tarek, this article was originally mine published here:
\n\nhttps://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/
\n\nYou should be attributing your source when you copy and paste something.
", "votes": 4, "replies": [] }, { "id": 896126, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-06-21T21:55:26.920000", "content": "@limarcambalina sorry, I was thinking that I am already sited the source, I added it now, and if you want I can delete this article, sorry again, you can verify that I am always citing people\"s work
", "votes": -1, "replies": [] }, { "id": 896216, "author_name": "LionHeart", "author_url": "", "post_date": "2020-06-22T01:16:17.640000", "content": "thanks for citing
", "votes": 1, "replies": [] }, { "id": 897355, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-06-22T19:53:44.170000", "content": "sorry again @limarcambalina
", "votes": -1, "replies": [] } ] }, { "id": 836825, "author_name": "Terence Cai", "author_url": "", "post_date": "2020-05-07T09:19:05.497000", "content": "Thank you !
", "votes": 1, "replies": [ { "id": 839160, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-05-09T05:57:55.067000", "content": "You are welcome
", "votes": -2, "replies": [] }, { "id": 872183, "author_name": "", "author_url": "", "post_date": "2020-06-03T01:31:37.500000", "content": "", "votes": 2, "replies": [] } ] }, { "id": 804425, "author_name": "Shaitender Singh", "author_url": "", "post_date": "2020-04-11T15:13:29.350000", "content": "Bookmarked, Thank You @hamditarek
", "votes": 1, "replies": [ { "id": 839159, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-05-09T05:57:38.390000", "content": "You are welcome
", "votes": -2, "replies": [] } ] }, { "id": 699224, "author_name": "Sachin Prabhu", "author_url": "", "post_date": "2019-12-20T07:45:32.627000", "content": "That's helpful :) Thank you :)
", "votes": 1, "replies": [ { "id": 699762, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-12-20T21:31:29.813000", "content": "You are welcome
", "votes": -1, "replies": [] } ] }, { "id": 697681, "author_name": "Mohamed Abdullah", "author_url": "", "post_date": "2019-12-18T09:07:03.093000", "content": "Thanks @hamditarek for sharing this data-sets 😊
", "votes": 1, "replies": [ { "id": 697907, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-12-18T14:39:24.950000", "content": "You are welcome
", "votes": -1, "replies": [] } ] }, { "id": 696914, "author_name": "dasmehdixtr", "author_url": "", "post_date": "2019-12-17T08:18:49.977000", "content": "Bookmarked, Thanks :100:
", "votes": 1, "replies": [ { "id": 697141, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-12-17T14:25:58.887000", "content": "You are welcome
", "votes": -1, "replies": [] } ] }, { "id": 697287, "author_name": "ravi tanwar", "author_url": "", "post_date": "2019-12-17T17:20:07.697000", "content": "gonna use this in my project , thanks!
", "votes": 2, "replies": [ { "id": 697906, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-12-18T14:39:00.353000", "content": "You are welcome
", "votes": -2, "replies": [] } ] }, { "id": 902736, "author_name": "", "author_url": "", "post_date": "2020-06-26T10:24:02.503000", "content": "", "votes": 0, "replies": [] }, { "id": 1255786, "author_name": "AbdulQayoom Abro", "author_url": "", "post_date": "2021-03-29T07:40:22.817000", "content": "Thank you !
", "votes": 0, "replies": [] }, { "id": 852783, "author_name": "Sumit Maan", "author_url": "", "post_date": "2020-05-18T17:12:15.147000", "content": "Thanks
", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "694898": "\n\n1. [Aligned Face Dataset](https://www.kaggle.com/frules11/pins-face-recognition)\nWith images taken from Pinterest, this dataset includes over 10,000 images of 100 different celebrities. There is an average of 100 images included of each celebrity.\n\n2. [CelebA Dataset](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html)\nFor non-commercial research purposes only, this dataset from MMLAB contains over 200,000 celebrity images.\n\n3. [Face Detection in Images with Bounding Boxes](https://dataturks.com/projects/devika.mishra/face_detection)\nA simple, yet useful dataset, Face Detection in Images contains just over 500 images with approximately 1,100 faces already tagged with bounding boxes.\n\n\n4. [Face Images with Marked Landmark Points](https://www.kaggle.com/drgilermo/face-images-with-marked-landmark-points)\nThis dataset includes over 7,000 facial images with keypoints annotated on every image. The number of keypoints on each image varies, with the max number of keypoints being 15 on a single image. The keypoints data is included in a separate CSV file.\n\n5. [Flickr Faces](https://github.com/NVlabs/ffhq-dataset)\nWith images taken from Flickr, this dataset has 210,000 images. The total image count is made up of 70,000 original images from Flickr, 70,000 images cropped at 1024 x 1024 pixels, and 70,000 cropped at 128 x 128 pixels.\n\n6. [Google Facial Expression Comparison](https://ai.google/tools/datasets/google-facial-expression/)\nFrom Google AI comes the Google Facial Expression Comparison dataset which includes 156,000 facial images. The images come in triplets, with two images out of each triplet annotated as the “most similar” in the triplet in terms of facial expression. In true Google fashion, these images were meticulously annotated and each triplet was worked on by at least six separate human annotators.\n\n7. [Labeled Faces in the Wild](https://www.kaggle.com/jessicali9530/lfw-dataset)\nCreated by researchers at the University of Massachusetts, this dataset was originally made to study unconstrained face recognition. It totals over 13,000 images of over 5,700 people. The dataset also includes helpful metadata in CSV format.\n\n8. [Real and Fake Face Detection](https://www.kaggle.com/ciplab/real-and-fake-face-detection)\nThis dataset was made to train facial recognition models to distinguish real face images from generated face images. The dataset includes over 1,000 real face images and over 900 fake face images which vary from easy, mid, and hard recognition difficulty.\n\n9. [Simpsons Faces](https://www.kaggle.com/kostastokis/simpsons-faces)\nWith images taken from seasons 25 to 28 of the popular American cartoon series, this dataset includes over 9,800 cropped faces of Simpsons characters.\n\n10. [Tufts Face Database](https://www.kaggle.com/kpvisionlab/tufts-face-database)\nWith over 100,000 images, the Tufts Face Database includes a huge collection of facial images divided into nine categories. The categories include computerized sketches, thermal, thermal cropped, three dimensional, Lytro, 2D RGB around, 2D RGB emotion, night vision, and video.\n\n11. [UMDFaces](https://www.umdfaces.io/)\nBy far the largest dataset on this list, the UMDFaces dataset has over 367,000 face annotations across over 8,200 different subjects in still images. Apart from those images, the dataset also includes over 3.7 million video frames all annotated with facial keypoints of over 3,100 subjects. It should be noted that this dataset is strictly for non-commercial research purposes only.\n\n12. [UTKFace](https://susanqq.github.io/UTKFace/)\nThe UTKFace dataset includes faces from a wide age range. The people in these images range from less than a year old to over 100 years old. The dataset includes over 20,000 face images with age, gender, and ethnicity annotations.\n\n13. [Wider Face](https://www.kaggle.com/mksaad/wider-face-a-face-detection-benchmark)\nThis dataset contains over 10,000 images that include multiple people or just a single person. The images are divided into numerous settings such as meetings, traffic, parades, and more.\n\n14. [Yale Face Database](https://www.kaggle.com/olgabelitskaya/yale-face-database)\nThe Yale Face Database is a dataset containing 165 GIF images of 15 different subjects in a variety of lighting conditions. The subjects in the images display different emotions and expressions.\n\n15. [Youtube Faces with Facial Keypoints](https://www.kaggle.com/selfishgene/youtube-faces-with-facial-keypoints)\nThis dataset is composed of public Youtube videos of celebrities which total 155,560 still frames. The videos have been cropped around the faces of the celebrities and have been annotated with facial keypoints for each frame of every video.\n\nSource: https://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/", "854428": "Actually this article was originally mine published here:\n\nhttps://lionbridge.ai/datasets/5-million-faces-top-15-free-image-datasets-for-facial-recognition/\n\nYou should be attributing your source when you copy and paste something.", "838300": "Thanks!", "837655": "Nice compilation. Thanks!", "836825": "Thank you !", "804425": "Bookmarked, Thank You @hamditarek ", "699224": "That's helpful :) Thank you :) ", "697681": "Thanks @hamditarek for sharing this data-sets 😊 ", "696914": "Bookmarked, Thanks :100:", "697287": "gonna use this in my project , thanks!", "902736": "", "1255786": "Thank you !", "852783": "Thanks " } }